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Merge remote-tracking branch 'origin/3.0' into fix/3.0_bugfix_wxy

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Xiaoyu Wang 2022-08-29 10:28:14 +08:00
parent 4895f19876 ee6ff78497
commit 381f48241f
155 changed files with 8190 additions and 4535 deletions
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2
cmake/cmake.define
View File

@ -2,8 +2,6 @@ cmake_minimum_required(VERSION 3.0)
set(CMAKE_VERBOSE_MAKEFILE OFF)
SET(BUILD_SHARED_LIBS "OFF")
#set output directory
SET(LIBRARY_OUTPUT_PATH ${PROJECT_BINARY_DIR}/build/lib)
SET(EXECUTABLE_OUTPUT_PATH ${PROJECT_BINARY_DIR}/build/bin)

16
cmake/cmake.install
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@ -1,3 +1,19 @@
SET(PREPARE_ENV_CMD "prepare_env_cmd")
SET(PREPARE_ENV_TARGET "prepare_env_target")
ADD_CUSTOM_COMMAND(OUTPUT ${PREPARE_ENV_CMD}
POST_BUILD
COMMAND echo "make test directory"
DEPENDS taosd
COMMAND ${CMAKE_COMMAND} -E make_directory ${TD_TESTS_OUTPUT_DIR}/cfg/
COMMAND ${CMAKE_COMMAND} -E make_directory ${TD_TESTS_OUTPUT_DIR}/log/
COMMAND ${CMAKE_COMMAND} -E make_directory ${TD_TESTS_OUTPUT_DIR}/data/
COMMAND ${CMAKE_COMMAND} -E echo dataDir ${TD_TESTS_OUTPUT_DIR}/data > ${TD_TESTS_OUTPUT_DIR}/cfg/taos.cfg
COMMAND ${CMAKE_COMMAND} -E echo logDir ${TD_TESTS_OUTPUT_DIR}/log >> ${TD_TESTS_OUTPUT_DIR}/cfg/taos.cfg
COMMAND ${CMAKE_COMMAND} -E echo charset UTF-8 >> ${TD_TESTS_OUTPUT_DIR}/cfg/taos.cfg
COMMAND ${CMAKE_COMMAND} -E echo monitor 0 >> ${TD_TESTS_OUTPUT_DIR}/cfg/taos.cfg
COMMENT "prepare taosd environment")
ADD_CUSTOM_TARGET(${PREPARE_ENV_TARGET} ALL WORKING_DIRECTORY ${TD_EXECUTABLE_OUTPUT_PATH} DEPENDS ${PREPARE_ENV_CMD})
IF (TD_LINUX)
SET(TD_MAKE_INSTALL_SH "${TD_SOURCE_DIR}/packaging/tools/make_install.sh")
INSTALL(CODE "MESSAGE(\"make install script: ${TD_MAKE_INSTALL_SH}\")")

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cmake/cmake.options
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@ -90,6 +90,12 @@ ELSE ()
ENDIF ()
ENDIF ()
option(
BUILD_SHARED_LIBS
""
OFF
)
option(
RUST_BINDINGS
"If build with rust-bindings"

2
cmake/taostools_CMakeLists.txt.in
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@ -2,7 +2,7 @@
# taos-tools
ExternalProject_Add(taos-tools
GIT_REPOSITORY https://github.com/taosdata/taos-tools.git
GIT_TAG 833b721
GIT_TAG e8bfca6
SOURCE_DIR "${TD_SOURCE_DIR}/tools/taos-tools"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE

44
docs/en/02-intro/index.md
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@ -3,7 +3,7 @@ title: Introduction
toc_max_heading_level: 2
---
TDengine is an open source, high-performance, cloud native [time-series database](https://tdengine.com/tsdb/) optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. Its code, including its cluster feature is open source under GNU AGPL v3.0. Besides the database engine, it provides [caching](../develop/cache), [stream processing](../develop/stream), [data subscription](../develop/tmq) and other functionalities to reduce the system complexity and cost of development and operation.
TDengine is an open source, high-performance, cloud native [time-series database](https://tdengine.com/tsdb/) optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. Its code, including its cluster feature is open source under GNU AGPL v3.0. Besides the database engine, it provides [caching](/develop/cache), [stream processing](/develop/stream), [data subscription](/develop/tmq) and other functionalities to reduce the system complexity and cost of development and operation.
This section introduces the major features, competitive advantages, typical use-cases and benchmarks to help you get a high level overview of TDengine.
@ -11,21 +11,33 @@ This section introduces the major features, competitive advantages, typical use-
The major features are listed below:
1. While TDengine supports [using SQL to insert](/develop/insert-data/sql-writing), it also supports [Schemaless writing](/reference/schemaless/) just like NoSQL databases. TDengine also supports standard protocols like [InfluxDB LINE](/develop/insert-data/influxdb-line)，[OpenTSDB Telnet](/develop/insert-data/opentsdb-telnet), [OpenTSDB JSON ](/develop/insert-data/opentsdb-json) among others.
2. TDengine supports seamless integration with third-party data collection agents like [Telegraf](/third-party/telegraf)，[Prometheus](/third-party/prometheus)，[StatsD](/third-party/statsd)，[collectd](/third-party/collectd)，[icinga2](/third-party/icinga2), [TCollector](/third-party/tcollector), [EMQX](/third-party/emq-broker), [HiveMQ](/third-party/hive-mq-broker). These agents can write data into TDengine with simple configuration and without a single line of code.
3. Support for [all kinds of queries](/develop/query-data), including aggregation, nested query, downsampling, interpolation and others.
4. Support for [user defined functions](/develop/udf).
5. Support for [caching](/develop/cache). TDengine always saves the last data point in cache, so Redis is not needed in some scenarios.
6. Support for [continuous query](../develop/stream).
7. Support for [data subscription](../develop/tmq) with the capability to specify filter conditions.
8. Support for [cluster](../deployment/), with the capability of increasing processing power by adding more nodes. High availability is supported by replication.
9. Provides an interactive [command-line interface](/reference/taos-shell) for management, maintenance and ad-hoc queries.
10. Provides many ways to [import](/operation/import) and [export](/operation/export) data.
11. Provides [monitoring](/operation/monitor) on running instances of TDengine.
12. Provides [connectors](/reference/connector/) for [C/C++](/reference/connector/cpp), [Java](/reference/connector/java), [Python](/reference/connector/python), [Go](/reference/connector/go), [Rust](/reference/connector/rust), [Node.js](/reference/connector/node) and other programming languages.
13. Provides a [REST API](/reference/rest-api/).
14. Supports seamless integration with [Grafana](/third-party/grafana) for visualization.
15. Supports seamless integration with Google Data Studio.
1. Insert data
* supports [using SQL to insert](/develop/insert-data/sql-writing).
* supports [schemaless writing](/reference/schemaless/) just like NoSQL databases. It also supports standard protocols like [InfluxDB LINE](/develop/insert-data/influxdb-line)，[OpenTSDB Telnet](/develop/insert-data/opentsdb-telnet), [OpenTSDB JSON ](/develop/insert-data/opentsdb-json) among others.
* supports seamless integration with third-party tools like [Telegraf](/third-party/telegraf/), [Prometheus](/third-party/prometheus/), [collectd](/third-party/collectd/), [StatsD](/third-party/statsd/), [TCollector](/third-party/tcollector/) and [icinga2/](/third-party/icinga2/), they can write data into TDengine with simple configuration and without a single line of code.
2. Query data
* supports standard [SQL](/taos-sql/), including nested query.
* supports [time series specific functions](/taos-sql/function/#time-series-extensions) and [time series specific queries](/taos-sql/distinguished), like downsampling, interpolation, cumulated sum, time weighted average, state window, session window and many others.
* supports [user defined functions](/taos-sql/udf).
3. [Caching](/develop/cache/): TDengine always saves the last data point in cache, so Redis is not needed for time-series data processing.
4. [Stream Processing](/develop/stream/): not only is the continuous query is supported, but TDengine also supports even driven stream processing, so Flink or spark is not needed for time-series daata processing.
5. [Data Dubscription](/develop/tmq/): application can subscribe a table or a set of tables. API is the same as Kafka, but you can specify filter conditions.
6. Visualization
* supports seamless integration with [Grafana](/third-party/grafana/) for visualization.
* supports seamless integration with Google Data Studio.
7. Cluster
* supports [cluster](/deployment/) with the capability of increasing processing power by adding more nodes.
* supports [deployment on Kubernetes](/deployment/k8s/)
* supports high availability via data replication.
8. Administration
* provides [monitoring](/operation/monitor) on running instances of TDengine.
* provides many ways to [import](/operation/import) and [export](/operation/export) data.
9. Tools
* provides an interactive [command-line interface](/reference/taos-shell) for management, maintenance and ad-hoc queries.
* provides a tool [taosBenchmark](/reference/taosbenchmark/) for testing the performance of TDengine.
10. Programming
* provides [connectors](/reference/connector/) for [C/C++](/reference/connector/cpp), [Java](/reference/connector/java), [Python](/reference/connector/python), [Go](/reference/connector/go), [Rust](/reference/connector/rust), [Node.js](/reference/connector/node) and other programming languages.
* provides a [REST API](/reference/rest-api/).
For more details on features, please read through the entire documentation.

444
docs/en/07-develop/03-insert-data/05-high-volume.md Normal file
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@ -0,0 +1,444 @@
---
sidebar_label: High Performance Writing
title: High Performance Writing
---
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
This chapter introduces how to write data into TDengine with high throughput.
## How to achieve high performance data writing
To achieve high performance writing, there are a few aspects to consider. In the following sections we will describe these important factors in achieving high performance writing.
### Application Program
From the perspective of application program, you need to consider:
1. The data size of each single write, also known as batch size. Generally speaking, higher batch size generates better writing performance. However, once the batch size is over a specific value, you will not get any additional benefit anymore. When using SQL to write into TDengine, it's better to put as much as possible data in single SQL. The maximum SQL length supported by TDengine is 1,048,576 bytes, i.e. 1 MB. It can be configured by parameter `maxSQLLength` on client side, and the default value is 65,480.
2. The number of concurrent connections. Normally more connections can get better result. However, once the number of connections exceeds the processing ability of the server side, the performance may downgrade.
3. The distribution of data to be written across tables or sub-tables. Writing to single table in one batch is more efficient than writing to multiple tables in one batch.
4. Data Writing Protocol.
- Prameter binding mode is more efficient than SQL because it doesn't have the cost of parsing SQL.
- Writing to known existing tables is more efficient than wirting to uncertain tables in automatic creating mode because the later needs to check whether the table exists or not before actually writing data into it
- Writing in SQL is more efficient than writing in schemaless mode because schemaless writing creats table automatically and may alter table schema
Application programs need to take care of the above factors and try to take advantage of them. The application progam should write to single table in each write batch. The batch size needs to be tuned to a proper value on a specific system. The number of concurrent connections needs to be tuned to a proper value too to achieve the best writing throughput.
### Data Source
Application programs need to read data from data source then write into TDengine. If you meet one or more of below situations, you need to setup message queues between the threads for reading from data source and the threads for writing into TDengine.
1. There are multiple data sources, the data generation speed of each data source is much slower than the speed of single writing thread. In this case, the purpose of message queues is to consolidate the data from multiple data sources together to increase the batch size of single write.
2. The speed of data generation from single data source is much higher than the speed of single writing thread. The purpose of message queue in this case is to provide buffer so that data is not lost and multiple writing threads can get data from the buffer.
3. The data for single table are from multiple data source. In this case the purpose of message queues is to combine the data for single table together to improve the write efficiency.
If the data source is Kafka, then the appication program is a consumer of Kafka, you can benefit from some kafka features to achieve high performance writing:
1. Put the data for a table in single partition of single topic so that it's easier to put the data for each table together and write in batch
2. Subscribe multiple topics to accumulate data together.
3. Add more consumers to gain more concurrency and throughput.
4. Incrase the size of single fetch to increase the size of write batch.
### Tune TDengine
TDengine is a distributed and high performance time series database, there are also some ways to tune TDengine to get better writing performance.
1. Set proper number of `vgroups` according to available CPU cores. Normally, we recommend 2 \* number_of_cores as a starting point. If the verification result shows this is not enough to utilize CPU resources, you can use a higher value.
2. Set proper `minTablesPerVnode`, `tableIncStepPerVnode`, and `maxVgroupsPerDb` according to the number of tables so that tables are distributed even across vgroups. The purpose is to balance the workload among all vnodes so that system resources can be utilized better to get higher performance.
For more performance tuning parameters, please refer to [Configuration Parameters](../../../reference/config).
## Sample Programs
This section will introduce the sample programs to demonstrate how to write into TDengine with high performance.
### Scenario
Below are the scenario for the sample programs of high performance wrting.
- Application program reads data from data source, the sample program simulates a data source by generating data
- The speed of single writing thread is much slower than the speed of generating data, so the program starts multiple writing threads while each thread establish a connection to TDengine and each thread has a message queue of fixed size.
- Application program maps the received data to different writing threads based on table name to make sure all the data for each table is always processed by a specific writing thread.
- Each writing thread writes the received data into TDengine once the message queue becomes empty or the read data meets a threshold.
![Thread Model of High Performance Writing into TDengine](highvolume.webp)
### Sample Programs
The sample programs listed in this section are based on the scenario described previously. If your scenarios is different, please try to adjust the code based on the principles described in this chapter.
The sample programs assume the source data is for all the different sub tables in same super table (meters). The super table has been created before the sample program starts to writing data. Sub tables are created automatically according to received data. If there are multiple super tables in your case, please try to adjust the part of creating table automatically.
<Tabs defaultValue="java" groupId="lang">
<TabItem label="Java" value="java">
**Program Inventory**
| Class | Description |
| ---------------- | ----------------------------------------------------------------------------------------------------- |
| FastWriteExample | Main Program |
| ReadTask | Read data from simulated data source and put into a queue according to the hash value of table name |
| WriteTask | Read data from Queue, compose a wirte batch and write into TDengine |
| MockDataSource | Generate data for some sub tables of super table meters |
| SQLWriter | WriteTask uses this class to compose SQL, create table automatically, check SQL length and write data |
| StmtWriter | Write in Parameter binding mode (Not finished yet) |
| DataBaseMonitor | Calculate the writing speed and output on console every 10 seconds |
Below is the list of complete code of the classes in above table and more detailed description.
<details>
<summary>FastWriteExample</summary>
The main Program is responsible for:
1. Create message queues
2. Start writing threads
3. Start reading threads
4. Otuput writing speed every 10 seconds
The main program provides 4 parameters for tuning：
1. The number of reading threads, default value is 1
2. The number of writing threads, default alue is 2
3. The total number of tables in the generated data, default value is 1000. These tables are distributed evenly across all writing threads. If the number of tables is very big, it will cost much time to firstly create these tables.
4. The batch size of single write, default value is 3,000
The capacity of message queue also impacts performance and can be tuned by modifying program. Normally it's always better to have a larger message queue. A larger message queue means lower possibility of being blocked when enqueueing and higher throughput. But a larger message queue consumes more memory space. The default value used in the sample programs is already big enoug.
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/FastWriteExample.java}}
```
</details>
<details>
<summary>ReadTask</summary>
ReadTask reads data from data source. Each ReadTask is associated with a simulated data source, each data source generates data for a group of specific tables, and the data of any table is only generated from a single specific data source.
ReadTask puts data in message queue in blocking mode. That means, the putting operation is blocked if the message queue is full.
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/ReadTask.java}}
```
</details>
<details>
<summary>WriteTask</summary>
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/WriteTask.java}}
```
</details>
<details>
<summary>MockDataSource</summary>
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/MockDataSource.java}}
```
</details>
<details>
<summary>SQLWriter</summary>
SQLWriter class encapsulates the logic of composing SQL and writing data. Please be noted that the tables have not been created before writing, but are created automatically when catching the exception of table doesn't exist. For other exceptions caught, the SQL which caused the exception are logged for you to debug.
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/SQLWriter.java}}
```
</details>
<details>
<summary>DataBaseMonitor</summary>
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/DataBaseMonitor.java}}
```
</details>
**Steps to Launch**
<details>
<summary>Launch Java Sample Program</summary>
You need to set environment variable `TDENGINE_JDBC_URL` before launching the program. If TDengine Server is setup on localhost, then the default value for user name, password and port can be used, like below:
```
TDENGINE_JDBC_URL="jdbc:TAOS://localhost:6030?user=root&password=taosdata"
```
**Launch in IDE**
1. Clone TDengine repolitory
```
git clone git@github.com:taosdata/TDengine.git --depth 1
```
2. Use IDE to open `docs/examples/java` directory
3. Configure environment variable `TDENGINE_JDBC_URL`, you can also configure it before launching the IDE, if so you can skip this step.
4. Run class `com.taos.example.highvolume.FastWriteExample`
**Launch on server**
If you want to launch the sample program on a remote server, please follow below steps:
1. Package the sample programs. Execute below command under directory `TDengine/docs/examples/java` ：
```
mvn package
```
2. Create `examples/java` directory on the server
```
mkdir -p examples/java
```
3. Copy dependencies (below commands assume you are working on a local Windows host and try to launch on a remote Linux host)
- Copy dependent packages
```
scp -r .\target\lib <user>@<host>:~/examples/java
```
- Copy the jar of sample programs
```
scp -r .\target\javaexample-1.0.jar <user>@<host>:~/examples/java
```
4. Configure environment variable
Edit `~/.bash_profile` or `~/.bashrc` and add below:
```
export TDENGINE_JDBC_URL="jdbc:TAOS://localhost:6030?user=root&password=taosdata"
```
If your TDengine server is not deployed on localhost or doesn't use default port, you need to change the above URL to correct value in your environment.
5. Launch the sample program
```
java -classpath lib/*:javaexample-1.0.jar com.taos.example.highvolume.FastWriteExample <read_thread_count> <white_thread_count> <total_table_count> <max_batch_size>
```
6. The sample program doesn't exit unless you press <kbd>CTRL</kbd> + <kbd>C</kbd> to terminate it.
Below is the output of running on a server of 16 cores, 64GB memory and SSD hard disk.
```
root@vm85$ java -classpath lib/*:javaexample-1.0.jar com.taos.example.highvolume.FastWriteExample 2 12
18:56:35.896 [main] INFO c.t.e.highvolume.FastWriteExample - readTaskCount=2, writeTaskCount=12 tableCount=1000 maxBatchSize=3000
18:56:36.011 [WriteThread-0] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.015 [WriteThread-0] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.021 [WriteThread-1] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.022 [WriteThread-1] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.031 [WriteThread-2] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.032 [WriteThread-2] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.041 [WriteThread-3] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.042 [WriteThread-3] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.093 [WriteThread-4] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.094 [WriteThread-4] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.099 [WriteThread-5] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.100 [WriteThread-5] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.100 [WriteThread-6] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.101 [WriteThread-6] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.103 [WriteThread-7] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.104 [WriteThread-7] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.105 [WriteThread-8] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.107 [WriteThread-8] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.108 [WriteThread-9] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.109 [WriteThread-9] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.156 [WriteThread-10] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.157 [WriteThread-11] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.158 [WriteThread-10] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.158 [ReadThread-0] INFO com.taos.example.highvolume.ReadTask - started
18:56:36.158 [ReadThread-1] INFO com.taos.example.highvolume.ReadTask - started
18:56:36.158 [WriteThread-11] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:46.369 [main] INFO c.t.e.highvolume.FastWriteExample - count=18554448 speed=1855444
18:56:56.946 [main] INFO c.t.e.highvolume.FastWriteExample - count=39059660 speed=2050521
18:57:07.322 [main] INFO c.t.e.highvolume.FastWriteExample - count=59403604 speed=2034394
18:57:18.032 [main] INFO c.t.e.highvolume.FastWriteExample - count=80262938 speed=2085933
18:57:28.432 [main] INFO c.t.e.highvolume.FastWriteExample - count=101139906 speed=2087696
18:57:38.921 [main] INFO c.t.e.highvolume.FastWriteExample - count=121807202 speed=2066729
18:57:49.375 [main] INFO c.t.e.highvolume.FastWriteExample - count=142952417 speed=2114521
18:58:00.689 [main] INFO c.t.e.highvolume.FastWriteExample - count=163650306 speed=2069788
18:58:11.646 [main] INFO c.t.e.highvolume.FastWriteExample - count=185019808 speed=2136950
```
</details>
</TabItem>
<TabItem label="Python" value="python">
**Program Inventory**
Sample programs in Python uses multi-process and cross-process message queues.
| Function/CLass | Description |
| ---------------------------- | --------------------------------------------------------------------------- |
| main Function | Program entry point, create child processes and message queues |
| run_monitor_process Function | Create database, super table, calculate writing speed and output to console |
| run_read_task Function | Read data and distribute to message queues |
| MockDataSource Class | Simulate data source, return next 1,000 rows of each table |
| run_write_task Function | Read as much as possible data from message queue and write in batch |
| SQLWriter Class | Write in SQL and create table utomatically |
| StmtWriter Class | Write in parameter binding mode (not finished yet) |
<details>
<summary>main function</summary>
`main` function is responsible for creating message queues and fork child processes, there are 3 kinds of child processes:
1. Monitoring process, initializes database and calculating writing speed
2. Reading process (n), reads data from data source
3. Writing process (m), wirtes data into TDengine
`main` function provides 5 parameters:
1. The number of reading tasks, default value is 1
2. The number of writing tasks, default value is 1
3. The number of tables, default value is 1,000
4. The capacity of message queue, default value is 1,000,000 bytes
5. The batch size in single write, default value is 3000
```python
{{#include docs/examples/python/fast_write_example.py:main}}
```
</details>
<details>
<summary>run_monitor_process</summary>
Monitoring process initilizes database and monitoring writing speed.
```python
{{#include docs/examples/python/fast_write_example.py:monitor}}
```
</details>
<details>
<summary>run_read_task function</summary>
Reading process reads data from other data system and distributes to the message queue allocated for it.
```python
{{#include docs/examples/python/fast_write_example.py:read}}
```
</details>
<details>
<summary>MockDataSource</summary>
Below is the simulated data source, we assume table name exists in each generated data.
```python
{{#include docs/examples/python/mockdatasource.py}}
```
</details>
<details>
<summary>run_write_task function</summary>
Writing process tries to read as much as possible data from message queue and writes in batch.
```python
{{#include docs/examples/python/fast_write_example.py:write}}
```
</details>
<details>
SQLWriter class encapsulates the logic of composing SQL and writing data. Please be noted that the tables have not been created before writing, but are created automatically when catching the exception of table doesn't exist. For other exceptions caught, the SQL which caused the exception are logged for you to debug. This class also checks the SQL length, if the SQL length is closed to `maxSQLLength` the SQL will be executed immediately. To improve writing efficiency, it's better to increase `maxSQLLength` properly.
<summary>SQLWriter</summary>
```python
{{#include docs/examples/python/sql_writer.py}}
```
</details>
**Steps to Launch**
<details>
<summary>Launch Sample Program in Python</summary>
1. Prerequisities
- TDengine client driver has been installed
- Python3 has been installed, the the version >= 3.8
- TDengine Python connector `taospy` has been installed
2. Install faster-fifo to replace python builtin multiprocessing.Queue
```
pip3 install faster-fifo
```
3. Click the "Copy" in the above sample programs to copy `fast_write_example.py` 、 `sql_writer.py` and `mockdatasource.py`.
4. Execute the program
```
python3 fast_write_example.py <READ_TASK_COUNT> <WRITE_TASK_COUNT> <TABLE_COUNT> <QUEUE_SIZE> <MAX_BATCH_SIZE>
```
Below is the output of running on a server of 16 cores, 64GB memory and SSD hard disk.
```
root@vm85$ python3 fast_write_example.py 8 8
2022-07-14 19:13:45,869 [root] - READ_TASK_COUNT=8, WRITE_TASK_COUNT=8, TABLE_COUNT=1000, QUEUE_SIZE=1000000, MAX_BATCH_SIZE=3000
2022-07-14 19:13:48,882 [root] - WriteTask-0 started with pid 718347
2022-07-14 19:13:48,883 [root] - WriteTask-1 started with pid 718348
2022-07-14 19:13:48,884 [root] - WriteTask-2 started with pid 718349
2022-07-14 19:13:48,884 [root] - WriteTask-3 started with pid 718350
2022-07-14 19:13:48,885 [root] - WriteTask-4 started with pid 718351
2022-07-14 19:13:48,885 [root] - WriteTask-5 started with pid 718352
2022-07-14 19:13:48,886 [root] - WriteTask-6 started with pid 718353
2022-07-14 19:13:48,886 [root] - WriteTask-7 started with pid 718354
2022-07-14 19:13:48,887 [root] - ReadTask-0 started with pid 718355
2022-07-14 19:13:48,888 [root] - ReadTask-1 started with pid 718356
2022-07-14 19:13:48,889 [root] - ReadTask-2 started with pid 718357
2022-07-14 19:13:48,889 [root] - ReadTask-3 started with pid 718358
2022-07-14 19:13:48,890 [root] - ReadTask-4 started with pid 718359
2022-07-14 19:13:48,891 [root] - ReadTask-5 started with pid 718361
2022-07-14 19:13:48,892 [root] - ReadTask-6 started with pid 718364
2022-07-14 19:13:48,893 [root] - ReadTask-7 started with pid 718365
2022-07-14 19:13:56,042 [DataBaseMonitor] - count=6676310 speed=667631.0
2022-07-14 19:14:06,196 [DataBaseMonitor] - count=20004310 speed=1332800.0
2022-07-14 19:14:16,366 [DataBaseMonitor] - count=32290310 speed=1228600.0
2022-07-14 19:14:26,527 [DataBaseMonitor] - count=44438310 speed=1214800.0
2022-07-14 19:14:36,673 [DataBaseMonitor] - count=56608310 speed=1217000.0
2022-07-14 19:14:46,834 [DataBaseMonitor] - count=68757310 speed=1214900.0
2022-07-14 19:14:57,280 [DataBaseMonitor] - count=80992310 speed=1223500.0
2022-07-14 19:15:07,689 [DataBaseMonitor] - count=93805310 speed=1281300.0
2022-07-14 19:15:18,020 [DataBaseMonitor] - count=106111310 speed=1230600.0
2022-07-14 19:15:28,356 [DataBaseMonitor] - count=118394310 speed=1228300.0
2022-07-14 19:15:38,690 [DataBaseMonitor] - count=130742310 speed=1234800.0
2022-07-14 19:15:49,000 [DataBaseMonitor] - count=143051310 speed=1230900.0
2022-07-14 19:15:59,323 [DataBaseMonitor] - count=155276310 speed=1222500.0
2022-07-14 19:16:09,649 [DataBaseMonitor] - count=167603310 speed=1232700.0
2022-07-14 19:16:19,995 [DataBaseMonitor] - count=179976310 speed=1237300.0
```
</details>
:::note
Don't establish connection to TDengine in the parent process if using Python connector in multi-process way, otherwise all the connections in child processes are blocked always. This is a known issue.
:::
</TabItem>
</Tabs>

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@ -20,11 +20,11 @@ In theory, larger cache sizes are always better. However, at a certain point, it
## Read Cache
When you create a database, you can configure whether the latest data from every subtable is cached. To do so, set the *cachelast* parameter as follows:
- 0: Caching is disabled.
- 1: The latest row of data in each subtable is cached. This option significantly improves the performance of the `LAST_ROW` function
- 2: The latest non-null value in each column of each subtable is cached. This option significantly improves the performance of the `LAST` function in normal situations, such as WHERE, ORDER BY, GROUP BY, and INTERVAL statements.
- 3: Rows and columns are both cached. This option is equivalent to simultaneously enabling options 1 and 2.
When you create a database, you can configure whether the latest data from every subtable is cached. To do so, set the *cachemodel* parameter as follows:
- none: Caching is disabled.
- last_row: The latest row of data in each subtable is cached. This option significantly improves the performance of the `LAST_ROW` function
- last_value: The latest non-null value in each column of each subtable is cached. This option significantly improves the performance of the `LAST` function in normal situations, such as WHERE, ORDER BY, GROUP BY, and INTERVAL statements.
- both: Rows and columns are both cached. This option is equivalent to simultaneously enabling option last_row and last_value.
## Metadata Cache

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@ -114,7 +114,9 @@ The above process can be repeated to add more dnodes in the cluster.
Any node that is in the cluster and online can be the firstEp of new nodes.
Nodes use the firstEp parameter only when joining a cluster for the first time. After a node has joined the cluster, it stores the latest mnode in its end point list and no longer makes use of firstEp.
However, firstEp is used by clients that connect to the cluster. For example, if you run `taos shell` without arguments, it connects to the firstEp by default.
However, firstEp is used by clients that connect to the cluster. For example, if you run TDengine CLI `taos` without arguments, it connects to the firstEp by default.
Two dnodes that are launched without a firstEp value operate independently of each other. It is not possible to add one dnode to the other dnode and form a cluster. It is also not possible to form two independent clusters into a new cluster.
:::

3
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@ -9,6 +9,7 @@ TDengine is a cloud-native time-series database that can be deployed on Kubernet
Before deploying TDengine on Kubernetes, perform the following:
* Current steps are compatible with Kubernetes v1.5 and later version.
* Install and configure minikube, kubectl, and helm.
* Install and deploy Kubernetes and ensure that it can be accessed and used normally. Update any container registries or other services as necessary.
@ -100,7 +101,7 @@ spec:
# Must set if you want a cluster.
- name: TAOS_FIRST_EP
value: "$(STS_NAME)-0.$(SERVICE_NAME).$(STS_NAMESPACE).svc.cluster.local:$(TAOS_SERVER_PORT)"
# TAOS_FQND should always be setted in k8s env.
# TAOS_FQDN should always be set in k8s env.
- name: TAOS_FQDN
value: "$(POD_NAME).$(SERVICE_NAME).$(STS_NAMESPACE).svc.cluster.local"
volumeMounts:

2
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@ -57,7 +57,7 @@ table_option: {
3. MAX_DELAY: specifies the maximum latency for pushing computation results. The default value is 15 minutes or the value of the INTERVAL parameter, whichever is smaller. Enter a value between 0 and 15 minutes in milliseconds, seconds, or minutes. You can enter multiple values separated by commas (,). Note: Retain the default value if possible. Configuring a small MAX_DELAY may cause results to be frequently pushed, affecting storage and query performance. This parameter applies only to supertables and takes effect only when the RETENTIONS parameter has been specified for the database.
4. ROLLUP: specifies aggregate functions to roll up. Rolling up a function provides downsampled results based on multiple axes. This parameter applies only to supertables and takes effect only when the RETENTIONS parameter has been specified for the database. You can specify only one function to roll up. The rollup takes effect on all columns except TS. Enter one of the following values: avg, sum, min, max, last, or first.
5. SMA: specifies functions on which to enable small materialized aggregates (SMA). SMA is user-defined precomputation of aggregates based on data blocks. Enter one of the following values: max, min, or sum This parameter can be used with supertables and standard tables.
6. TTL: specifies the time to live (TTL) for the table. If the period specified by the TTL parameter elapses without any data being written to the table, TDengine will automatically delete the table. Note: The system may not delete the table at the exact moment that the TTL expires. Enter a value in days. The default value is 0. Note: The TTL parameter has a higher priority than the KEEP parameter. If a table is marked for deletion because the TTL has expired, it will be deleted even if the time specified by the KEEP parameter has not elapsed. This parameter can be used with standard tables and subtables.
6. TTL: specifies the time to live (TTL) for the table. If TTL is specified when creatinga table, after the time period for which the table has been existing is over TTL, TDengine will automatically delete the table. Please be noted that the system may not delete the table at the exact moment that the TTL expires but guarantee there is such a system and finally the table will be deleted. The unit of TTL is in days. The default value is 0, i.e. never expire.
## Create Subtables

4
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@ -1139,7 +1139,7 @@ SELECT STATECOUNT(field_name, oper, val) FROM { tb_name | stb_name } [WHERE clau
**Applicable parameter values**:
- oper : Can be one of `LT` (lower than), `GT` (greater than), `LE` (lower than or equal to), `GE` (greater than or equal to), `NE` (not equal to), `EQ` (equal to), the value is case insensitive
- oper : Can be one of `'LT'` (lower than), `'GT'` (greater than), `'LE'` (lower than or equal to), `'GE'` (greater than or equal to), `'NE'` (not equal to), `'EQ'` (equal to), the value is case insensitive, the value must be in quotes.
- val ： Numeric types
**Return value type**: Integer
@ -1166,7 +1166,7 @@ SELECT stateDuration(field_name, oper, val, unit) FROM { tb_name | stb_name } [W
**Applicable parameter values**:
- oper : Can be one of `LT` (lower than), `GT` (greater than), `LE` (lower than or equal to), `GE` (greater than or equal to), `NE` (not equal to), `EQ` (equal to), the value is case insensitive
- oper : Can be one of `'LT'` (lower than), `'GT'` (greater than), `'LE'` (lower than or equal to), `'GE'` (greater than or equal to), `'NE'` (not equal to), `'EQ'` (equal to), the value is case insensitive, the value must be in quotes.
- val ： Numeric types
- unit: The unit of time interval. Enter one of the following options: 1b (nanoseconds), 1u (microseconds), 1a (milliseconds), 1s (seconds), 1m (minutes), 1h (hours), 1d (days), or 1w (weeks) If you do not enter a unit of time, the precision of the current database is used by default.

2
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@ -30,7 +30,7 @@ The following characters cannot occur in a password: single quotation marks ('),
- Maximum number of columns is 4096. There must be at least 2 columns, and the first column must be timestamp.
- The maximum length of a tag name is 64 bytes
- Maximum number of tags is 128. There must be at least 1 tag. The total length of tag values cannot exceed 16 KB.
- Maximum length of single SQL statement is 1 MB (1048576 bytes). It can be configured in the parameter `maxSQLLength` in the client side, the applicable range is [65480, 1048576].
- Maximum length of single SQL statement is 1 MB (1048576 bytes).
- At most 4096 columns can be returned by `SELECT`. Functions in the query statement constitute columns. An error is returned if the limit is exceeded.
- Maximum numbers of databases, STables, tables are dependent only on the system resources.
- The number of replicas can only be 1 or 3.

2
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@ -194,7 +194,7 @@ Shows information about streams in the system.
SHOW SUBSCRIPTIONS;
```
Shows all subscriptions in the current database.
Shows all subscriptions in the system.
## SHOW TABLES

141
docs/en/13-operation/01-pkg-install.md
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@ -1,12 +1,12 @@
---
title: Install & Uninstall
title: Install and Uninstall
description: Install, Uninstall, Start, Stop and Upgrade
---
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
TDengine community version provides deb and rpm packages for users to choose from, based on their system environment. The deb package supports Debian, Ubuntu and derivative systems. The rpm package supports CentOS, RHEL, SUSE and derivative systems. Furthermore, a tar.gz package is provided for TDengine Enterprise customers.
This document gives more information about installing, uninstalling, and upgrading TDengine.
## Install
@ -35,12 +35,28 @@ TDengine is removed successfully!
```
Apt-get package of taosTools can be uninstalled as below:
```
$ sudo apt remove taostools
Reading package lists... Done
Building dependency tree
Reading state information... Done
The following packages will be REMOVED:
taostools
0 upgraded, 0 newly installed, 1 to remove and 0 not upgraded.
After this operation, 68.3 MB disk space will be freed.
Do you want to continue? [Y/n]
(Reading database ... 147973 files and directories currently installed.)
Removing taostools (2.1.2) ...
```
</TabItem>
<TabItem label="Uninstall Deb" value="debuninst">
Deb package of TDengine can be uninstalled as below:
```bash
```
$ sudo dpkg -r tdengine
(Reading database ... 137504 files and directories currently installed.)
Removing tdengine (3.0.0.0) ...
@ -48,6 +64,14 @@ TDengine is removed successfully!
```
Deb package of taosTools can be uninstalled as below:
```
$ sudo dpkg -r taostools
(Reading database ... 147973 files and directories currently installed.)
Removing taostools (2.1.2) ...
```
</TabItem>
<TabItem label="Uninstall RPM" value="rpmuninst">
@ -59,6 +83,13 @@ $ sudo rpm -e tdengine
TDengine is removed successfully!
```
RPM package of taosTools can be uninstalled as below:
```
sudo rpm -e taostools
taosToole is removed successfully!
```
</TabItem>
<TabItem label="Uninstall tar.gz" value="taruninst">
@ -67,115 +98,69 @@ tar.gz package of TDengine can be uninstalled as below:
```
$ rmtaos
Nginx for TDengine is running, stopping it...
TDengine is removed successfully!
```
taosKeeper is removed successfully!
tar.gz package of taosTools can be uninstalled as below:
```
$ rmtaostools
Start to uninstall taos tools ...
taos tools is uninstalled successfully!
```
</TabItem>
<TabItem label="Windows uninstall" value="windows">
Run C:\TDengine\unins000.exe to uninstall TDengine on a Windows system.
</TabItem>
</Tabs>
:::note
:::info
- We strongly recommend not to use multiple kinds of installation packages on a single host TDengine.
- After deb package is installed, if the installation directory is removed manually, uninstall or reinstall will not work. This issue can be resolved by using the command below which cleans up TDengine package information. You can then reinstall if needed.
- We strongly recommend not to use multiple kinds of installation packages on a single host TDengine. The packages may affect each other and cause errors.
```bash
$ sudo rm -f /var/lib/dpkg/info/tdengine*
```
- After deb package is installed, if the installation directory is removed manually, uninstall or reinstall will not work. This issue can be resolved by using the command below which cleans up TDengine package information.
- After rpm package is installed, if the installation directory is removed manually, uninstall or reinstall will not work. This issue can be resolved by using the command below which cleans up TDengine package information. You can then reinstall if needed.
```
$ sudo rm -f /var/lib/dpkg/info/tdengine*
```
```bash
$ sudo rpm -e --noscripts tdengine
```
You can then reinstall if needed.
- After rpm package is installed, if the installation directory is removed manually, uninstall or reinstall will not work. This issue can be resolved by using the command below which cleans up TDengine package information.
```
$ sudo rpm -e --noscripts tdengine
```
You can then reinstall if needed.
:::
## Installation Directory
TDengine is installed at /usr/local/taos if successful.
```bash
$ cd /usr/local/taos
$ ll
$ ll
total 28
drwxr-xr-x 7 root root 4096 Feb 22 09:34 ./
drwxr-xr-x 12 root root 4096 Feb 22 09:34 ../
drwxr-xr-x 2 root root 4096 Feb 22 09:34 bin/
drwxr-xr-x 2 root root 4096 Feb 22 09:34 cfg/
lrwxrwxrwx 1 root root 13 Feb 22 09:34 data -> /var/lib/taos/
drwxr-xr-x 2 root root 4096 Feb 22 09:34 driver/
drwxr-xr-x 10 root root 4096 Feb 22 09:34 examples/
drwxr-xr-x 2 root root 4096 Feb 22 09:34 include/
lrwxrwxrwx 1 root root 13 Feb 22 09:34 log -> /var/log/taos/
```
During the installation process:
- Configuration directory, data directory, and log directory are created automatically if they don't exist
- The default configuration file is located at /etc/taos/taos.cfg, which is a copy of /usr/local/taos/cfg/taos.cfg
- The default data directory is /var/lib/taos, which is a soft link to /usr/local/taos/data
- The default log directory is /var/log/taos, which is a soft link to /usr/local/taos/log
- The executables at /usr/local/taos/bin are linked to /usr/bin
- The DLL files at /usr/local/taos/driver are linked to /usr/lib
- The header files at /usr/local/taos/include are linked to /usr/include
:::note
Uninstalling and Modifying Files
- When TDengine is uninstalled, the configuration /etc/taos/taos.cfg, data directory /var/lib/taos, log directory /var/log/taos are kept. They can be deleted manually with caution, because data can't be recovered. Please follow data integrity, security, backup or relevant SOPs before deleting any data.
- When reinstalling TDengine, if the default configuration file /etc/taos/taos.cfg exists, it will be kept and the configuration file in the installation package will be renamed to taos.cfg.orig and stored at /usr/local/taos/cfg to be used as configuration sample. Otherwise the configuration file in the installation package will be installed to /etc/taos/taos.cfg and used.
## Start and Stop
Linux system services `systemd`, `systemctl` or `service` are used to start, stop and restart TDengine. The server process of TDengine is `taosd`, which is started automatically after the Linux system is started. System operators can use `systemd`, `systemctl` or `service` to start, stop or restart TDengine server.
For example, if using `systemctl` , the commands to start, stop, restart and check TDengine server are below:
- Start server：`systemctl start taosd`
- Stop server：`systemctl stop taosd`
- Restart server：`systemctl restart taosd`
- Check server status：`systemctl status taosd`
Another component named as `taosAdapter` is to provide HTTP service for TDengine, it should be started and stopped using `systemctl`.
If the server process is OK, the output of `systemctl status` is like below:
```
Active: active (running)
```
Otherwise, the output is as below:
```
Active: inactive (dead)
```
## Upgrade
There are two aspects in upgrade operation: upgrade installation package and upgrade a running server.
To upgrade a package, follow the steps mentioned previously to first uninstall the old version then install the new version.
Upgrading a running server is much more complex. First please check the version number of the old version and the new version. The version number of TDengine consists of 4 sections, only if the first 3 sections match can the old version be upgraded to the new version. The steps of upgrading a running server are as below:
- Stop inserting data
- Make sure all data is persisted to disk
- Make some simple queries (Such as total rows in stables, tables and so on. Note down the values. Follow best practices and relevant SOPs.)
- Stop the cluster of TDengine
- Uninstall old version and install new version
- Start the cluster of TDengine
- Execute simple queries, such as the ones executed prior to installing the new package, to make sure there is no data loss
- Execute simple queries, such as the ones executed prior to installing the new package, to make sure there is no data loss
- Run some simple data insertion statements to make sure the cluster works well
- Restore business services
:::warning
TDengine doesn't guarantee any lower version is compatible with the data generated by a higher version, so it's never recommended to downgrade the version.
:::

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@ -1,40 +1,32 @@
---
sidebar_label: Resource Planning
title: Resource Planning
---
It is important to plan computing and storage resources if using TDengine to build an IoT, time-series or Big Data platform. How to plan the CPU, memory and disk resources required, will be described in this chapter.
## Memory Requirement of Server Side
## Server Memory Requirements
By default, the number of vgroups created for each database is the same as the number of CPU cores. This can be configured by the parameter `maxVgroupsPerDb`. Each vnode in a vgroup stores one replica. Each vnode consumes a fixed amount of memory, i.e. `blocks` \* `cache`. In addition, some memory is required for tag values associated with each table. A fixed amount of memory is required for each cluster. So, the memory required for each DB can be calculated using the formula below:
Each database creates a fixed number of vgroups. This number is 2 by default and can be configured with the `vgroups` parameter. The number of replicas can be controlled with the `replica` parameter. Each replica requires one vnode per vgroup. Altogether, the memory required by each database depends on the following configuration options:
- vgroups
- replica
- buffer
- pages
- pagesize
- cachesize
For more information, see [Database](../../taos-sql/database).
The memory required by a database is therefore greater than or equal to:
```
Database Memory Size = maxVgroupsPerDb * replica * (blocks * cache + 10MB) + numOfTables * (tagSizePerTable + 0.5KB)
vgroups * replica * (buffer + pages * pagesize + cachesize)
```
For example, assuming the default value of `maxVgroupPerDB` is 64, the default value of `cache` is 16M, the default value of `blocks` is 6, there are 100,000 tables in a DB, the replica number is 1, total length of tag values is 256 bytes, the total memory required for this DB is: 64 \* 1 \* (16 \* 6 + 10) + 100000 \* (0.25 + 0.5) / 1000 = 6792M.
However, note that this requirement is spread over all dnodes in the cluster, not on a single physical machine. The physical servers that run dnodes meet the requirement together. If a cluster has multiple databases, the memory required increases accordingly. In complex environments where dnodes were added after initial deployment in response to increasing resource requirements, load may not be balanced among the original dnodes and newer dnodes. In this situation, the actual status of your dnodes is more important than theoretical calculations.
In the real operation of TDengine, we are more concerned about the memory used by each TDengine server process `taosd`.
```
taosd_memory = vnode_memory + mnode_memory + query_memory
```
In the above formula:
1. "vnode_memory" of a `taosd` process is the memory used by all vnodes hosted by this `taosd` process. It can be roughly calculated by firstly adding up the total memory of all DBs whose memory usage can be derived according to the formula for Database Memory Size, mentioned above, then dividing by number of dnodes and multiplying the number of replicas.
```
vnode_memory = (sum(Database Memory Size) / number_of_dnodes) * replica
```
2. "mnode_memory" of a `taosd` process is the memory consumed by a mnode. If there is one (and only one) mnode hosted in a `taosd` process, the memory consumed by "mnode" is "0.2KB \* the total number of tables in the cluster".
3. "query_memory" is the memory used when processing query requests. Each ongoing query consumes at least "0.2 KB \* total number of involved tables".
Please note that the above formulas can only be used to estimate the minimum memory requirement, instead of maximum memory usage. In a real production environment, it's better to reserve some redundance beyond the estimated minimum memory requirement. If memory is abundant, it's suggested to increase the value of parameter `blocks` to speed up data insertion and data query.
## Memory Requirement of Client Side
## Client Memory Requirements
For the client programs using TDengine client driver `taosc` to connect to the server side there is a memory requirement as well.
@ -56,10 +48,10 @@ So, at least 3GB needs to be reserved for such a client.
The CPU resources required depend on two aspects:
- **Data Insertion** Each dnode of TDengine can process at least 10,000 insertion requests in one second, while each insertion request can have multiple rows. The difference in computing resource consumed, between inserting 1 row at a time, and inserting 10 rows at a time is very small. So, the more the number of rows that can be inserted one time, the higher the efficiency. Inserting in batch also imposes requirements on the client side which needs to cache rows to insert in batch once the number of cached rows reaches a threshold.
- **Data Insertion** Each dnode of TDengine can process at least 10,000 insertion requests in one second, while each insertion request can have multiple rows. The difference in computing resource consumed, between inserting 1 row at a time, and inserting 10 rows at a time is very small. So, the more the number of rows that can be inserted one time, the higher the efficiency. If each insert request contains more than 200 records, a single core can process more than 1 million records per second. Inserting in batch also imposes requirements on the client side which needs to cache rows to insert in batch once the number of cached rows reaches a threshold.
- **Data Query** High efficiency query is provided in TDengine, but it's hard to estimate the CPU resource required because the queries used in different use cases and the frequency of queries vary significantly. It can only be verified with the query statements, query frequency, data size to be queried, and other requirements provided by users.
In short, the CPU resource required for data insertion can be estimated but it's hard to do so for query use cases. In real operation, it's suggested to control CPU usage below 50%. If this threshold is exceeded, it's a reminder for system operator to add more nodes in the cluster to expand resources.
In short, the CPU resource required for data insertion can be estimated but it's hard to do so for query use cases. If possible, ensure that CPU usage remains below 50%. If this threshold is exceeded, it's a reminder for system operator to add more nodes in the cluster to expand resources.
## Disk Requirement
@ -77,6 +69,6 @@ To increase performance, multiple disks can be setup for parallel data reading o
## Number of Hosts
A host can be either physical or virtual. The total memory, total CPU, total disk required can be estimated according to the formulae mentioned previously. Then, according to the system resources that a single host can provide, assuming all hosts have the same resources, the number of hosts can be derived easily.
A host can be either physical or virtual. The total memory, total CPU, total disk required can be estimated according to the formulae mentioned previously. If the number of data replicas is not 1, the required resources are multiplied by the number of replicas.
**Quick Estimation for CPU, Memory and Disk** Please refer to [Resource Estimate](https://www.taosdata.com/config/config.html).
Then, according to the system resources that a single host can provide, assuming all hosts have the same resources, the number of hosts can be derived easily.

20
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@ -1,6 +1,5 @@
---
sidebar_label: Fault Tolerance
title: Fault Tolerance & Disaster Recovery
title: Fault Tolerance and Disaster Recovery
---
## Fault Tolerance
@ -11,22 +10,21 @@ When a data block is received by TDengine, the original data block is first writ
There are 2 configuration parameters related to WAL:
- walLevel：
- 0：wal is disabled
- 1：wal is enabled without fsync
- 2：wal is enabled with fsync
- fsync：This parameter is only valid when walLevel is set to 2. It specifies the interval, in milliseconds, of invoking fsync. If set to 0, it means fsync is invoked immediately once WAL is written.
- wal_level: Specifies the WAL level. 1 indicates that WAL is enabled but fsync is disabled. 2 indicates that WAL and fsync are both enabled. The default value is 1.
- wal_fsync_period: This parameter is only valid when wal_level is set to 2. It specifies the interval, in milliseconds, of invoking fsync. If set to 0, it means fsync is invoked immediately once WAL is written.
To achieve absolutely no data loss, walLevel should be set to 2 and fsync should be set to 1. There is a performance penalty to the data ingestion rate. However, if the concurrent data insertion threads on the client side can reach a big enough number, for example 50, the data ingestion performance will be still good enough. Our verification shows that the drop is only 30% when fsync is set to 3,000 milliseconds.
To achieve absolutely no data loss, set wal_level to 2 and wal_fsync_period to 0. There is a performance penalty to the data ingestion rate. However, if the concurrent data insertion threads on the client side can reach a big enough number, for example 50, the data ingestion performance will be still good enough. Our verification shows that the drop is only 30% when wal_fsync_period is set to 3000 milliseconds.
## Disaster Recovery
TDengine uses replication to provide high availability and disaster recovery capability.
TDengine uses replication to provide high availability.
A TDengine cluster is managed by mnode. To ensure the high availability of mnode, multiple replicas can be configured by the system parameter `numOfMnodes`. The data replication between mnode replicas is performed in a synchronous way to guarantee metadata consistency.
A TDengine cluster is managed by mnodes. You can configure up to three mnodes to ensure high availability. The data replication between mnode replicas is performed in a synchronous way to guarantee metadata consistency.
The number of replicas for time series data in TDengine is associated with each database. There can be many databases in a cluster and each database can be configured with a different number of replicas. When creating a database, parameter `replica` is used to configure the number of replications. To achieve high availability, `replica` needs to be higher than 1.
The number of replicas for time series data in TDengine is associated with each database. There can be many databases in a cluster and each database can be configured with a different number of replicas. When creating a database, the parameter `replica` is used to specify the number of replicas. To achieve high availability, set `replica` to 3.
The number of dnodes in a TDengine cluster must NOT be lower than the number of replicas for any database, otherwise it would fail when trying to create a table.
As long as the dnodes of a TDengine cluster are deployed on different physical machines and the replica number is higher than 1, high availability can be achieved without any other assistance. For disaster recovery, dnodes of a TDengine cluster should be deployed in geographically different data centers.
Alternatively, you can use taosX to synchronize the data from one TDengine cluster to another cluster in a remote location. However, taosX is only available in TDengine enterprise version, for more information please contact tdengine.com.

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@ -13,110 +13,59 @@ Diagnostic steps：
1. If the port range to be diagnosed is being occupied by a `taosd` server process, please first stop `taosd.
2. On the server side, execute command `taos -n server -P <port> -l <pktlen>` to monitor the port range starting from the port specified by `-P` parameter with the role of "server".
3. On the client side, execute command `taos -n client -h <fqdn of server> -P <port> -l <pktlen>` to send a testing package to the specified server and port.
-l <pktlen\>： The size of the testing package, in bytes. The value range is [11, 64,000] and default value is 1,000. Please note that the package length must be same in the above 2 commands executed on server side and client side respectively.
-l <pktlen\>： The size of the testing package, in bytes. The value range is [11, 64,000] and default value is 1,000.
Please note that the package length must be same in the above 2 commands executed on server side and client side respectively.
Output of the server side for the example is below:
```bash
# taos -n server -P 6000
12/21 14:50:13.522509 0x7f536f455200 UTL work as server, host:172.27.0.7 startPort:6000 endPort:6011 pkgLen:1000
12/21 14:50:13.522659 0x7f5352242700 UTL TCP server at port:6000 is listening
12/21 14:50:13.522727 0x7f5351240700 UTL TCP server at port:6001 is listening
# taos -n server -P 6030 -l 1000
network test server is initialized, port:6030
request is received, size:1000
request is received, size:1000
...
...
...
12/21 14:50:13.523954 0x7f5342fed700 UTL TCP server at port:6011 is listening
12/21 14:50:13.523989 0x7f53437ee700 UTL UDP server at port:6010 is listening
12/21 14:50:13.524019 0x7f53427ec700 UTL UDP server at port:6011 is listening
12/21 14:50:22.192849 0x7f5352242700 UTL TCP: read:1000 bytes from 172.27.0.8 at 6000
12/21 14:50:22.192993 0x7f5352242700 UTL TCP: write:1000 bytes to 172.27.0.8 at 6000
12/21 14:50:22.237082 0x7f5351a41700 UTL UDP: recv:1000 bytes from 172.27.0.8 at 6000
12/21 14:50:22.237203 0x7f5351a41700 UTL UDP: send:1000 bytes to 172.27.0.8 at 6000
12/21 14:50:22.237450 0x7f5351240700 UTL TCP: read:1000 bytes from 172.27.0.8 at 6001
12/21 14:50:22.237576 0x7f5351240700 UTL TCP: write:1000 bytes to 172.27.0.8 at 6001
12/21 14:50:22.281038 0x7f5350a3f700 UTL UDP: recv:1000 bytes from 172.27.0.8 at 6001
12/21 14:50:22.281141 0x7f5350a3f700 UTL UDP: send:1000 bytes to 172.27.0.8 at 6001
...
...
...
12/21 14:50:22.677443 0x7f5342fed700 UTL TCP: read:1000 bytes from 172.27.0.8 at 6011
12/21 14:50:22.677576 0x7f5342fed700 UTL TCP: write:1000 bytes to 172.27.0.8 at 6011
12/21 14:50:22.721144 0x7f53427ec700 UTL UDP: recv:1000 bytes from 172.27.0.8 at 6011
12/21 14:50:22.721261 0x7f53427ec700 UTL UDP: send:1000 bytes to 172.27.0.8 at 6011
request is received, size:1000
request is received, size:1000
```
Output of the client side for the example is below:
```bash
# taos -n client -h 172.27.0.7 -P 6000
12/21 14:50:22.192434 0x7fc95d859200 UTL work as client, host:172.27.0.7 startPort:6000 endPort:6011 pkgLen:1000
taos -n client -h v3s2 -P 6030 -l 1000
network test client is initialized, the server is v3s2:6030
request is sent, size:1000
response is received, size:1000
request is sent, size:1000
response is received, size:1000
...
...
...
request is sent, size:1000
response is received, size:1000
request is sent, size:1000
response is received, size:1000
12/21 14:50:22.192472 0x7fc95d859200 UTL server ip:172.27.0.7 is resolved from host:172.27.0.7
12/21 14:50:22.236869 0x7fc95d859200 UTL successed to test TCP port:6000
12/21 14:50:22.237215 0x7fc95d859200 UTL successed to test UDP port:6000
...
...
...
12/21 14:50:22.676891 0x7fc95d859200 UTL successed to test TCP port:6010
12/21 14:50:22.677240 0x7fc95d859200 UTL successed to test UDP port:6010
12/21 14:50:22.720893 0x7fc95d859200 UTL successed to test TCP port:6011
12/21 14:50:22.721274 0x7fc95d859200 UTL successed to test UDP port:6011
total succ: 100/100 cost: 16.23 ms speed: 5.87 MB/s
```
The output needs to be checked carefully for the system operator to find the root cause and resolve the problem.
## Startup Status and RPC Diagnostic
`taos -n startup -h <fqdn of server>` can be used to check the startup status of a `taosd` process. This is a common task which should be performed by a system operator, especially in the case of a cluster, to determine whether `taosd` has been started successfully.
`taos -n rpc -h <fqdn of server>` can be used to check whether the port of a started `taosd` can be accessed or not. If `taosd` process doesn't respond or is working abnormally, this command can be used to initiate a rpc communication with the specified fqdn to determine whether it's a network problem or whether `taosd` is abnormal.
## Sync and Arbitrator Diagnostic
```bash
taos -n sync -P 6040 -h <fqdn of server>
taos -n sync -P 6042 -h <fqdn of server>
```
The above commands can be executed in a Linux shell to check whether the port for sync is working well and whether the sync module on the server side is working well. Additionally, `-P 6042` is used to check whether the arbitrator is configured properly and is working well.
## Network Speed Diagnostic
`taos -n speed -h <fqdn of server> -P 6030 -N 10 -l 10000000 -S TCP`
From version 2.2.0.0 onwards, the above command can be executed in a Linux shell to test network speed. The command sends uncompressed packages to a running `taosd` server process or a simulated server process started by `taos -n server` to test the network speed. Parameters can be used when testing network speed are as below:
-n：When set to "speed", it means testing network speed.
-h：The FQDN or IP of the server process to be connected to; if not set, the FQDN configured in `taos.cfg` is used.
-P：The port of the server process to connect to, the default value is 6030.
-N：The number of packages that will be sent in the test, range is [1,10000], default value is 100.
-l：The size of each package in bytes, range is [1024, 1024 \* 1024 \* 1024], default value is 1024.
-S：The type of network packages to send, can be either TCP or UDP, default value is TCP.
## FQDN Resolution Diagnostic
`taos -n fqdn -h <fqdn of server>`
From version 2.2.0.0 onward, the above command can be executed in a Linux shell to test the resolution speed of FQDN. It can be used to try to resolve a FQDN to an IP address and record the time spent in this process. The parameters that can be used for this purpose are as below:
-n：When set to "fqdn", it means testing the speed of resolving FQDN.
-h：The FQDN to be resolved. If not set, the `FQDN` parameter in `taos.cfg` is used by default.
## Server Log
The parameter `debugFlag` is used to control the log level of the `taosd` server process. The default value is 131. For debugging and tracing, it needs to be set to either 135 or 143 respectively.
The parameter `debugFlag` is used to control the log level of the `taosd` server process. The default value is 131. For debugging and tracing, it needs to be set to either 135 or 143 respectively.
Once this parameter is set to 135 or 143, the log file grows very quickly especially when there is a huge volume of data insertion and data query requests. If all the logs are stored together, some important information may be missed very easily and so on the server side, important information is stored in a different place from other logs.
- The log at level of INFO, WARNING and ERROR is stored in `taosinfo` so that it is easy to find important information
- The log at level of DEBUG (135) and TRACE (143) and other information not handled by `taosinfo` are stored in `taosdlog`
Once this parameter is set to 135 or 143, the log file grows very quickly especially when there is a huge volume of data insertion and data query requests. Ensure that the disk drive on which logs are stored has sufficient space.
## Client Log
An independent log file, named as "taoslog+<seq num\>" is generated for each client program, i.e. a client process. The default value of `debugFlag` is also 131 and only logs at level of INFO/ERROR/WARNING are recorded. As stated above, for debugging and tracing, it needs to be changed to 135 or 143 respectively, so that logs at DEBUG or TRACE level can be recorded.
An independent log file, named as "taoslog+<seq num\>" is generated for each client program, i.e. a client process. The parameter `debugFlag` is used to control the log level. The default value is 131. For debugging and tracing, it needs to be set to either 135 or 143 respectively.
The default value of `debugFlag` is also 131 and only logs at level of INFO/ERROR/WARNING are recorded. As stated above, for debugging and tracing, it needs to be changed to 135 or 143 respectively, so that logs at DEBUG or TRACE level can be recorded.
The maximum length of a single log file is controlled by parameter `numOfLogLines` and only 2 log files are kept for each `taosd` server process.
Log files are written in an async way to minimize the workload on disk, but the trade off for performance is that a few log lines may be lost in some extreme conditions.
Log files are written in an async way to minimize the workload on disk, but the trade off for performance is that a few log lines may be lost in some extreme conditions. You can configure asynclog to 0 when needed for troubleshooting purposes to ensure that no log information is lost.

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@ -72,7 +72,7 @@ Next, ensure the hostname "tdengine" is resolvable in `/etc/hosts`.
echo 127.0.0.1 tdengine |sudo tee -a /etc/hosts
```
Finally, the TDengine service can be accessed from the taos shell or any connector with "tdengine" as the server address.
Finally, the TDengine service can be accessed from the TDengine CLI or any connector with "tdengine" as the server address.
```shell
taos -h tdengine -P 6030

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@ -3,7 +3,8 @@ title: Schemaless Writing
description: "The Schemaless write method eliminates the need to create super tables/sub tables in advance and automatically creates the storage structure corresponding to the data, as it is written to the interface."
---
In IoT applications, data is collected for many purposes such as intelligent control, business analysis, device monitoring and so on. Due to changes in business or functional requirements or changes in device hardware, the application logic and even the data collected may change. To provide the flexibility needed in such cases and in a rapidly changing IoT landscape, TDengine provides a series of interfaces for the schemaless writing method. These interfaces eliminate the need to create super tables and subtables in advance by automatically creating the storage structure corresponding to the data as the data is written to the interface. When necessary, schemaless writing will automatically add the required columns to ensure that the data written by the user is stored correctly.
In IoT applications, data is collected for many purposes such as intelligent control, business analysis, device monitoring and so on. Due to changes in business or functional requirements or changes in device hardware, the application logic and even the data collected may change. Schemaless writing automatically creates storage structures for your data as it is being written to TDengine, so that you do not need to create supertables in advance. When necessary, schemaless writing
will automatically add the required columns to ensure that the data written by the user is stored correctly.
The schemaless writing method creates super tables and their corresponding subtables. These are completely indistinguishable from the super tables and subtables created directly via SQL. You can write data directly to them via SQL statements. Note that the names of tables created by schemaless writing are based on fixed mapping rules for tag values, so they are not explicitly ideographic and they lack readability.
@ -19,12 +20,12 @@ With the following formatting conventions, schemaless writing uses a single stri
measurement,tag_set field_set timestamp
```
where :
where:
- measurement will be used as the data table name. It will be separated from tag_set by a comma.
- tag_set will be used as tag data in the format `<tag_key>=<tag_value>,<tag_key>=<tag_value>`, i.e. multiple tags' data can be separated by a comma. It is separated from field_set by space.
- field_set will be used as normal column data in the format of `<field_key>=<field_value>,<field_key>=<field_value>`, again using a comma to separate multiple normal columns of data. It is separated from the timestamp by a space.
- The timestamp is the primary key corresponding to the data in this row.
- `tag_set` will be used as tags, with format like `<tag_key>=<tag_value>,<tag_key>=<tag_value>` Enter a space between `tag_set` and `field_set`.
- `field_set`will be used as data columns, with format like `<field_key>=<field_value>,<field_key>=<field_value>` Enter a space between `field_set` and `timestamp`.
- `timestamp` is the primary key timestamp corresponding to this row of data
All data in tag_set is automatically converted to the NCHAR data type and does not require double quotes (").
@ -37,16 +38,18 @@ In the schemaless writing data line protocol, each data item in the field_set ne
| **Serial number** | **Postfix** | **Mapping type** | **Size (bytes)** |
| -------- | -------- | ------------ | -------------- |
| 1 | none or f64 | double | 8 |
| 2 | f32 | float | 4 |
| 3 | i8/u8 | TinyInt/UTinyInt | 1 |
| 4 | i16/u16 | SmallInt/USmallInt | 2 |
| 5 | i32/u32 | Int/UInt | 4 |
| 6 | i64/i/u64/u | Bigint/Bigint/UBigint/UBigint | 8 |
| 1 | None or f64 | double | 8 |
| 2 | f32 | float | 4 |
| 3 | i8/u8 | TinyInt/UTinyInt | 1 |
| 4 | i16/u16 | SmallInt/USmallInt | 2 |
| 5 | i32/u32 | Int/UInt | 4 |
| 6 | i64/i/u64/u | BigInt/BigInt/UBigInt/UBigInt | 8 |
- `t`, `T`, `true`, `True`, `TRUE`, `f`, `F`, `false`, and `False` will be handled directly as BOOL types.
For example, the following data rows indicate that the t1 label is "3" (NCHAR), the t2 label is "4" (NCHAR), and the t3 label is "t3" to the super table named `st` labeled "t3" (NCHAR), write c1 column as 3 (BIGINT), c2 column as false (BOOL), c3 column is "passit" (BINARY), c4 column is 4 (DOUBLE), and the primary key timestamp is 1626006833639000000 in one row.
For example, the following data rows indicate that the t1 label is "3" (NCHAR), the t2 label is "4" (NCHAR), and the t3 label
is "t3" to the super table named `st` labeled "t3" (NCHAR), write c1 column as 3 (BIGINT), c2 column as false (BOOL), c3 column
is "passit" (BINARY), c4 column is 4 (DOUBLE), and the primary key timestamp is 1626006833639000000 in one row.
```json
st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4f64 1626006833639000000
@ -65,18 +68,22 @@ Schemaless writes process row data according to the following principles.
```
Note that tag_key1, tag_key2 are not the original order of the tags entered by the user but the result of using the tag names in ascending order of the strings. Therefore, tag_key1 is not the first tag entered in the line protocol.
The string's MD5 hash value "md5_val" is calculated after the ranking is completed. The calculation result is then combined with the string to generate the table name: "t_md5_val". "t*" is a fixed prefix that every table generated by this mapping relationship has.
The string's MD5 hash value "md5_val" is calculated after the ranking is completed. The calculation result is then combined with the string to generate the table name: "t_md5_val". "t_" is a fixed prefix that every table generated by this mapping relationship has.
You can configure smlChildTableName to specify table names, for example, `smlChildTableName=tname`. You can insert `st,tname=cpul,t1=4 c1=3 1626006833639000000` and the cpu1 table will be automatically created. Note that if multiple rows have the same tname but different tag_set values, the tag_set of the first row is used to create the table and the others are ignored.
2. If the super table obtained by parsing the line protocol does not exist, this super table is created.
If the subtable obtained by the parse line protocol does not exist, Schemaless creates the sub-table according to the subtable name determined in steps 1 or 2.
3. If the subtable obtained by the parse line protocol does not exist, Schemaless creates the sub-table according to the subtable name determined in steps 1 or 2.
4. If the specified tag or regular column in the data row does not exist, the corresponding tag or regular column is added to the super table (only incremental).
5. If there are some tag columns or regular columns in the super table that are not specified to take values in a data row, then the values of these columns are set to NULL.
5. If there are some tag columns or regular columns in the super table that are not specified to take values in a data row, then the values of these columns are set to
NULL.
6. For BINARY or NCHAR columns, if the length of the value provided in a data row exceeds the column type limit, the maximum length of characters allowed to be stored in the column is automatically increased (only incremented and not decremented) to ensure complete preservation of the data.
7. Errors encountered throughout the processing will interrupt the writing process and return an error code.
8. In order to improve the efficiency of writing, it is assumed by default that the order of the fields in the same Super is the same (the first data contains all fields, and the following data is in this order). If the order is different, the parameter smlDataFormat needs to be configured to be false. Otherwise, the data is written in the same order, and the data in the library will be abnormal.
8. It is assumed that the order of field_set in a supertable is consistent, meaning that the first record contains all fields and subsequent records store fields in the same order. If the order is not consistent, set smlDataFormat to false. Otherwise, data will be written out of order and a database error will occur.
:::tip
All processing logic of schemaless will still follow TDengine's underlying restrictions on data structures, such as the total length of each row of data cannot exceed 16k bytes. See [TAOS SQL Boundary Limits](/taos-sql/limit) for specific constraints in this area.
All processing logic of schemaless will still follow TDengine's underlying restrictions on data structures, such as the total length of each row of data cannot exceed
16KB. See [TAOS SQL Boundary Limits](/taos-sql/limit) for specific constraints in this area.
:::
## Time resolution recognition
@ -85,75 +92,74 @@ Three specified modes are supported in the schemaless writing process, as follow
| **Serial** | **Value** | **Description** |
| -------- | ------------------- | ------------------------------- |
| 1 | SML_LINE_PROTOCOL | InfluxDB Line Protocol |
| 2 | SML_TELNET_PROTOCOL | OpenTSDB Text Line Protocol |
| 3 | SML_JSON_PROTOCOL | JSON protocol format |
| 1 | SML_LINE_PROTOCOL | InfluxDB Line Protocol |
| 2 | SML_TELNET_PROTOCOL | OpenTSDB file protocol |
| 3 | SML_JSON_PROTOCOL | OpenTSDB JSON protocol |
In the SML_LINE_PROTOCOL parsing mode, the user is required to specify the time resolution of the input timestamp. The available time resolutions are shown in the following table.
In InfluxDB line protocol mode, you must specify the precision of the input timestamp. Valid precisions are described in the following table.
| **Serial Number** | **Time Resolution Definition** | **Meaning** |
| **No.** | **Precision** | **Description** |
| -------- | --------------------------------- | -------------- |
| 1 | TSDB_SML_TIMESTAMP_NOT_CONFIGURED | Not defined (invalid) |
| 2 | TSDB_SML_TIMESTAMP_HOURS | hour |
| 3 | TSDB_SML_TIMESTAMP_MINUTES | MINUTES
| 4 | TSDB_SML_TIMESTAMP_SECONDS | SECONDS
| 5 | TSDB_SML_TIMESTAMP_MILLI_SECONDS | milliseconds
| 6 | TSDB_SML_TIMESTAMP_MICRO_SECONDS | microseconds
| 7 | TSDB_SML_TIMESTAMP_NANO_SECONDS | nanoseconds |
| 1 | TSDB_SML_TIMESTAMP_NOT_CONFIGURED | Not defined (invalid) |
| 2 | TSDB_SML_TIMESTAMP_HOURS | Hours |
| 3 | TSDB_SML_TIMESTAMP_MINUTES | Minutes |
| 4 | TSDB_SML_TIMESTAMP_SECONDS | Seconds |
| 5 | TSDB_SML_TIMESTAMP_MILLI_SECONDS | Milliseconds |
| 6 | TSDB_SML_TIMESTAMP_MICRO_SECONDS | Microseconds |
| 7 | TSDB_SML_TIMESTAMP_NANO_SECONDS | Nanoseconds |
In SML_TELNET_PROTOCOL and SML_JSON_PROTOCOL modes, the time precision is determined based on the length of the timestamp (in the same way as the OpenTSDB standard operation), and the user-specified time resolution is ignored at this point.
In OpenTSDB file and JSON protocol modes, the precision of the timestamp is determined from its length in the standard OpenTSDB manner. User input is ignored.
## Data schema mapping rules
## Data Model Mapping
This section describes how data for line protocols are mapped to data with a schema. The data measurement in each line protocol is mapped as follows:
- The tag name in tag_set is the name of the tag in the data schema
- The name in field_set is the column's name.
The following data is used as an example to illustrate the mapping rules.
This section describes how data in line protocol is mapped to a schema. The data measurement in each line is mapped to a
supertable name. The tag name in tag_set is the tag name in the schema, and the name in field_set is the column name in the schema. The following example shows how data is mapped:
```json
st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4f64 1626006833639000000
```
The row data mapping generates a super table: `st`, which contains three labels of type NCHAR: t1, t2, t3. Five data columns are ts (timestamp), c1 (bigint), c3 (binary), c2 (bool), c4 (bigint). The mapping becomes the following SQL statement.
This row is mapped to a supertable: `st` contains three NCHAR tags: t1, t2, and t3. Five columns are created: ts (timestamp), c1 (bigint), c3 (binary), c2 (bool), and c4 (bigint). The following SQL statement is generated:
```json
create stable st (_ts timestamp, c1 bigint, c2 bool, c3 binary(6), c4 bigint) tags(t1 nchar(1), t2 nchar(1), t3 nchar(2))
```
## Data schema change handling
## Processing Schema Changes
This section describes the impact on the data schema for different line protocol data writing cases.
This section describes the impact on the schema caused by different data being written.
When writing to an explicitly identified field type using the line protocol, subsequent changes to the field's type definition will result in an explicit data schema error, i.e., will trigger a write API report error. As shown below, the
If you use line protocol to write to a specific tag field and then later change the field type, a schema error will ocur. This triggers an error on the write API. This is shown as follows:
```json
st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4 1626006833639000000
st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4i 1626006833640000000
st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4 1626006833639000000
st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4i 1626006833640000000
```
The data type mapping in the first row defines column c4 as DOUBLE, but the data in the second row is declared as BIGINT by the numeric suffix, which triggers a parsing error with schemaless writing.
The first row defines c4 as a double. However, in the second row, the suffix indicates that the value of c4 is a bigint. This causes schemaless writing to throw an error.
If the line protocol before the column declares the data column as BINARY, the subsequent one requires a longer binary length, which triggers a super table schema change.
An error also occurs if data input into a binary column exceeds the defined length of the column.
```json
st,t1=3,t2=4,t3=t3 c1=3i64,c5="pass" 1626006833639000000
st,t1=3,t2=4,t3=t3 c1=3i64,c5="passit" 1626006833640000000
st,t1=3,t2=4,t3=t3 c1=3i64,c5="pass" 1626006833639000000
st,t1=3,t2=4,t3=t3 c1=3i64,c5="passit" 1626006833640000000
```
The first line of the line protocol parsing will declare column c5 is a BINARY(4) field. The second line data write will parse column c5 as a BINARY column. But in the second line, c5's width is 6 so you need to increase the width of the BINARY field to be able to accommodate the new string.
The first row defines c5 as a binary(4). but the second row writes 6 bytes to it. This means that the length of the binary column must be expanded to contain the data.
```json
st,t1=3,t2=4,t3=t3 c1=3i64 1626006833639000000
st,t1=3,t2=4,t3=t3 c1=3i64,c6="passit" 1626006833640000000
st,t1=3,t2=4,t3=t3 c1=3i64 1626006833639000000
st,t1=3,t2=4,t3=t3 c1=3i64,c6="passit" 1626006833640000000
```
The second line of data has an additional column c6 of type BINARY(6) compared to the first row. Then a column c6 of type BINARY(6) is automatically added at this point.
The preceding data includes a new entry, c6, with type binary(6). When this occurs, a new column c6 with type binary(6) is added automatically.
## Write integrity
## Write Integrity
TDengine provides idempotency guarantees for data writing, i.e., you can repeatedly call the API to write data with errors. However, it does not give atomicity guarantees for writing multiple rows of data. During the process of writing numerous rows of data in one batch, some data will be written successfully, and some data will fail.
TDengine guarantees the idempotency of data writes. This means that you can repeatedly call the API to perform write operations with bad data. However, TDengine does not guarantee the atomicity of multi-row writes. In a multi-row write, some data may be written successfully and other data unsuccessfully.
## Error code
##: Error Codes
If it is an error in the data itself during the schemaless writing process, the application will get `TSDB_CODE_TSC_LINE_SYNTAX_ERROR` error message, which indicates that the error occurred in writing. The other error codes are consistent with the TDengine and can be obtained via the `taos_errstr()` to get the specific cause of the error.
The TSDB_CODE_TSC_LINE_SYNTAX_ERROR indicates an error in the schemaless writing component.
This error occurs when writing text. For other errors, schemaless writing uses the standard TDengine error codes
found in taos_errstr.

17
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@ -6,9 +6,7 @@ title: Grafana
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
TDengine can be quickly integrated with the open-source data visualization system [Grafana](https://www.grafana.com/) to build a data monitoring and alerting system. The whole process does not require any code development. And you can visualize the contents of the data tables in TDengine on a dashboard.
You can learn more about using the TDengine plugin on [GitHub](https://github.com/taosdata/grafanaplugin/blob/master/README.md).
TDengine can be quickly integrated with the open-source data visualization system [Grafana](https://www.grafana.com/) to build a data monitoring and alerting system. The whole process does not require any code development. And you can visualize the contents of the data tables in TDengine on a dashboard. You can learn more about using the TDengine plugin on [GitHub](https://github.com/taosdata/grafanaplugin/blob/master/README.md).
## Prerequisites
@ -65,7 +63,6 @@ Restart Grafana service and open Grafana in web-browser, usually <http://localho
Save the script and type `./install.sh --help` for the full usage of the script.
</TabItem>
<TabItem value="manual" label="Install & Configure Manually">
Follow the installation steps in [Grafana](https://grafana.com/grafana/plugins/tdengine-datasource/?tab=installation) with the [``grafana-cli`` command-line tool](https://grafana.com/docs/grafana/latest/administration/cli/) for plugin installation.
@ -76,7 +73,7 @@ grafana-cli plugins install tdengine-datasource
sudo -u grafana grafana-cli plugins install tdengine-datasource
```
Alternatively, you can manually download the .zip file from [GitHub](https://github.com/taosdata/grafanaplugin/releases/tag/latest) or [Grafana](https://grafana.com/grafana/plugins/tdengine-datasource/?tab=installation) and unpack it into your grafana plugins directory.
You can also download zip files from [GitHub](https://github.com/taosdata/grafanaplugin/releases/tag/latest) or [Grafana](https://grafana.com/grafana/plugins/tdengine-datasource/?tab=installation) and install manually. The commands are as follows:
```bash
GF_VERSION=3.2.2
@ -131,7 +128,7 @@ docker run -d \
grafana/grafana
```
You can setup a zero-configuration stack for TDengine + Grafana by [docker-compose](https://docs.docker.com/compose/) and [Grafana provisioning](https://grafana.com/docs/grafana/latest/administration/provisioning/) file：
You can setup a zero-configuration stack for TDengine + Grafana by [docker-compose](https://docs.docker.com/compose/) and [Grafana provisioning](https://grafana.com/docs/grafana/latest/administration/provisioning/) file:
1. Save the provisioning configuration file to `tdengine.yml`.
@ -196,7 +193,7 @@ Go back to the main interface to create a dashboard and click Add Query to enter
As shown above, select the `TDengine` data source in the `Query` and enter the corresponding SQL in the query box below for query.
- INPUT SQL: enter the statement to be queried (the result set of the SQL statement should be two columns and multiple rows), for example: `select avg(mem_system) from log.dn where ts >= $from and ts < $to interval($interval)`, where, from, to and interval are built-in variables of the TDengine plugin, indicating the range and time interval of queries fetched from the Grafana plugin panel. In addition to the built-in variables, custom template variables are also supported.
- INPUT SQL: Enter the desired query (the results being two columns and multiple rows), such as `select _wstart, avg(mem_system) from log.dnodes_info where ts >= $from and ts < $to interval($interval)`. In this statement, $from, $to, and $interval are variables that Grafana replaces with the query time range and interval. In addition to the built-in variables, custom template variables are also supported.
- ALIAS BY: This allows you to set the current query alias.
- GENERATE SQL: Clicking this button will automatically replace the corresponding variables and generate the final executed statement.
@ -208,7 +205,11 @@ Follow the default prompt to query the average system memory usage for the speci
### Importing the Dashboard
You can install TDinsight dashboard in data source configuration page (like `http://localhost:3000/datasources/edit/1/dashboards`) as a monitoring visualization tool for TDengine cluster. The dashboard is published in Grafana as [Dashboard 15167 - TDinsight](https://grafana.com/grafana/dashboards/15167). Check the [TDinsight User Manual](/reference/tdinsight/) for the details.
You can install TDinsight dashboard in data source configuration page (like `http://localhost:3000/datasources/edit/1/dashboards`) as a monitoring visualization tool for TDengine cluster. Ensure that you use TDinsight for 3.x.
![TDengine Database Grafana plugine import dashboard](./import_dashboard.webp)
A dashboard for TDengine 2.x has been published on Grafana: [Dashboard 15167 - TDinsight](https://grafana.com/grafana/dashboards/15167)) 。 Check the [TDinsight User Manual](/reference/tdinsight/) for the details.
For more dashboards using TDengine data source, [search here in Grafana](https://grafana.com/grafana/dashboards/?dataSource=tdengine-datasource). Here is a sub list:

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@ -1,6 +1,6 @@
---
sidebar_label: StatsD
title: StatsD writing
title: StatsD Writing
---
import StatsD from "../14-reference/_statsd.mdx"
@ -12,8 +12,8 @@ You can write StatsD data to TDengine by simply modifying the configuration file
## Prerequisites
To write StatsD data to TDengine requires the following preparations.
- The TDengine cluster has been deployed and is working properly
- taosAdapter is installed and running properly. Please refer to the [taosAdapter manual](/reference/taosadapter) for details.
1. The TDengine cluster is deployed and functioning properly
2. taosAdapter is installed and running properly. Please refer to the taosAdapter manual for details.
- StatsD has been installed. To install StatsD, please refer to [official documentation](https://github.com/statsd/statsd)
## Configuration steps
@ -39,8 +39,12 @@ $ echo "foo:1|c" | nc -u -w0 127.0.0.1 8125
Use the TDengine CLI to verify that StatsD data is written to TDengine and can read out correctly.
```
Welcome to the TDengine shell from Linux, Client Version:3.0.0.0
Copyright (c) 2022 by TAOS Data, Inc. All rights reserved.
taos> show databases;
name | created_time | ntables | vgroups | replica | quorum | days | keep | cache(MB) | blocks | minrows | maxrows | wallevel | fsync | comp | cachelast | precision | update | status |
====================================================================================================================================================================================================================================================================================
log | 2022-04-20 07:19:50.260 | 11 | 1 | 1 | 1 | 10 | 3650 | 16 | 6 | 100 | 4096 | 1 | 3000 | 2 | 0 | ms | 0 | ready |
statsd | 2022-04-20 09:54:51.220 | 1 | 1 | 1 | 1 | 10 | 3650 | 16 | 6 | 100 | 4096 | 1 | 3000 | 2 | 0 | ns | 2 | ready |
Query OK, 2 row(s) in set (0.003142s)
taos> use statsd;
Database changed.

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@ -1,6 +1,6 @@
---
sidebar_label: HiveMQ Broker
title: HiveMQ Broker writing
title: HiveMQ Broker Writing
---
[HiveMQ](https://www.hivemq.com/) is an MQTT broker that provides community and enterprise editions. HiveMQ is mainly for enterprise emerging machine-to-machine M2M communication and internal transport, meeting scalability, ease of management, and security features. HiveMQ provides an open-source plug-in development kit. MQTT data can be saved to TDengine via TDengine extension for HiveMQ. Please refer to the [HiveMQ extension - TDengine documentation](https://github.com/huskar-t/hivemq-tdengine-extension/blob/b62a26ecc164a310104df57691691b237e091c89/README_EN.md) for details on how to use it.
[HiveMQ](https://www.hivemq.com/) is an MQTT broker that provides community and enterprise editions. HiveMQ is mainly for enterprise emerging machine-to-machine M2M communication and internal transport, meeting scalability, ease of management, and security features. HiveMQ provides an open-source plug-in development kit. MQTT data can be saved to TDengine via TDengine extension for HiveMQ. For more information, see [HiveMQ TDengine Extension](https://github.com/huskar-t/hivemq-tdengine-extension/blob/b62a26ecc164a310104df57691691b237e091c89/README_EN.md).

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@ -1,114 +1,163 @@
---
sidebar_label: FAQ
title: Frequently Asked Questions
---
## Submit an Issue
If the tips in FAQ don't help much, please submit an issue on [GitHub](https://github.com/taosdata/TDengine) to describe your problem. In your description please include the TDengine version, hardware and OS information, the steps to reproduce the problem and any other relevant information. It would be very helpful if you can package the contents in `/var/log/taos` and `/etc/taos` and upload. These two are the default directories used by TDengine. If you have changed the default directories in your configuration, please package the files in your configured directories. We recommended setting `debugFlag` to 135 in `taos.cfg`, restarting `taosd`, then reproducing the problem and collecting the logs. If you don't want to restart, an alternative way of setting `debugFlag` is executing `alter dnode <dnode_id> debugFlag 135` command in TDengine CLI `taos`. During normal running, however, please make sure `debugFlag` is set to 131.
If your issue could not be resolved by reviewing this documentation, you can submit your issue on GitHub and receive support from the TDengine Team. When you submit an issue, attach the following directories from your TDengine deployment:
1. The directory containing TDengine logs (`/var/log/taos` by default)
2. The directory containing TDengine configuration files (`/etc/taos` by default)
In your GitHub issue, provide the version of TDengine and the operating system and environment for your deployment, the operations that you performed when the issue occurred, and the time of occurrence and affected tables.
To obtain more debugging information, open `taos.cfg` and set the `debugFlag` parameter to `135`. Then restart TDengine Server and reproduce the issue. The debug-level logs generated help the TDengine Team to resolve your issue. If it is not possible to restart TDengine Server, you can run the following command in the TDengine CLI to set the debug flag:
```
alter dnode <dnode_id> 'debugFlag' '135';
```
You can run the `SHOW DNODES` command to determine the dnode ID.
When debugging information is no longer needed, set `debugFlag` to 131.
## Frequently Asked Questions
### 1. How to upgrade to TDengine 2.0 from older version?
### 1. What are the best practices for upgrading a previous version of TDengine to version 3.0?
version 2.x is not compatible with version 1.x. With regard to the configuration and data files, please perform the following steps before upgrading. Please follow data integrity, security, backup and other relevant SOPs, best practices before removing/deleting any data.
TDengine 3.0 is not compatible with the configuration and data files from previous versions. Before upgrading, perform the following steps:
1. Delete configuration files: `sudo rm -rf /etc/taos/taos.cfg`
2. Delete log files: `sudo rm -rf /var/log/taos/`
3. Delete data files if the data doesn't need to be kept: `sudo rm -rf /var/lib/taos/`
4. Install latest 2.x version
5. If the data needs to be kept and migrated to newer version, please contact professional service at TDengine for assistance.
1. Run `sudo rm -rf /etc/taos/taos.cfg` to delete your configuration file.
2. Run `sudo rm -rf /var/log/taos/` to delete your log files.
3. Run `sudo rm -rf /var/lib/taos/` to delete your data files.
4. Install TDengine 3.0.
5. For assistance in migrating data to TDengine 3.0, contact [TDengine Support](https://tdengine.com/support).
### 2. How to handle "Unable to establish connection"？
### 4. How can I resolve the "Unable to establish connection" error?
When the client is unable to connect to the server, you can try the following ways to troubleshoot and resolve the problem.
This error indicates that the client could not connect to the server. Perform the following troubleshooting steps:
1. Check the network
1. Check the network.
- Check if the hosts where the client and server are running are accessible to each other, for example by `ping` command.
- Check if the TCP/UDP on port 6030-6042 are open for access if firewall is enabled. If possible, disable the firewall for diagnostics, but please ensure that you are following security and other relevant protocols.
- Check if the FQDN and serverPort are configured correctly in `taos.cfg` used by the server side.
- Check if the `firstEp` is set properly in the `taos.cfg` used by the client side.
- For machines deployed in the cloud, verify that your security group can access ports 6030 and 6031 (TCP and UDP).
- For virtual machines deployed locally, verify that the hosts where the client and server are running are accessible to each other. Do not use localhost as the hostname.
- For machines deployed on a corporate network, verify that your NAT configuration allows the server to respond to the client.
2. Make sure the client version and server version are same.
2. Verify that the client and server are running the same version of TDengine.
3. On server side, check the running status of `taosd` by executing `systemctl status taosd` . If your server is started using another way instead of `systemctl`, use the proper method to check whether the server process is running normally.
3. On the server, run `systemctl status taosd` to verify that taosd is running normally. If taosd is stopped, run `systemctl start taosd`.
4. If using connector of Python, Java, Go, Rust, C#, node.JS on Linux to connect to the server, please make sure `libtaos.so` is in directory `/usr/local/taos/driver` and `/usr/local/taos/driver` is in system lib search environment variable `LD_LIBRARY_PATH`.
4. Verify that the client is configured with the correct FQDN for the server.
5. If using connector on Windows, please make sure `C:\TDengine\driver\taos.dll` is in your system lib search path. We recommend putting `taos.dll` under `C:\Windows\System32`.
5. If the server cannot be reached with the `ping` command, verify that network and DNS or hosts file settings are correct. For a TDengine cluster, the client must be able to ping the FQDN of every node in the cluster.
6. Some advanced network diagnostics tools
6. Verify that your firewall settings allow all hosts in the cluster to communicate on ports 6030 and 6041 (TCP and UDP). You can run `ufw status` (Ubuntu) or `firewall-cmd --list-port` (CentOS) to check the configuration.
- On Linux system tool `nc` can be used to check whether the TCP/UDP can be accessible on a specified port
Check whether a UDP port is open: `nc -vuz {hostIP} {port} `
Check whether a TCP port on server side is open: `nc -l {port}`
Check whether a TCP port on client side is open: `nc {hostIP} {port}`
7. If you are using the Python, Java, Go, Rust, C#, or Node.js connector on Linux to connect to the server, verify that `libtaos.so` is in the `/usr/local/taos/driver` directory and `/usr/local/taos/driver` is in the `LD_LIBRARY_PATH` environment variable.
- On Windows system `Test-NetConnection -ComputerName {fqdn} -Port {port}` on PowerShell can be used to check whether the port on server side is open for access.
8. If you are using Windows, verify that `C:\TDengine\driver\taos.dll` is in the `PATH` environment variable. If possible, move `taos.dll` to the `C:\Windows\System32` directory.
7. TDengine CLI `taos` can also be used to check network, please refer to [TDengine CLI](/reference/taos-shell).
9. On Linux systems, you can use the `nc` tool to check whether a port is accessible:
- To check whether a UDP port is open, run `nc -vuz {hostIP} {port}`.
- To check whether a TCP port on the server side is open, run `nc -l {port}`.
- To check whether a TCP port on client side is open, run `nc {hostIP} {port}`.
### 3. How to handle "Unexpected generic error in RPC" or "Unable to resolve FQDN" ?
10. On Windows systems, you can run `Test-NetConnection -ComputerName {fqdn} -Port {port}` in PowerShell to check whether a port on the server side is accessible.
This error is caused because the FQDN can't be resolved. Please try following ways:
11. You can also use the TDengine CLI to diagnose network issues. For more information, see [Problem Diagnostics](https://docs.tdengine.com/operation/diagnose/).
1. Check whether the FQDN is configured properly on the server side
2. If DSN server is configured in the network, please check whether it works; otherwise, check `/etc/hosts` to see whether the FQDN is configured with correct IP
3. If the network configuration on the server side is OK, try to ping the server from the client side.
4. If TDengine has been used before with an old hostname then the hostname has been changed, please check `/var/lib/taos/taos/dnode/dnodeEps.json`. Before setting up a new TDengine cluster, it's better to cleanup the directories configured.
### 5. How can I resolve the "Unable to resolve FQDN" error?
### 4. "Invalid SQL" is returned even though the Syntax is correct
Clients and dnodes must be able to resolve the FQDN of each required node. You can confirm your configuration as follows:
"Invalid SQL" is returned when the length of SQL statement exceeds maximum allowed length or the syntax is not correct.
1. Verify that the FQDN is configured properly on the server.
2. If your network has a DNS server, verify that it is operational.
3. If your network does not have a DNS server, verify that the FQDNs in the `hosts` file are correct.
4. On the client, use the `ping` command to test your connection to the server. If you cannot ping an FQDN, TDengine cannot reach it.
5. If TDengine has been previously installed and the `hostname` was modified, open `dnode.json` in the `data` folder and verify that the endpoint configuration is correct. The default location of the dnode file is `/var/lib/taos/dnode`. Ensure that you clean up previous installations before reinstalling TDengine.
6. Confirm whether FQDNs are preconfigured in `/etc/hosts` and `/etc/hostname`.
### 5. Whether validation queries are supported?
### 6. What is the most effective way to write data to TDengine?
It's suggested to use a builtin database named as `log` to monitor.
Writing data in batches provides higher efficiency in most situations. You can insert one or more data records into one or more tables in a single SQL statement.
<a class="anchor" id="update"></a>
### 9. Why are table names not fully displayed?
### 6. Can I delete a record?
The number of columns in the TDengine CLI terminal display is limited. This can cause table names to be cut off, and if you use an incomplete name in a statement, the "Table does not exist" error will occur. You can increase the display size with the `maxBinaryDisplayWidth` parameter or the SQL statement `set max_binary_display_width`. You can also append `\G` to your SQL statement to bypass this limitation.
From version 2.6.0.0 Enterprise version, deleting data can be supported.
### 10. How can I migrate data?
### 7. How to create a table of over 1024 columns?
In TDengine, the `hostname` uniquely identifies a machine. When you move data files to a new machine, you must configure the new machine to have the same `host name` as the original machine.
From version 2.1.7.0, at most 4096 columns can be defined for a table.
:::note
### 8. How to improve the efficiency of inserting data?
The data structure of previous versions of TDengine is not compatible with version 3.0. To migrate from TDengine 1.x or 2.x to 3.0, you must export data from your older deployment and import it back into TDengine 3.0.
Inserting data in batch is a good practice. Single SQL statement can insert data for one or multiple tables in batch.
:::
### 9. JDBC Error： the executed SQL is not a DML or a DDL？
### 11. How can I temporary change the log level from the TDengine Client?
Please upgrade to latest JDBC driver, for details please refer to [Java Connector](/reference/connector/java)
### 10. Failed to connect with error "invalid timestamp"
The most common reason is that the time setting is not aligned on the client side and the server side. On Linux system, please use `ntpdate` command. On Windows system, please enable automatic sync in system time setting.
### 11. Table name is not shown in full
There is a display width setting in TDengine CLI `taos`. It can be controlled by configuration parameter `maxBinaryDisplayWidth`, or can be set using SQL command `set max_binary_display_width`. A more convenient way is to append `\G` in a SQL command to bypass this limitation.
### 12. How to change log level temporarily?
Below SQL command can be used to adjust log level temporarily
To change the log level for debugging purposes, you can use the following command:
```sql
ALTER LOCAL flag_name flag_value;
ALTER LOCAL local_option
local_option: {
'resetLog'
| 'rpcDebugFlag' value
| 'tmrDebugFlag' value
| 'cDebugFlag' value
| 'uDebugFlag' value
| 'debugFlag' value
}
```
- flag_name can be: debugFlag，cDebugFlag，tmrDebugFlag，uDebugFlag，rpcDebugFlag
- flag_value can be: 131 (INFO/WARNING/ERROR), 135 (plus DEBUG), 143 (plus TRACE)
<a class="anchor" id="timezone"></a>
Use `resetlog` to remove all logs generated on the local client. Use the other parameters to specify a log level for a specific component.
### 13. What to do if go compilation fails?
For each parameter, you can set the value to `131` (error and warning), `135` (error, warning, and debug), or `143` (error, warning, debug, and trace).
From version 2.3.0.0, a new component named `taosAdapter` is introduced. Its' developed in Go. If you want to compile from source code and meet go compilation problems, try to do below steps to resolve Go environment problems.
### Why do TDengine components written in Go fail to compile?
```sh
go env -w GO111MODULE=on
go env -w GOPROXY=https://goproxy.cn,direct
```
TDengine includes taosAdapter, an independent component written in Go. This component provides the REST API as well as data access for other products such as Prometheus and Telegraf.
When using the develop branch, you must run `git submodule update --init --recursive` to download the taosAdapter repository and then compile it.
TDengine Go components require Go version 1.14 or later.
### 13. How can I query the storage space being used by my data?
The TDengine data files are stored in `/var/lib/taos` by default. Log files are stored in `/var/log/taos`.
To see how much space your data files occupy, run `du -sh /var/lib/taos/vnode --exclude='wal'`. This excludes the write-ahead log (WAL) because its size is relatively fixed while writes are occurring, and it is written to disk and cleared when you shut down TDengine.
If you want to see how much space is occupied by a single database, first determine which vgroup is storing the database by running `show vgroups`. Then check `/var/lib/taos/vnode` for the files associated with the vgroup ID.
### 15. How is timezone information processed for timestamps?
TDengine uses the timezone of the client for timestamps. The server timezone does not affect timestamps. The client converts Unix timestamps in SQL statements to UTC before sending them to the server. When you query data on the server, it provides timestamps in UTC to the client, which converts them to its local time.
Timestamps are processed as follows:
1. The client uses its system timezone unless it has been configured otherwise.
2. A timezone configured in `taos.cfg` takes precedence over the system timezone.
3. A timezone explicitly specified when establishing a connection to TDengine through a connector takes precedence over `taos.cfg` and the system timezone. For example, the Java connector allows you to specify a timezone in the JDBC URL.
4. If you use an RFC 3339 timestamp (2013-04-12T15:52:01.123+08:00), or an ISO 8601 timestamp (2013-04-12T15:52:01.123+0800), the timezone specified in the timestamp is used instead of the timestamps configured using any other method.
### 16. Which network ports are required by TDengine?
See [serverPort](https://docs.tdengine.com/reference/config/#serverport) in Configuration Parameters.
Note that ports are specified using 6030 as the default first port. If you change this port, all other ports change as well.
### 17. Why do applications such as Grafana fail to connect to TDengine over the REST API?
In TDengine, the REST API is provided by taosAdapter. Ensure that taosAdapter is running before you connect an application to TDengine over the REST API. You can run `systemctl start taosadapter` to start the service.
Note that the log path for taosAdapter must be configured separately. The default path is `/var/log/taos`. You can choose one of eight log levels. The default is `info`. You can set the log level to `panic` to disable log output. You can modify the taosAdapter configuration file to change these settings. The default location is `/etc/taos/taosadapter.toml`.
For more information, see [taosAdapter](https://docs.tdengine.com/reference/taosadapter/).
### 18. How can I resolve out-of-memory (OOM) errors?
OOM errors are thrown by the operating system when its memory, including swap, becomes insufficient and it needs to terminate processes to remain operational. Most OOM errors in TDengine occur for one of the following reasons: free memory is less than the value of `vm.min_free_kbytes` or free memory is less than the size of the request. If TDengine occupies reserved memory, an OOM error can occur even when free memory is sufficient.
TDengine preallocates memory to each vnode. The number of vnodes per database is determined by the `vgroups` parameter, and the amount of memory per vnode is determined by the `buffer` parameter. To prevent OOM errors from occurring, ensure that you prepare sufficient memory on your hosts to support the number of vnodes that your deployment requires. Configure an appropriately sized swap space. If you continue to receive OOM errors, your SQL statements may be querying too much data for your system. TDengine Enterprise Edition includes optimized memory management that increases stability for enterprise customers.

16
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View File

@ -16,14 +16,14 @@ public class RestInsertExample {
private static List<String> getRawData() {
return Arrays.asList(
"d1001,2018-10-03 14:38:05.000,10.30000,219,0.31000,California.SanFrancisco,2",
"d1001,2018-10-03 14:38:15.000,12.60000,218,0.33000,California.SanFrancisco,2",
"d1001,2018-10-03 14:38:16.800,12.30000,221,0.31000,California.SanFrancisco,2",
"d1002,2018-10-03 14:38:16.650,10.30000,218,0.25000,California.SanFrancisco,3",
"d1003,2018-10-03 14:38:05.500,11.80000,221,0.28000,California.LosAngeles,2",
"d1003,2018-10-03 14:38:16.600,13.40000,223,0.29000,California.LosAngeles,2",
"d1004,2018-10-03 14:38:05.000,10.80000,223,0.29000,California.LosAngeles,3",
"d1004,2018-10-03 14:38:06.500,11.50000,221,0.35000,California.LosAngeles,3"
"d1001,2018-10-03 14:38:05.000,10.30000,219,0.31000,'California.SanFrancisco',2",
"d1001,2018-10-03 14:38:15.000,12.60000,218,0.33000,'California.SanFrancisco',2",
"d1001,2018-10-03 14:38:16.800,12.30000,221,0.31000,'California.SanFrancisco',2",
"d1002,2018-10-03 14:38:16.650,10.30000,218,0.25000,'California.SanFrancisco',3",
"d1003,2018-10-03 14:38:05.500,11.80000,221,0.28000,'California.LosAngeles',2",
"d1003,2018-10-03 14:38:16.600,13.40000,223,0.29000,'California.LosAngeles',2",
"d1004,2018-10-03 14:38:05.000,10.80000,223,0.29000,'California.LosAngeles',3",
"d1004,2018-10-03 14:38:06.500,11.50000,221,0.35000,'California.LosAngeles',3"
);
}

2
docs/examples/java/src/main/java/com/taos/example/SubscribeDemo.java
View File

@ -57,7 +57,7 @@ public class SubscribeDemo {
properties.setProperty(TMQConstants.ENABLE_AUTO_COMMIT, "true");
properties.setProperty(TMQConstants.GROUP_ID, "test");
properties.setProperty(TMQConstants.VALUE_DESERIALIZER,
"com.taosdata.jdbc.MetersDeserializer");
"com.taos.example.MetersDeserializer");
// poll data
try (TaosConsumer<Meters> consumer = new TaosConsumer<>(properties)) {

63
docs/examples/java/src/main/java/com/taos/example/highvolume/DataBaseMonitor.java Normal file
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@ -0,0 +1,63 @@
package com.taos.example.highvolume;
import java.sql.*;
/**
* Prepare target database.
* Count total records in database periodically so that we can estimate the writing speed.
*/
public class DataBaseMonitor {
private Connection conn;
private Statement stmt;
public DataBaseMonitor init() throws SQLException {
if (conn == null) {
String jdbcURL = System.getenv("TDENGINE_JDBC_URL");
conn = DriverManager.getConnection(jdbcURL);
stmt = conn.createStatement();
}
return this;
}
public void close() {
try {
stmt.close();
} catch (SQLException e) {
}
try {
conn.close();
} catch (SQLException e) {
}
}
public void prepareDatabase() throws SQLException {
stmt.execute("DROP DATABASE IF EXISTS test");
stmt.execute("CREATE DATABASE test");
stmt.execute("CREATE STABLE test.meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (location BINARY(64), groupId INT)");
}
public Long count() throws SQLException {
if (!stmt.isClosed()) {
ResultSet result = stmt.executeQuery("SELECT count(*) from test.meters");
result.next();
return result.getLong(1);
}
return null;
}
/**
* show test.stables;
*
* name | created_time | columns | tags | tables |
* ============================================================================================
* meters | 2022-07-20 08:39:30.902 | 4 | 2 | 620000 |
*/
public Long getTableCount() throws SQLException {
if (!stmt.isClosed()) {
ResultSet result = stmt.executeQuery("show test.stables");
result.next();
return result.getLong(5);
}
return null;
}
}

70
docs/examples/java/src/main/java/com/taos/example/highvolume/FastWriteExample.java Normal file
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@ -0,0 +1,70 @@
package com.taos.example.highvolume;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.sql.*;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.BlockingQueue;
public class FastWriteExample {
final static Logger logger = LoggerFactory.getLogger(FastWriteExample.class);
final static int taskQueueCapacity = 1000000;
final static List<BlockingQueue<String>> taskQueues = new ArrayList<>();
final static List<ReadTask> readTasks = new ArrayList<>();
final static List<WriteTask> writeTasks = new ArrayList<>();
final static DataBaseMonitor databaseMonitor = new DataBaseMonitor();
public static void stopAll() {
logger.info("shutting down");
readTasks.forEach(task -> task.stop());
writeTasks.forEach(task -> task.stop());
databaseMonitor.close();
}
public static void main(String[] args) throws InterruptedException, SQLException {
int readTaskCount = args.length > 0 ? Integer.parseInt(args[0]) : 1;
int writeTaskCount = args.length > 1 ? Integer.parseInt(args[1]) : 3;
int tableCount = args.length > 2 ? Integer.parseInt(args[2]) : 1000;
int maxBatchSize = args.length > 3 ? Integer.parseInt(args[3]) : 3000;
logger.info("readTaskCount={}, writeTaskCount={} tableCount={} maxBatchSize={}",
readTaskCount, writeTaskCount, tableCount, maxBatchSize);
databaseMonitor.init().prepareDatabase();
// Create task queues, whiting tasks and start writing threads.
for (int i = 0; i < writeTaskCount; ++i) {
BlockingQueue<String> queue = new ArrayBlockingQueue<>(taskQueueCapacity);
taskQueues.add(queue);
WriteTask task = new WriteTask(queue, maxBatchSize);
Thread t = new Thread(task);
t.setName("WriteThread-" + i);
t.start();
}
// create reading tasks and start reading threads
int tableCountPerTask = tableCount / readTaskCount;
for (int i = 0; i < readTaskCount; ++i) {
ReadTask task = new ReadTask(i, taskQueues, tableCountPerTask);
Thread t = new Thread(task);
t.setName("ReadThread-" + i);
t.start();
}
Runtime.getRuntime().addShutdownHook(new Thread(FastWriteExample::stopAll));
long lastCount = 0;
while (true) {
Thread.sleep(10000);
long numberOfTable = databaseMonitor.getTableCount();
long count = databaseMonitor.count();
logger.info("numberOfTable={} count={} speed={}", numberOfTable, count, (count - lastCount) / 10);
lastCount = count;
}
}
}

53
docs/examples/java/src/main/java/com/taos/example/highvolume/MockDataSource.java Normal file
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@ -0,0 +1,53 @@
package com.taos.example.highvolume;
import java.util.Iterator;
/**
* Generate test data
*/
class MockDataSource implements Iterator {
private String tbNamePrefix;
private int tableCount;
private long maxRowsPerTable = 1000000000L;
// 100 milliseconds between two neighbouring rows.
long startMs = System.currentTimeMillis() - maxRowsPerTable * 100;
private int currentRow = 0;
private int currentTbId = -1;
// mock values
String[] location = {"LosAngeles", "SanDiego", "Hollywood", "Compton", "San Francisco"};
float[] current = {8.8f, 10.7f, 9.9f, 8.9f, 9.4f};
int[] voltage = {119, 116, 111, 113, 118};
float[] phase = {0.32f, 0.34f, 0.33f, 0.329f, 0.141f};
public MockDataSource(String tbNamePrefix, int tableCount) {
this.tbNamePrefix = tbNamePrefix;
this.tableCount = tableCount;
}
@Override
public boolean hasNext() {
currentTbId += 1;
if (currentTbId == tableCount) {
currentTbId = 0;
currentRow += 1;
}
return currentRow < maxRowsPerTable;
}
@Override
public String next() {
long ts = startMs + 100 * currentRow;
int groupId = currentTbId % 5 == 0 ? currentTbId / 5 : currentTbId / 5 + 1;
StringBuilder sb = new StringBuilder(tbNamePrefix + "_" + currentTbId + ","); // tbName
sb.append(ts).append(','); // ts
sb.append(current[currentRow % 5]).append(','); // current
sb.append(voltage[currentRow % 5]).append(','); // voltage
sb.append(phase[currentRow % 5]).append(','); // phase
sb.append(location[currentRow % 5]).append(','); // location
sb.append(groupId); // groupID
return sb.toString();
}
}

58
docs/examples/java/src/main/java/com/taos/example/highvolume/ReadTask.java Normal file
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@ -0,0 +1,58 @@
package com.taos.example.highvolume;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.Iterator;
import java.util.List;
import java.util.concurrent.BlockingQueue;
class ReadTask implements Runnable {
private final static Logger logger = LoggerFactory.getLogger(ReadTask.class);
private final int taskId;
private final List<BlockingQueue<String>> taskQueues;
private final int queueCount;
private final int tableCount;
private boolean active = true;
public ReadTask(int readTaskId, List<BlockingQueue<String>> queues, int tableCount) {
this.taskId = readTaskId;
this.taskQueues = queues;
this.queueCount = queues.size();
this.tableCount = tableCount;
}
/**
* Assign data received to different queues.
* Here we use the suffix number in table name.
* You are expected to define your own rule in practice.
*
* @param line record received
* @return which queue to use
*/
public int getQueueId(String line) {
String tbName = line.substring(0, line.indexOf(',')); // For example: tb1_101
String suffixNumber = tbName.split("_")[1];
return Integer.parseInt(suffixNumber) % this.queueCount;
}
@Override
public void run() {
logger.info("started");
Iterator<String> it = new MockDataSource("tb" + this.taskId, tableCount);
try {
while (it.hasNext() && active) {
String line = it.next();
int queueId = getQueueId(line);
taskQueues.get(queueId).put(line);
}
} catch (Exception e) {
logger.error("Read Task Error", e);
}
}
public void stop() {
logger.info("stop");
this.active = false;
}
}

205
docs/examples/java/src/main/java/com/taos/example/highvolume/SQLWriter.java Normal file
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@ -0,0 +1,205 @@
package com.taos.example.highvolume;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.sql.*;
import java.util.HashMap;
import java.util.Map;
/**
* A helper class encapsulate the logic of writing using SQL.
* <p>
* The main interfaces are two methods:
* <ol>
* <li>{@link SQLWriter#processLine}, which receive raw lines from WriteTask and group them by table names.</li>
* <li>{@link SQLWriter#flush}, which assemble INSERT statement and execute it.</li>
* </ol>
* <p>
* There is a technical skill worth mentioning: we create table as needed when "table does not exist" error occur instead of creating table automatically using syntax "INSET INTO tb USING stb".
* This ensure that checking table existence is a one-time-only operation.
* </p>
*
* </p>
*/
public class SQLWriter {
final static Logger logger = LoggerFactory.getLogger(SQLWriter.class);
private Connection conn;
private Statement stmt;
/**
* current number of buffered records
*/
private int bufferedCount = 0;
/**
* Maximum number of buffered records.
* Flush action will be triggered if bufferedCount reached this value,
*/
private int maxBatchSize;
/**
* Maximum SQL length.
*/
private int maxSQLLength;
/**
* Map from table name to column values. For example:
* "tb001" -> "(1648432611249,2.1,114,0.09) (1648432611250,2.2,135,0.2)"
*/
private Map<String, String> tbValues = new HashMap<>();
/**
* Map from table name to tag values in the same order as creating stable.
* Used for creating table.
*/
private Map<String, String> tbTags = new HashMap<>();
public SQLWriter(int maxBatchSize) {
this.maxBatchSize = maxBatchSize;
}
/**
* Get Database Connection
*
* @return Connection
* @throws SQLException
*/
private static Connection getConnection() throws SQLException {
String jdbcURL = System.getenv("TDENGINE_JDBC_URL");
return DriverManager.getConnection(jdbcURL);
}
/**
* Create Connection and Statement
*
* @throws SQLException
*/
public void init() throws SQLException {
conn = getConnection();
stmt = conn.createStatement();
stmt.execute("use test");
ResultSet rs = stmt.executeQuery("show variables");
while (rs.next()) {
String configName = rs.getString(1);
if ("maxSQLLength".equals(configName)) {
maxSQLLength = Integer.parseInt(rs.getString(2));
logger.info("maxSQLLength={}", maxSQLLength);
}
}
}
/**
* Convert raw data to SQL fragments, group them by table name and cache them in a HashMap.
* Trigger writing when number of buffered records reached maxBachSize.
*
* @param line raw data get from task queue in format: tbName,ts,current,voltage,phase,location,groupId
*/
public void processLine(String line) throws SQLException {
bufferedCount += 1;
int firstComma = line.indexOf(',');
String tbName = line.substring(0, firstComma);
int lastComma = line.lastIndexOf(',');
int secondLastComma = line.lastIndexOf(',', lastComma - 1);
String value = "(" + line.substring(firstComma + 1, secondLastComma) + ") ";
if (tbValues.containsKey(tbName)) {
tbValues.put(tbName, tbValues.get(tbName) + value);
} else {
tbValues.put(tbName, value);
}
if (!tbTags.containsKey(tbName)) {
String location = line.substring(secondLastComma + 1, lastComma);
String groupId = line.substring(lastComma + 1);
String tagValues = "('" + location + "'," + groupId + ')';
tbTags.put(tbName, tagValues);
}
if (bufferedCount == maxBatchSize) {
flush();
}
}
/**
* Assemble INSERT statement using buffered SQL fragments in Map {@link SQLWriter#tbValues} and execute it.
* In case of "Table does not exit" exception, create all tables in the sql and retry the sql.
*/
public void flush() throws SQLException {
StringBuilder sb = new StringBuilder("INSERT INTO ");
for (Map.Entry<String, String> entry : tbValues.entrySet()) {
String tableName = entry.getKey();
String values = entry.getValue();
String q = tableName + " values " + values + " ";
if (sb.length() + q.length() > maxSQLLength) {
executeSQL(sb.toString());
logger.warn("increase maxSQLLength or decrease maxBatchSize to gain better performance");
sb = new StringBuilder("INSERT INTO ");
}
sb.append(q);
}
executeSQL(sb.toString());
tbValues.clear();
bufferedCount = 0;
}
private void executeSQL(String sql) throws SQLException {
try {
stmt.executeUpdate(sql);
} catch (SQLException e) {
// convert to error code defined in taoserror.h
int errorCode = e.getErrorCode() & 0xffff;
if (errorCode == 0x362 || errorCode == 0x218) {
// Table does not exist
createTables();
executeSQL(sql);
} else {
logger.error("Execute SQL: {}", sql);
throw e;
}
} catch (Throwable throwable) {
logger.error("Execute SQL: {}", sql);
throw throwable;
}
}
/**
* Create tables in batch using syntax:
* <p>
* CREATE TABLE [IF NOT EXISTS] tb_name1 USING stb_name TAGS (tag_value1, ...) [IF NOT EXISTS] tb_name2 USING stb_name TAGS (tag_value2, ...) ...;
* </p>
*/
private void createTables() throws SQLException {
StringBuilder sb = new StringBuilder("CREATE TABLE ");
for (String tbName : tbValues.keySet()) {
String tagValues = tbTags.get(tbName);
sb.append("IF NOT EXISTS ").append(tbName).append(" USING meters TAGS ").append(tagValues).append(" ");
}
String sql = sb.toString();
try {
stmt.executeUpdate(sql);
} catch (Throwable throwable) {
logger.error("Execute SQL: {}", sql);
throw throwable;
}
}
public boolean hasBufferedValues() {
return bufferedCount > 0;
}
public int getBufferedCount() {
return bufferedCount;
}
public void close() {
try {
stmt.close();
} catch (SQLException e) {
}
try {
conn.close();
} catch (SQLException e) {
}
}
}

4
docs/examples/java/src/main/java/com/taos/example/highvolume/StmtWriter.java Normal file
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@ -0,0 +1,4 @@
package com.taos.example.highvolume;
public class StmtWriter {
}

58
docs/examples/java/src/main/java/com/taos/example/highvolume/WriteTask.java Normal file
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@ -0,0 +1,58 @@
package com.taos.example.highvolume;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.concurrent.BlockingQueue;
class WriteTask implements Runnable {
private final static Logger logger = LoggerFactory.getLogger(WriteTask.class);
private final int maxBatchSize;
// the queue from which this writing task get raw data.
private final BlockingQueue<String> queue;
// A flag indicate whether to continue.
private boolean active = true;
public WriteTask(BlockingQueue<String> taskQueue, int maxBatchSize) {
this.queue = taskQueue;
this.maxBatchSize = maxBatchSize;
}
@Override
public void run() {
logger.info("started");
String line = null; // data getting from the queue just now.
SQLWriter writer = new SQLWriter(maxBatchSize);
try {
writer.init();
while (active) {
line = queue.poll();
if (line != null) {
// parse raw data and buffer the data.
writer.processLine(line);
} else if (writer.hasBufferedValues()) {
// write data immediately if no more data in the queue
writer.flush();
} else {
// sleep a while to avoid high CPU usage if no more data in the queue and no buffered records, .
Thread.sleep(100);
}
}
if (writer.hasBufferedValues()) {
writer.flush();
}
} catch (Exception e) {
String msg = String.format("line=%s, bufferedCount=%s", line, writer.getBufferedCount());
logger.error(msg, e);
} finally {
writer.close();
}
}
public void stop() {
logger.info("stop");
this.active = false;
}
}

20
docs/examples/java/src/test/java/com/taos/test/TestAll.java
View File

@ -23,16 +23,16 @@ public class TestAll {
String jdbcUrl = "jdbc:TAOS://localhost:6030?user=root&password=taosdata";
try (Connection conn = DriverManager.getConnection(jdbcUrl)) {
try (Statement stmt = conn.createStatement()) {
String sql = "INSERT INTO power.d1001 USING power.meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:05.000',10.30000,219,0.31000)\n" +
" power.d1001 USING power.meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 15:38:15.000',12.60000,218,0.33000)\n" +
" power.d1001 USING power.meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 15:38:16.800',12.30000,221,0.31000)\n" +
" power.d1002 USING power.meters TAGS(California.SanFrancisco, 3) VALUES('2018-10-03 15:38:16.650',10.30000,218,0.25000)\n" +
" power.d1003 USING power.meters TAGS(California.LosAngeles, 2) VALUES('2018-10-03 15:38:05.500',11.80000,221,0.28000)\n" +
" power.d1003 USING power.meters TAGS(California.LosAngeles, 2) VALUES('2018-10-03 15:38:16.600',13.40000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS(California.LosAngeles, 3) VALUES('2018-10-03 15:38:05.000',10.80000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS(California.LosAngeles, 3) VALUES('2018-10-03 15:38:06.000',10.80000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS(California.LosAngeles, 3) VALUES('2018-10-03 15:38:07.000',10.80000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS(California.LosAngeles, 3) VALUES('2018-10-03 15:38:08.500',11.50000,221,0.35000)";
String sql = "INSERT INTO power.d1001 USING power.meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:05.000',10.30000,219,0.31000)\n" +
" power.d1001 USING power.meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 15:38:15.000',12.60000,218,0.33000)\n" +
" power.d1001 USING power.meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 15:38:16.800',12.30000,221,0.31000)\n" +
" power.d1002 USING power.meters TAGS('California.SanFrancisco', 3) VALUES('2018-10-03 15:38:16.650',10.30000,218,0.25000)\n" +
" power.d1003 USING power.meters TAGS('California.LosAngeles', 2) VALUES('2018-10-03 15:38:05.500',11.80000,221,0.28000)\n" +
" power.d1003 USING power.meters TAGS('California.LosAngeles', 2) VALUES('2018-10-03 15:38:16.600',13.40000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 15:38:05.000',10.80000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 15:38:06.000',10.80000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 15:38:07.000',10.80000,223,0.29000)\n" +
" power.d1004 USING power.meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 15:38:08.500',11.50000,221,0.35000)";
stmt.execute(sql);
}

180
docs/examples/python/fast_write_example.py Normal file
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@ -0,0 +1,180 @@
# install dependencies:
# recommend python >= 3.8
# pip3 install faster-fifo
#
import logging
import math
import sys
import time
import os
from multiprocessing import Process
from faster_fifo import Queue
from mockdatasource import MockDataSource
from queue import Empty
from typing import List
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG, format="%(asctime)s [%(name)s] - %(message)s")
READ_TASK_COUNT = 1
WRITE_TASK_COUNT = 1
TABLE_COUNT = 1000
QUEUE_SIZE = 1000000
MAX_BATCH_SIZE = 3000
read_processes = []
write_processes = []
def get_connection():
"""
If variable TDENGINE_FIRST_EP is provided then it will be used. If not, firstEP in /etc/taos/taos.cfg will be used.
You can also override the default username and password by supply variable TDENGINE_USER and TDENGINE_PASSWORD
"""
import taos
firstEP = os.environ.get("TDENGINE_FIRST_EP")
if firstEP:
host, port = firstEP.split(":")
else:
host, port = None, 0
user = os.environ.get("TDENGINE_USER", "root")
password = os.environ.get("TDENGINE_PASSWORD", "taosdata")
return taos.connect(host=host, port=int(port), user=user, password=password)
# ANCHOR: read
def run_read_task(task_id: int, task_queues: List[Queue]):
table_count_per_task = TABLE_COUNT // READ_TASK_COUNT
data_source = MockDataSource(f"tb{task_id}", table_count_per_task)
try:
for batch in data_source:
for table_id, rows in batch:
# hash data to different queue
i = table_id % len(task_queues)
# block putting forever when the queue is full
task_queues[i].put_many(rows, block=True, timeout=-1)
except KeyboardInterrupt:
pass
# ANCHOR_END: read
# ANCHOR: write
def run_write_task(task_id: int, queue: Queue):
from sql_writer import SQLWriter
log = logging.getLogger(f"WriteTask-{task_id}")
writer = SQLWriter(get_connection)
lines = None
try:
while True:
try:
# get as many as possible
lines = queue.get_many(block=False, max_messages_to_get=MAX_BATCH_SIZE)
writer.process_lines(lines)
except Empty:
time.sleep(0.01)
except KeyboardInterrupt:
pass
except BaseException as e:
log.debug(f"lines={lines}")
raise e
# ANCHOR_END: write
def set_global_config():
argc = len(sys.argv)
if argc > 1:
global READ_TASK_COUNT
READ_TASK_COUNT = int(sys.argv[1])
if argc > 2:
global WRITE_TASK_COUNT
WRITE_TASK_COUNT = int(sys.argv[2])
if argc > 3:
global TABLE_COUNT
TABLE_COUNT = int(sys.argv[3])
if argc > 4:
global QUEUE_SIZE
QUEUE_SIZE = int(sys.argv[4])
if argc > 5:
global MAX_BATCH_SIZE
MAX_BATCH_SIZE = int(sys.argv[5])
# ANCHOR: monitor
def run_monitor_process():
log = logging.getLogger("DataBaseMonitor")
conn = get_connection()
conn.execute("DROP DATABASE IF EXISTS test")
conn.execute("CREATE DATABASE test")
conn.execute("CREATE STABLE test.meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) "
"TAGS (location BINARY(64), groupId INT)")
def get_count():
res = conn.query("SELECT count(*) FROM test.meters")
rows = res.fetch_all()
return rows[0][0] if rows else 0
last_count = 0
while True:
time.sleep(10)
count = get_count()
log.info(f"count={count} speed={(count - last_count) / 10}")
last_count = count
# ANCHOR_END: monitor
# ANCHOR: main
def main():
set_global_config()
logging.info(f"READ_TASK_COUNT={READ_TASK_COUNT}, WRITE_TASK_COUNT={WRITE_TASK_COUNT}, "
f"TABLE_COUNT={TABLE_COUNT}, QUEUE_SIZE={QUEUE_SIZE}, MAX_BATCH_SIZE={MAX_BATCH_SIZE}")
monitor_process = Process(target=run_monitor_process)
monitor_process.start()
time.sleep(3) # waiting for database ready.
task_queues: List[Queue] = []
# create task queues
for i in range(WRITE_TASK_COUNT):
queue = Queue(max_size_bytes=QUEUE_SIZE)
task_queues.append(queue)
# create write processes
for i in range(WRITE_TASK_COUNT):
p = Process(target=run_write_task, args=(i, task_queues[i]))
p.start()
logging.debug(f"WriteTask-{i} started with pid {p.pid}")
write_processes.append(p)
# create read processes
for i in range(READ_TASK_COUNT):
queues = assign_queues(i, task_queues)
p = Process(target=run_read_task, args=(i, queues))
p.start()
logging.debug(f"ReadTask-{i} started with pid {p.pid}")
read_processes.append(p)
try:
monitor_process.join()
except KeyboardInterrupt:
monitor_process.terminate()
[p.terminate() for p in read_processes]
[p.terminate() for p in write_processes]
[q.close() for q in task_queues]
def assign_queues(read_task_id, task_queues):
"""
Compute target queues for a specific read task.
"""
ratio = WRITE_TASK_COUNT / READ_TASK_COUNT
from_index = math.floor(read_task_id * ratio)
end_index = math.ceil((read_task_id + 1) * ratio)
return task_queues[from_index:end_index]
if __name__ == '__main__':
main()
# ANCHOR_END: main

49
docs/examples/python/mockdatasource.py Normal file
View File

@ -0,0 +1,49 @@
import time
class MockDataSource:
samples = [
"8.8,119,0.32,LosAngeles,0",
"10.7,116,0.34,SanDiego,1",
"9.9,111,0.33,Hollywood,2",
"8.9,113,0.329,Compton,3",
"9.4,118,0.141,San Francisco,4"
]
def __init__(self, tb_name_prefix, table_count):
self.table_name_prefix = tb_name_prefix + "_"
self.table_count = table_count
self.max_rows = 10000000
self.current_ts = round(time.time() * 1000) - self.max_rows * 100
# [(tableId, tableName, values),]
self.data = self._init_data()
def _init_data(self):
lines = self.samples * (self.table_count // 5 + 1)
data = []
for i in range(self.table_count):
table_name = self.table_name_prefix + str(i)
data.append((i, table_name, lines[i])) # tableId, row
return data
def __iter__(self):
self.row = 0
return self
def __next__(self):
"""
next 1000 rows for each table.
return: {tableId:[row,...]}
"""
# generate 1000 timestamps
ts = []
for _ in range(1000):
self.current_ts += 100
ts.append(str(self.current_ts))
# add timestamp to each row
# [(tableId, ["tableName,ts,current,voltage,phase,location,groupId"])]
result = []
for table_id, table_name, values in self.data:
rows = [table_name + ',' + t + ',' + values for t in ts]
result.append((table_id, rows))
return result

90
docs/examples/python/sql_writer.py Normal file
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@ -0,0 +1,90 @@
import logging
import taos
class SQLWriter:
log = logging.getLogger("SQLWriter")
def __init__(self, get_connection_func):
self._tb_values = {}
self._tb_tags = {}
self._conn = get_connection_func()
self._max_sql_length = self.get_max_sql_length()
self._conn.execute("USE test")
def get_max_sql_length(self):
rows = self._conn.query("SHOW variables").fetch_all()
for r in rows:
name = r[0]
if name == "maxSQLLength":
return int(r[1])
return 1024 * 1024
def process_lines(self, lines: str):
"""
:param lines: [[tbName,ts,current,voltage,phase,location,groupId]]
"""
for line in lines:
ps = line.split(",")
table_name = ps[0]
value = '(' + ",".join(ps[1:-2]) + ') '
if table_name in self._tb_values:
self._tb_values[table_name] += value
else:
self._tb_values[table_name] = value
if table_name not in self._tb_tags:
location = ps[-2]
group_id = ps[-1]
tag_value = f"('{location}',{group_id})"
self._tb_tags[table_name] = tag_value
self.flush()
def flush(self):
"""
Assemble INSERT statement and execute it.
When the sql length grows close to MAX_SQL_LENGTH, the sql will be executed immediately, and a new INSERT statement will be created.
In case of "Table does not exit" exception, tables in the sql will be created and the sql will be re-executed.
"""
sql = "INSERT INTO "
sql_len = len(sql)
buf = []
for tb_name, values in self._tb_values.items():
q = tb_name + " VALUES " + values
if sql_len + len(q) >= self._max_sql_length:
sql += " ".join(buf)
self.execute_sql(sql)
sql = "INSERT INTO "
sql_len = len(sql)
buf = []
buf.append(q)
sql_len += len(q)
sql += " ".join(buf)
self.execute_sql(sql)
self._tb_values.clear()
def execute_sql(self, sql):
try:
self._conn.execute(sql)
except taos.Error as e:
error_code = e.errno & 0xffff
# Table does not exit
if error_code == 9731:
self.create_tables()
else:
self.log.error("Execute SQL: %s", sql)
raise e
except BaseException as baseException:
self.log.error("Execute SQL: %s", sql)
raise baseException
def create_tables(self):
sql = "CREATE TABLE "
for tb in self._tb_values.keys():
tag_values = self._tb_tags[tb]
sql += "IF NOT EXISTS " + tb + " USING meters TAGS " + tag_values + " "
try:
self._conn.execute(sql)
except BaseException as e:
self.log.error("Execute SQL: %s", sql)
raise e

2
docs/zh/07-develop/03-insert-data/01-sql-writing.mdx
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@ -23,7 +23,7 @@ import PhpStmt from "./_php_stmt.mdx";
## SQL 写入简介
应用通过连接器执行 INSERT 语句来插入数据，用户还可以通过 TAOS Shell，手动输入 INSERT 语句插入数据。
应用通过连接器执行 INSERT 语句来插入数据，用户还可以通过 TDengine CLI，手动输入 INSERT 语句插入数据。
### 一次写入一条
下面这条 INSERT 就将一条记录写入到表 d1001 中：

440
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@ -0,0 +1,440 @@
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
# 高效写入
本节介绍如何高效地向 TDengine 写入数据。
## 高效写入原理 {#principle}
### 客户端程序的角度 {#application-view}
从客户端程序的角度来说，高效写入数据要考虑以下几个因素：
1. 单次写入的数据量。一般来讲，每批次写入的数据量越大越高效（但超过一定阈值其优势会消失）。使用 SQL 写入 TDengine 时，尽量在一条 SQL 中拼接更多数据。目前，TDengine 支持的一条 SQL 的最大长度为 1,048,576（1M）个字符。可通过配置客户端参数 maxSQLLength（默认值为 65480）进行修改。
2. 并发连接数。一般来讲，同时写入数据的并发连接数越多写入越高效（但超过一定阈值反而会下降，取决于服务端处理能力）。
3. 数据在不同表（或子表）之间的分布，即要写入数据的相邻性。一般来说，每批次只向同一张表（或子表）写入数据比向多张表（或子表）写入数据要更高效；
4. 写入方式。一般来讲：
- 参数绑定写入比 SQL 写入更高效。因参数绑定方式避免了 SQL 解析。（但增加了 C 接口的调用次数，对于连接器也有性能损耗）。
- SQL 写入不自动建表比自动建表更高效。因自动建表要频繁检查表是否存在
- SQL 写入比无模式写入更高效。因无模式写入会自动建表且支持动态更改表结构
客户端程序要充分且恰当地利用以上几个因素。在单次写入中尽量只向同一张表（或子表）写入数据，每批次写入的数据量经过测试和调优设定为一个最适合当前系统处理能力的数值，并发写入的连接数同样经过测试和调优后设定为一个最适合当前系统处理能力的数值，以实现在当前系统中的最佳写入速度。
### 数据源的角度 {#datasource-view}
客户端程序通常需要从数据源读数据再写入 TDengine。从数据源角度来说，以下几种情况需要在读线程和写线程之间增加队列：
1. 有多个数据源，单个数据源生成数据的速度远小于单线程写入的速度，但数据量整体比较大。此时队列的作用是把多个数据源的数据汇聚到一起，增加单次写入的数据量。
2. 单个数据源生成数据的速度远大于单线程写入的速度。此时队列的作用是增加写入的并发度。
3. 单张表的数据分散在多个数据源。此时队列的作用是将同一张表的数据提前汇聚到一起，提高写入时数据的相邻性。
如果写应用的数据源是 Kafka, 写应用本身即 Kafka 的消费者，则可利用 Kafka 的特性实现高效写入。比如：
1. 将同一张表的数据写到同一个 Topic 的同一个 Partition，增加数据的相邻性
2. 通过订阅多个 Topic 实现数据汇聚
3. 通过增加 Consumer 线程数增加写入的并发度
4. 通过增加每次 fetch 的最大数据量来增加单次写入的最大数据量
### 服务器配置的角度 {#setting-view}
从服务器配置的角度来说，也有很多优化写入性能的方法。
如果总表数不多(远小于核数乘以1000), 且无论怎么调节客户端程序，taosd 进程的 CPU 使用率都很低，那么很可能是因为表在各个 vgroup 分布不均。比如：数据库总表数是 1000 且 minTablesPerVnode 设置的也是 1000，那么所有的表都会分布在 1 个 vgroup 上。此时如果将 minTablesPerVnode 和 tablelncStepPerVnode 都设置成 100， 则可将表分布至 10 个 vgroup。（假设 maxVgroupsPerDb 大于等于 10）。
如果总表数比较大（比如大于500万），适当增加 maxVgroupsPerDb 也能显著提高建表的速度。maxVgroupsPerDb 默认值为 0， 自动配置为 CPU 的核数。 如果表的数量巨大，也建议调节 maxTablesPerVnode 参数，以免超过单个 vnode 建表的上限。
更多调优参数，请参考 [配置参考](../../../reference/config)部分。
## 高效写入示例 {#sample-code}
### 场景设计 {#scenario}
下面的示例程序展示了如何高效写入数据，场景设计如下：
- TDengine 客户端程序从其它数据源不断读入数据，在示例程序中采用生成模拟数据的方式来模拟读取数据源
- 单个连接向 TDengine 写入的速度无法与读数据的速度相匹配，因此客户端程序启动多个线程，每个线程都建立了与 TDengine 的连接，每个线程都有一个独占的固定大小的消息队列
- 客户端程序将接收到的数据根据所属的表名（或子表名）HASH 到不同的线程，即写入该线程所对应的消息队列，以此确保属于某个表（或子表）的数据一定会被一个固定的线程处理
- 各个子线程在将所关联的消息队列中的数据读空后或者读取数据量达到一个预定的阈值后将该批数据写入 TDengine，并继续处理后面接收到的数据
![TDengine 高效写入示例场景的线程模型](highvolume.webp)
### 示例代码 {#code}
这一部分是针对以上场景的示例代码。对于其它场景高效写入原理相同，不过代码需要适当修改。
本示例代码假设源数据属于同一张超级表(meters)的不同子表。程序在开始写入数据之前已经在 test 库创建了这个超级表。对于子表，将根据收到的数据，由应用程序自动创建。如果实际场景是多个超级表，只需修改写任务自动建表的代码。
<Tabs defaultValue="java" groupId="lang">
<TabItem label="Java" value="java">
**程序清单**
| 类名 | 功能说明 |
| ---------------- | --------------------------------------------------------------------------- |
| FastWriteExample | 主程序 |
| ReadTask | 从模拟源中读取数据，将表名经过 hash 后得到 Queue 的 index，写入对应的 Queue |
| WriteTask | 从 Queue 中获取数据，组成一个 Batch，写入 TDengine |
| MockDataSource | 模拟生成一定数量 meters 子表的数据 |
| SQLWriter | WriteTask 依赖这个类完成 SQL 拼接、自动建表、 SQL 写入、SQL 长度检查 |
| StmtWriter | 实现参数绑定方式批量写入（暂未完成） |
| DataBaseMonitor | 统计写入速度，并每隔 10 秒把当前写入速度打印到控制台 |
以下是各类的完整代码和更详细的功能说明。
<details>
<summary>FastWriteExample</summary>
主程序负责：
1. 创建消息队列
2. 启动写线程
3. 启动读线程
4. 每隔 10 秒统计一次写入速度
主程序默认暴露了 4 个参数，每次启动程序都可调节，用于测试和调优：
1. 读线程个数。默认为 1。
2. 写线程个数。默认为 3。
3. 模拟生成的总表数。默认为 1000。将会平分给各个读线程。如果总表数较大，建表需要花费较长，开始统计的写入速度可能较慢。
4. 每批最多写入记录数量。默认为 3000。
队列容量(taskQueueCapacity)也是与性能有关的参数，可通过修改程序调节。一般来讲，队列容量越大，入队被阻塞的概率越小，队列的吞吐量越大，但是内存占用也会越大。 示例程序默认值已经设置地足够大。
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/FastWriteExample.java}}
```
</details>
<details>
<summary>ReadTask</summary>
读任务负责从数据源读数据。每个读任务都关联了一个模拟数据源。每个模拟数据源可生成一点数量表的数据。不同的模拟数据源生成不同表的数据。
读任务采用阻塞的方式写消息队列。也就是说，一旦队列满了，写操作就会阻塞。
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/ReadTask.java}}
```
</details>
<details>
<summary>WriteTask</summary>
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/WriteTask.java}}
```
</details>
<details>
<summary>MockDataSource</summary>
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/MockDataSource.java}}
```
</details>
<details>
<summary>SQLWriter</summary>
SQLWriter 类封装了拼 SQL 和写数据的逻辑。注意，所有的表都没有提前创建，而是在 catch 到表不存在异常的时候，再以超级表为模板批量建表，然后重新执行 INSERT 语句。对于其它异常，这里简单地记录当时执行的 SQL 语句到日志中，你也可以记录更多线索到日志，已便排查错误和故障恢复。
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/SQLWriter.java}}
```
</details>
<details>
<summary>DataBaseMonitor</summary>
```java
{{#include docs/examples/java/src/main/java/com/taos/example/highvolume/DataBaseMonitor.java}}
```
</details>
**执行步骤**
<details>
<summary>执行 Java 示例程序</summary>
执行程序前需配置环境变量 `TDENGINE_JDBC_URL`。如果 TDengine Server 部署在本机，且用户名、密码和端口都是默认值，那么可配置：
```
TDENGINE_JDBC_URL="jdbc:TAOS://localhost:6030?user=root&password=taosdata"
```
**本地集成开发环境执行示例程序**
1. clone TDengine 仓库
```
git clone git@github.com:taosdata/TDengine.git --depth 1
```
2. 用集成开发环境打开 `docs/examples/java` 目录。
3. 在开发环境中配置环境变量 `TDENGINE_JDBC_URL`。如果已配置了全局的环境变量 `TDENGINE_JDBC_URL` 可跳过这一步。
4. 运行类 `com.taos.example.highvolume.FastWriteExample`。
**远程服务器上执行示例程序**
若要在服务器上执行示例程序，可按照下面的步骤操作：
1. 打包示例代码。在目录 TDengine/docs/examples/java 下执行：
```
mvn package
```
2. 远程服务器上创建 examples 目录：
```
mkdir -p examples/java
```
3. 复制依赖到服务器指定目录：
- 复制依赖包，只用复制一次
```
scp -r .\target\lib <user>@<host>:~/examples/java
```
- 复制本程序的 jar 包，每次更新代码都需要复制
```
scp -r .\target\javaexample-1.0.jar <user>@<host>:~/examples/java
```
4. 配置环境变量。
编辑 `~/.bash_profile` 或 `~/.bashrc` 添加如下内容例如：
```
export TDENGINE_JDBC_URL="jdbc:TAOS://localhost:6030?user=root&password=taosdata"
```
以上使用的是本地部署 TDengine Server 时默认的 JDBC URL。你需要根据自己的实际情况更改。
5. 用 java 命令启动示例程序，命令模板：
```
java -classpath lib/*:javaexample-1.0.jar com.taos.example.highvolume.FastWriteExample <read_thread_count> <white_thread_count> <total_table_count> <max_batch_size>
```
6. 结束测试程序。测试程序不会自动结束，在获取到当前配置下稳定的写入速度后，按 <kbd>CTRL</kbd> + <kbd>C</kbd> 结束程序。
下面是一次实际运行的日志输出，机器配置 16核 + 64G + 固态硬盘。
```
root@vm85$ java -classpath lib/*:javaexample-1.0.jar com.taos.example.highvolume.FastWriteExample 2 12
18:56:35.896 [main] INFO c.t.e.highvolume.FastWriteExample - readTaskCount=2, writeTaskCount=12 tableCount=1000 maxBatchSize=3000
18:56:36.011 [WriteThread-0] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.015 [WriteThread-0] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.021 [WriteThread-1] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.022 [WriteThread-1] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.031 [WriteThread-2] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.032 [WriteThread-2] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.041 [WriteThread-3] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.042 [WriteThread-3] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.093 [WriteThread-4] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.094 [WriteThread-4] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.099 [WriteThread-5] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.100 [WriteThread-5] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.100 [WriteThread-6] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.101 [WriteThread-6] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.103 [WriteThread-7] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.104 [WriteThread-7] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.105 [WriteThread-8] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.107 [WriteThread-8] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.108 [WriteThread-9] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.109 [WriteThread-9] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.156 [WriteThread-10] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.157 [WriteThread-11] INFO c.taos.example.highvolume.WriteTask - started
18:56:36.158 [WriteThread-10] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:36.158 [ReadThread-0] INFO com.taos.example.highvolume.ReadTask - started
18:56:36.158 [ReadThread-1] INFO com.taos.example.highvolume.ReadTask - started
18:56:36.158 [WriteThread-11] INFO c.taos.example.highvolume.SQLWriter - maxSQLLength=1048576
18:56:46.369 [main] INFO c.t.e.highvolume.FastWriteExample - count=18554448 speed=1855444
18:56:56.946 [main] INFO c.t.e.highvolume.FastWriteExample - count=39059660 speed=2050521
18:57:07.322 [main] INFO c.t.e.highvolume.FastWriteExample - count=59403604 speed=2034394
18:57:18.032 [main] INFO c.t.e.highvolume.FastWriteExample - count=80262938 speed=2085933
18:57:28.432 [main] INFO c.t.e.highvolume.FastWriteExample - count=101139906 speed=2087696
18:57:38.921 [main] INFO c.t.e.highvolume.FastWriteExample - count=121807202 speed=2066729
18:57:49.375 [main] INFO c.t.e.highvolume.FastWriteExample - count=142952417 speed=2114521
18:58:00.689 [main] INFO c.t.e.highvolume.FastWriteExample - count=163650306 speed=2069788
18:58:11.646 [main] INFO c.t.e.highvolume.FastWriteExample - count=185019808 speed=2136950
```
</details>
</TabItem>
<TabItem label="Python" value="python">
**程序清单**
Python 示例程序中采用了多进程的架构，并使用了跨进程的消息队列。
| 函数或类 | 功能说明 |
| ------------------------ | -------------------------------------------------------------------- |
| main 函数 | 程序入口， 创建各个子进程和消息队列 |
| run_monitor_process 函数 | 创建数据库，超级表，统计写入速度并定时打印到控制台 |
| run_read_task 函数 | 读进程主要逻辑，负责从其它数据系统读数据，并分发数据到为之分配的队列 |
| MockDataSource 类 | 模拟数据源, 实现迭代器接口，每次批量返回每张表的接下来 1000 条数据 |
| run_write_task 函数 | 写进程主要逻辑。每次从队列中取出尽量多的数据，并批量写入 |
| SQLWriter类 | SQL 写入和自动建表 |
| StmtWriter 类 | 实现参数绑定方式批量写入（暂未完成） |
<details>
<summary>main 函数</summary>
main 函数负责创建消息队列和启动子进程，子进程有 3 类：
1. 1 个监控进程，负责数据库初始化和统计写入速度
2. n 个读进程，负责从其它数据系统读数据
3. m 个写进程，负责写数据库
main 函数可以接收 5 个启动参数，依次是：
1. 读任务（进程）数, 默认为 1
2. 写任务（进程）数, 默认为 1
3. 模拟生成的总表数，默认为 1000
4. 队列大小（单位字节），默认为 1000000
5. 每批最多写入记录数量， 默认为 3000
```python
{{#include docs/examples/python/fast_write_example.py:main}}
```
</details>
<details>
<summary>run_monitor_process</summary>
监控进程负责初始化数据库，并监控当前的写入速度。
```python
{{#include docs/examples/python/fast_write_example.py:monitor}}
```
</details>
<details>
<summary>run_read_task 函数</summary>
读进程，负责从其它数据系统读数据，并分发数据到为之分配的队列。
```python
{{#include docs/examples/python/fast_write_example.py:read}}
```
</details>
<details>
<summary>MockDataSource</summary>
以下是模拟数据源的实现，我们假设数据源生成的每一条数据都带有目标表名信息。实际中你可能需要一定的规则确定目标表名。
```python
{{#include docs/examples/python/mockdatasource.py}}
```
</details>
<details>
<summary>run_write_task 函数</summary>
写进程每次从队列中取出尽量多的数据，并批量写入。
```python
{{#include docs/examples/python/fast_write_example.py:write}}
```
</details>
<details>
SQLWriter 类封装了拼 SQL 和写数据的逻辑。所有的表都没有提前创建，而是在发生表不存在错误的时候，再以超级表为模板批量建表，然后重新执行 INSERT 语句。对于其它错误会记录当时执行的 SQL， 以便排查错误和故障恢复。这个类也对 SQL 是否超过最大长度限制做了检查，如果接近 SQL 最大长度限制（maxSQLLength），将会立即执行 SQL。为了减少 SQL 此时，建议将 maxSQLLength 适当调大。
<summary>SQLWriter</summary>
```python
{{#include docs/examples/python/sql_writer.py}}
```
</details>
**执行步骤**
<details>
<summary>执行 Python 示例程序</summary>
1. 前提条件
- 已安装 TDengine 客户端驱动
- 已安装 Python3， 推荐版本 >= 3.8
- 已安装 taospy
2. 安装 faster-fifo 代替 python 内置的 multiprocessing.Queue
```
pip3 install faster-fifo
```
3. 点击上面的“查看源码”链接复制 `fast_write_example.py` 、 `sql_writer.py` 和 `mockdatasource.py` 三个文件。
4. 执行示例程序
```
python3 fast_write_example.py <READ_TASK_COUNT> <WRITE_TASK_COUNT> <TABLE_COUNT> <QUEUE_SIZE> <MAX_BATCH_SIZE>
```
下面是一次实际运行的输出, 机器配置 16核 + 64G + 固态硬盘。
```
root@vm85$ python3 fast_write_example.py 8 8
2022-07-14 19:13:45,869 [root] - READ_TASK_COUNT=8, WRITE_TASK_COUNT=8, TABLE_COUNT=1000, QUEUE_SIZE=1000000, MAX_BATCH_SIZE=3000
2022-07-14 19:13:48,882 [root] - WriteTask-0 started with pid 718347
2022-07-14 19:13:48,883 [root] - WriteTask-1 started with pid 718348
2022-07-14 19:13:48,884 [root] - WriteTask-2 started with pid 718349
2022-07-14 19:13:48,884 [root] - WriteTask-3 started with pid 718350
2022-07-14 19:13:48,885 [root] - WriteTask-4 started with pid 718351
2022-07-14 19:13:48,885 [root] - WriteTask-5 started with pid 718352
2022-07-14 19:13:48,886 [root] - WriteTask-6 started with pid 718353
2022-07-14 19:13:48,886 [root] - WriteTask-7 started with pid 718354
2022-07-14 19:13:48,887 [root] - ReadTask-0 started with pid 718355
2022-07-14 19:13:48,888 [root] - ReadTask-1 started with pid 718356
2022-07-14 19:13:48,889 [root] - ReadTask-2 started with pid 718357
2022-07-14 19:13:48,889 [root] - ReadTask-3 started with pid 718358
2022-07-14 19:13:48,890 [root] - ReadTask-4 started with pid 718359
2022-07-14 19:13:48,891 [root] - ReadTask-5 started with pid 718361
2022-07-14 19:13:48,892 [root] - ReadTask-6 started with pid 718364
2022-07-14 19:13:48,893 [root] - ReadTask-7 started with pid 718365
2022-07-14 19:13:56,042 [DataBaseMonitor] - count=6676310 speed=667631.0
2022-07-14 19:14:06,196 [DataBaseMonitor] - count=20004310 speed=1332800.0
2022-07-14 19:14:16,366 [DataBaseMonitor] - count=32290310 speed=1228600.0
2022-07-14 19:14:26,527 [DataBaseMonitor] - count=44438310 speed=1214800.0
2022-07-14 19:14:36,673 [DataBaseMonitor] - count=56608310 speed=1217000.0
2022-07-14 19:14:46,834 [DataBaseMonitor] - count=68757310 speed=1214900.0
2022-07-14 19:14:57,280 [DataBaseMonitor] - count=80992310 speed=1223500.0
2022-07-14 19:15:07,689 [DataBaseMonitor] - count=93805310 speed=1281300.0
2022-07-14 19:15:18,020 [DataBaseMonitor] - count=106111310 speed=1230600.0
2022-07-14 19:15:28,356 [DataBaseMonitor] - count=118394310 speed=1228300.0
2022-07-14 19:15:38,690 [DataBaseMonitor] - count=130742310 speed=1234800.0
2022-07-14 19:15:49,000 [DataBaseMonitor] - count=143051310 speed=1230900.0
2022-07-14 19:15:59,323 [DataBaseMonitor] - count=155276310 speed=1222500.0
2022-07-14 19:16:09,649 [DataBaseMonitor] - count=167603310 speed=1232700.0
2022-07-14 19:16:19,995 [DataBaseMonitor] - count=179976310 speed=1237300.0
```
</details>
:::note
使用 Python 连接器多进程连接 TDengine 的时候，有一个限制：不能在父进程中建立连接，所有连接只能在子进程中创建。
如果在父进程中创建连接，子进程再创建连接就会一直阻塞。这是个已知问题。
:::
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@ -52,7 +52,7 @@ Query OK, 2 row(s) in set (0.001100s)
### 示例一
在 TAOS Shell，查找加利福尼亚州所有智能电表采集的电压平均值，并按照 location 分组。
在 TDengine CLI，查找加利福尼亚州所有智能电表采集的电压平均值，并按照 location 分组。
```
taos> SELECT AVG(voltage), location FROM meters GROUP BY location;
@ -65,7 +65,7 @@ Query OK, 2 rows in database (0.005995s)
### 示例二
在 TAOS shell, 查找 groupId 为 2 的所有智能电表的记录条数，电流的最大值。
在 TDengine CLI, 查找 groupId 为 2 的所有智能电表的记录条数，电流的最大值。
```
taos> SELECT count(*), max(current) FROM meters where groupId = 2;

10
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@ -20,11 +20,11 @@ create database db0 vgroups 100 buffer 16MB
## 读缓存
在创建数据库时可以选择是否缓存该数据库中每个子表的最新数据。由参数 cachelast 设置，分为三种情况：
- 0: 不缓存
- 1: 缓存子表最近一行数据，这将显著改善 last_row 函数的性能
- 2: 缓存子表每一列最近的非 NULL 值，这将显著改善无特殊影响（比如 WHERE, ORDER BY, GROUP BY, INTERVAL）时的 last 函数的性能
- 3: 同时缓存行和列，即等同于上述 cachelast 值为 1 或 2 时的行为同时生效
在创建数据库时可以选择是否缓存该数据库中每个子表的最新数据。由参数 cachemodel 设置，分为四种情况：
- none: 不缓存
- last_row: 缓存子表最近一行数据，这将显著改善 last_row 函数的性能
- last_value: 缓存子表每一列最近的非 NULL 值，这将显著改善无特殊影响（比如 WHERE, ORDER BY, GROUP BY, INTERVAL）时的 last 函数的性能
- both: 同时缓存最近的行和列，即等同于上述 cachemodel 值为 last_row 和 last_value 的行为同时生效
## 元数据缓存

4
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@ -71,7 +71,7 @@ serverPort 6030
## 启动集群
按照《立即开始》里的步骤，启动第一个数据节点，例如 h1.taosdata.com，然后执行 taos，启动 taos shell，从 shell 里执行命令“SHOW DNODES”，如下所示：
按照《立即开始》里的步骤，启动第一个数据节点，例如 h1.taosdata.com，然后执行 taos，启动 TDengine CLI，在其中执行命令 “SHOW DNODES”，如下所示：
```
taos> show dnodes;
@ -115,7 +115,7 @@ SHOW DNODES;
任何已经加入集群在线的数据节点，都可以作为后续待加入节点的 firstEp。
firstEp 这个参数仅仅在该数据节点首次加入集群时有作用，加入集群后，该数据节点会保存最新的 mnode 的 End Point 列表，不再依赖这个参数。
接下来，配置文件中的 firstEp 参数就主要在客户端连接的时候使用了，例如 taos shell 如果不加参数，会默认连接由 firstEp 指定的节点。
接下来，配置文件中的 firstEp 参数就主要在客户端连接的时候使用了，例如 TDengine CLI 如果不加参数，会默认连接由 firstEp 指定的节点。
两个没有配置 firstEp 参数的数据节点 dnode 启动后，会独立运行起来。这个时候，无法将其中一个数据节点加入到另外一个数据节点，形成集群。无法将两个独立的集群合并成为新的集群。
:::

3
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@ -10,6 +10,7 @@ description: 利用 Kubernetes 部署 TDengine 集群的详细指南
要使用 Kubernetes 部署管理 TDengine 集群，需要做好如下准备工作。
* 本文适用 Kubernetes v1.5 以上版本
* 本文和下一章使用 minikube、kubectl 和 helm 等工具进行安装部署，请提前安装好相应软件
* Kubernetes 已经安装部署并能正常访问使用或更新必要的容器仓库或其他服务
@ -366,7 +367,7 @@ kubectl scale statefulsets tdengine --replicas=1
```
在 taos shell 中的所有数据库操作将无法成功。
在 TDengine CLI 中的所有数据库操作将无法成功。
```
taos> show dnodes;

43
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@ -10,27 +10,27 @@ description: 对表的各种管理操作
```sql
CREATE TABLE [IF NOT EXISTS] [db_name.]tb_name (create_definition [, create_definitionn] ...) [table_options]
CREATE TABLE create_subtable_clause
CREATE TABLE [IF NOT EXISTS] [db_name.]tb_name (create_definition [, create_definitionn] ...)
[TAGS (create_definition [, create_definitionn] ...)]
[table_options]
create_subtable_clause: {
create_subtable_clause [create_subtable_clause] ...
| [IF NOT EXISTS] [db_name.]tb_name USING [db_name.]stb_name [(tag_name [, tag_name] ...)] TAGS (tag_value [, tag_value] ...)
}
create_definition:
col_name column_definition
column_definition:
type_name [comment 'string_value']
table_options:
table_option ...
table_option: {
COMMENT 'string_value'
| WATERMARK duration[,duration]
@ -54,12 +54,13 @@ table_option: {
需要注意的是转义字符中的内容必须是可打印字符。
**参数说明**
1. COMMENT：表注释。可用于超级表、子表和普通表。
2. WATERMARK：指定窗口的关闭时间，默认值为 5 秒，最小单位毫秒，范围为0到15分钟，多个以逗号分隔。只可用于超级表，且只有当数据库使用了RETENTIONS参数时，才可以使用此表参数。
3. MAX_DELAY：用于控制推送计算结果的最大延迟，默认值为 interval 的值(但不能超过最大值)，最小单位毫秒，范围为1毫秒到15分钟，多个以逗号分隔。注：不建议 MAX_DELAY 设置太小，否则会过于频繁的推送结果，影响存储和查询性能，如无特殊需求，取默认值即可。只可用于超级表，且只有当数据库使用了RETENTIONS参数时，才可以使用此表参数。
4. ROLLUP：Rollup 指定的聚合函数，提供基于多层级的降采样聚合结果。只可用于超级表。只有当数据库使用了RETENTIONS参数时，才可以使用此表参数。作用于超级表除TS列外的其它所有列，但是只能定义一个聚合函数。 聚合函数支持 avg, sum, min, max, last, first。
5. SMA：Small Materialized Aggregates，提供基于数据块的自定义预计算功能。预计算类型包括MAX、MIN和SUM。可用于超级表/普通表。
6. TTL：Time to Live，是用户用来指定表的生命周期的参数。如果在持续的TTL时间内，都没有数据写入该表，则TDengine系统会自动删除该表。这个TTL的时间只是一个大概时间，我们系统不保证到了时间一定会将其删除，而只保证存在这样一个机制。TTL单位是天，默认为0，表示不限制。用户需要注意，TTL优先级高于KEEP，即TTL时间满足删除机制时，即使当前数据的存在时间小于KEEP，此表也会被删除。只可用于子表和普通表。
2. WATERMARK：指定窗口的关闭时间，默认值为 5 秒，最小单位毫秒，范围为 0 到 15 分钟，多个以逗号分隔。只可用于超级表，且只有当数据库使用了 RETENTIONS 参数时，才可以使用此表参数。
3. MAX_DELAY：用于控制推送计算结果的最大延迟，默认值为 interval 的值(但不能超过最大值)，最小单位毫秒，范围为 1 毫秒到 15 分钟，多个以逗号分隔。注：不建议 MAX_DELAY 设置太小，否则会过于频繁的推送结果，影响存储和查询性能，如无特殊需求，取默认值即可。只可用于超级表，且只有当数据库使用了 RETENTIONS 参数时，才可以使用此表参数。
4. ROLLUP：Rollup 指定的聚合函数，提供基于多层级的降采样聚合结果。只可用于超级表。只有当数据库使用了 RETENTIONS 参数时，才可以使用此表参数。作用于超级表除 TS 列外的其它所有列，但是只能定义一个聚合函数。 聚合函数支持 avg, sum, min, max, last, first。
5. SMA：Small Materialized Aggregates，提供基于数据块的自定义预计算功能。预计算类型包括 MAX、MIN 和 SUM。可用于超级表/普通表。
6. TTL：Time to Live，是用户用来指定表的生命周期的参数。如果创建表时指定了这个参数，当该表的存在时间超过 TTL 指定的时间后，TDengine 自动删除该表。这个 TTL 的时间只是一个大概时间，系统不保证到了时间一定会将其删除，而只保证存在这样一个机制且最终一定会删除。TTL 单位是天，默认为 0，表示不限制，到期时间为表创建时间加上 TTL 时间。
## 创建子表
@ -89,7 +90,7 @@ CREATE TABLE [IF NOT EXISTS] tb_name1 USING stb_name TAGS (tag_value1, ...) [IF
```sql
ALTER TABLE [db_name.]tb_name alter_table_clause
alter_table_clause: {
alter_table_options
| ADD COLUMN col_name column_type
@ -97,10 +98,10 @@ alter_table_clause: {
| MODIFY COLUMN col_name column_type
| RENAME COLUMN old_col_name new_col_name
}
alter_table_options:
alter_table_option ...
alter_table_option: {
TTL value
| COMMENT 'string_value'
@ -110,6 +111,7 @@ alter_table_option: {
**使用说明**
对普通表可以进行如下修改操作
1. ADD COLUMN：添加列。
2. DROP COLUMN：删除列。
3. MODIFY COLUMN：修改列定义，如果数据列的类型是可变长类型，那么可以使用此指令修改其宽度，只能改大，不能改小。
@ -143,15 +145,15 @@ ALTER TABLE tb_name RENAME COLUMN old_col_name new_col_name
```sql
ALTER TABLE [db_name.]tb_name alter_table_clause
alter_table_clause: {
alter_table_options
| SET TAG tag_name = new_tag_value
}
alter_table_options:
alter_table_option ...
alter_table_option: {
TTL value
| COMMENT 'string_value'
@ -159,6 +161,7 @@ alter_table_option: {
```
**使用说明**
1. 对子表的列和标签的修改，除了更改标签值以外，都要通过超级表才能进行。
### 修改子表标签值
@ -169,7 +172,7 @@ ALTER TABLE tb_name SET TAG tag_name=new_tag_value;
## 删除表
可以在一条SQL语句中删除一个或多个普通表或子表。
可以在一条 SQL 语句中删除一个或多个普通表或子表。
```sql
DROP TABLE [IF EXISTS] [db_name.]tb_name [, [IF EXISTS] [db_name.]tb_name] ...
@ -179,7 +182,7 @@ DROP TABLE [IF EXISTS] [db_name.]tb_name [, [IF EXISTS] [db_name.]tb_name] ...
### 显示所有表
如下SQL语句可以列出当前数据库中的所有表名。
如下 SQL 语句可以列出当前数据库中的所有表名。
```sql
SHOW TABLES [LIKE tb_name_wildchar];

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@ -1167,7 +1167,7 @@ SELECT stateDuration(field_name, oper, val, unit) FROM { tb_name | stb_name } [W
**参数范围**：
- oper : "LT" (小于)、"GT"（大于）、"LE"（小于等于）、"GE"（大于等于）、"NE"（不等于）、"EQ"（等于），不区分大小写。
- oper : `'LT'` (小于)、`'GT'`（大于）、`'LE'`（小于等于）、`'GE'`（大于等于）、`'NE'`（不等于）、`'EQ'`（等于），不区分大小写，但需要用`''`包括。
- val : 数值型
- unit : 时间长度的单位，可取值时间单位： 1b(纳秒), 1u(微秒)，1a(毫秒)，1s(秒)，1m(分)，1h(小时)，1d(天), 1w(周)。如果省略，默认为当前数据库精度。

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@ -31,7 +31,7 @@ description: 合法字符集和命名中的限制规则
- 最多允许 4096 列，最少需要 2 列，第一列必须是时间戳。
- 标签名最大长度为 64
- 最多允许 128 个，至少要有 1 个标签，一个表中标签值的总长度不超过 16KB
- SQL 语句最大长度 1048576 个字符，也可通过客户端配置参数 maxSQLLength 修改，取值范围 65480 ~ 1048576
- SQL 语句最大长度 1048576 个字符
- SELECT 语句的查询结果，最多允许返回 4096 列（语句中的函数调用可能也会占用一些列空间），超限时需要显式指定较少的返回数据列，以避免语句执行报错
- 库的数目，超级表的数目、表的数目，系统不做限制，仅受系统资源限制
- 数据库的副本数只能设置为 1 或 3

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@ -195,7 +195,7 @@ SHOW STREAMS;
SHOW SUBSCRIPTIONS;
```
显示当前数据库下的所有的订阅关系
显示当前系统内所有的订阅关系
## SHOW TABLES

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@ -32,7 +32,7 @@ taos> show databases;
Query OK, 2 rows in database (0.033802s)
```
因为运行在容器中的 TDengine 服务端使用容器的 hostname 建立连接，使用 taos shell 或者各种连接器（例如 JDBC-JNI）从容器外访问容器内的 TDengine 比较复杂，所以上述方式是访问容器中 TDengine 服务的最简单的方法，适用于一些简单场景。如果在一些复杂场景下想要从容器化使用 taos shell 或者各种连接器访问容器中的 TDengine 服务，请参考下一节。
因为运行在容器中的 TDengine 服务端使用容器的 hostname 建立连接，使用 TDengine CLI 或者各种连接器（例如 JDBC-JNI）从容器外访问容器内的 TDengine 比较复杂，所以上述方式是访问容器中 TDengine 服务的最简单的方法，适用于一些简单场景。如果在一些复杂场景下想要从容器化使用 TDengine CLI 或者各种连接器访问容器中的 TDengine 服务，请参考下一节。
## 在 host 网络上启动 TDengine
@ -75,7 +75,7 @@ docker run -d \
echo 127.0.0.1 tdengine |sudo tee -a /etc/hosts
```
最后，可以从 taos shell 或者任意连接器以 "tdengine" 为服务端地址访问 TDengine 服务。
最后，可以从 TDengine CLI 或者任意连接器以 "tdengine" 为服务端地址访问 TDengine 服务。
```shell
taos -h tdengine -P 6030
@ -354,7 +354,7 @@ test-docker_td-2_1 /tini -- /usr/bin/entrypoi ... Up
test-docker_td-3_1 /tini -- /usr/bin/entrypoi ... Up
```
4. 用 taos shell 查看 dnodes
4. 用 TDengine CLI 查看 dnodes
```shell

48
docs/zh/17-operation/01-pkg-install.md
View File

@ -47,7 +47,7 @@ lrwxrwxrwx 1 root root 13 Feb 22 09:34 log -> /var/log/taos/
<Tabs>
<TabItem label="apt-get 卸载" value="aptremove">
卸载命令如下:
TDengine 卸载命令如下:
```
$ sudo apt-get remove tdengine
@ -65,10 +65,26 @@ TDengine is removed successfully!
```
taosTools 卸载命令如下:
```
$ sudo apt remove taostools
Reading package lists... Done
Building dependency tree
Reading state information... Done
The following packages will be REMOVED:
taostools
0 upgraded, 0 newly installed, 1 to remove and 0 not upgraded.
After this operation, 68.3 MB disk space will be freed.
Do you want to continue? [Y/n]
(Reading database ... 147973 files and directories currently installed.)
Removing taostools (2.1.2) ...
```
</TabItem>
<TabItem label="Deb 卸载" value="debuninst">
卸载命令如下:
TDengine 卸载命令如下:
```
$ sudo dpkg -r tdengine
@ -78,28 +94,52 @@ TDengine is removed successfully!
```
taosTools 卸载命令如下:
```
$ sudo dpkg -r taostools
(Reading database ... 147973 files and directories currently installed.)
Removing taostools (2.1.2) ...
```
</TabItem>
<TabItem label="RPM 卸载" value="rpmuninst">
卸载命令如下:
卸载 TDengine 命令如下:
```
$ sudo rpm -e tdengine
TDengine is removed successfully!
```
卸载 taosTools 命令如下:
```
sudo rpm -e taostools
taosToole is removed successfully!
```
</TabItem>
<TabItem label="tar.gz 卸载" value="taruninst">
卸载命令如下:
卸载 TDengine 命令如下:
```
$ rmtaos
TDengine is removed successfully!
```
卸载 taosTools 命令如下：
```
$ rmtaostools
Start to uninstall taos tools ...
taos tools is uninstalled successfully!
```
</TabItem>
<TabItem label="Windows 卸载" value="windows">
在 C:\TDengine 目录下，通过运行 unins000.exe 卸载程序来卸载 TDengine。

2
docs/zh/17-operation/08-export.md
View File

@ -7,7 +7,7 @@ description: 如何导出 TDengine 中的数据
## 按表导出 CSV 文件
如果用户需要导出一个表或一个 STable 中的数据，可在 taos shell 中运行：
如果用户需要导出一个表或一个 STable 中的数据，可在 TDengine CLI 中运行：
```sql
select * from <tb_name> >> data.csv;

2
docs/zh/27-train-faq/01-faq.md
View File

@ -116,7 +116,7 @@ charset UTF-8
### 9. 表名显示不全
由于 taos shell 在终端中显示宽度有限，有可能比较长的表名显示不全，如果按照显示的不全的表名进行相关操作会发生 Table does not exist 错误。解决方法可以是通过修改 taos.cfg 文件中的设置项 maxBinaryDisplayWidth， 或者直接输入命令 set max_binary_display_width 100。或者在命令结尾使用 \G 参数来调整结果的显示方式。
由于 TDengine CLI 在终端中显示宽度有限，有可能比较长的表名显示不全，如果按照显示的不全的表名进行相关操作会发生 Table does not exist 错误。解决方法可以是通过修改 taos.cfg 文件中的设置项 maxBinaryDisplayWidth， 或者直接输入命令 set max_binary_display_width 100。或者在命令结尾使用 \G 参数来调整结果的显示方式。
### 10. 如何进行数据迁移？

2
examples/JDBC/JDBCDemo/README-jdbc-windows.md
View File

@ -129,7 +129,7 @@ https://www.taosdata.com/cn/all-downloads/
192.168.236.136 td01
```
配置完成后，在命令行内使用taos shell连接server端
配置完成后，在命令行内使用TDengine CLI连接server端
```shell
C:\TDengine>taos -h td01

11
examples/c/tmq_taosx.c
View File

@ -163,6 +163,13 @@ int32_t init_env() {
}
taos_free_result(pRes);
pRes = taos_query(pConn, "create table if not exists ct4 using st1(t3) tags('ct4')");
if (taos_errno(pRes) != 0) {
printf("failed to create child table ct4, reason:%s\n", taos_errstr(pRes));
return -1;
}
taos_free_result(pRes);
pRes = taos_query(pConn, "insert into ct3 values(1626006833600, 5, 6, 'c') ct1 values(1626006833601, 2, 3, 'sds') (1626006833602, 4, 5, 'ddd') ct0 values(1626006833602, 4, 3, 'hwj') ct1 values(now+5s, 23, 32, 's21ds')");
if (taos_errno(pRes) != 0) {
printf("failed to insert into ct3, reason:%s\n", taos_errstr(pRes));
@ -379,6 +386,8 @@ tmq_t* build_consumer() {
tmq_conf_set(conf, "td.connect.pass", "taosdata");
tmq_conf_set(conf, "msg.with.table.name", "true");
tmq_conf_set(conf, "enable.auto.commit", "true");
tmq_conf_set(conf, "experimental.snapshot.enable", "true");
/*tmq_conf_set(conf, "experimental.snapshot.enable", "true");*/
@ -406,7 +415,7 @@ void basic_consume_loop(tmq_t* tmq, tmq_list_t* topics) {
}
int32_t cnt = 0;
while (running) {
TAOS_RES* tmqmessage = tmq_consumer_poll(tmq, -1);
TAOS_RES* tmqmessage = tmq_consumer_poll(tmq, 1000);
if (tmqmessage) {
cnt++;
msg_process(tmqmessage);

2
examples/nodejs/README-win.md
View File

@ -35,7 +35,7 @@ Python 2.7.18
下载地址：https://www.taosdata.com/cn/all-downloads/，选择一个合适的windows-client下载（client应该尽量与server端的版本保持一致）
使用client的taos shell连接server
使用client的TDengine CLI连接server
```shell
>taos -h node5

1
include/common/tcommon.h
View File

@ -184,6 +184,7 @@ typedef struct SQueryTableDataCond {
STimeWindow twindows;
int64_t startVersion;
int64_t endVersion;
int64_t schemaVersion;
} SQueryTableDataCond;
int32_t tEncodeDataBlock(void** buf, const SSDataBlock* pBlock);

1
include/common/tdataformat.h
View File

@ -96,6 +96,7 @@ char *tTagValToData(const STagVal *pTagVal, bool isJson);
int32_t tEncodeTag(SEncoder *pEncoder, const STag *pTag);
int32_t tDecodeTag(SDecoder *pDecoder, STag **ppTag);
int32_t tTagToValArray(const STag *pTag, SArray **ppArray);
void tTagSetCid(const STag *pTag, int16_t iTag, int16_t cid);
void debugPrintSTag(STag *pTag, const char *tag, int32_t ln); // TODO: remove
int32_t parseJsontoTagData(const char *json, SArray *pTagVals, STag **ppTag, void *pMsgBuf);

36
include/common/tmsg.h
View File

@ -2617,7 +2617,7 @@ enum {
typedef struct {
int8_t type;
union {
// snapshot data
// snapshot
struct {
int64_t uid;
int64_t ts;
@ -2677,15 +2677,6 @@ typedef struct {
int32_t tSerializeSMDropSmaReq(void* buf, int32_t bufLen, SMDropSmaReq* pReq);
int32_t tDeserializeSMDropSmaReq(void* buf, int32_t bufLen, SMDropSmaReq* pReq);
typedef struct {
int32_t vgId;
SEpSet epSet;
} SVgEpSet;
typedef struct {
int32_t padding;
} SRSmaExecMsg;
typedef struct {
int8_t version; // for compatibility(default 0)
int8_t intervalUnit; // MACRO: TIME_UNIT_XXX
@ -2945,33 +2936,14 @@ static FORCE_INLINE void tDeleteSMqSubTopicEp(SMqSubTopicEp* pSubTopicEp) {
typedef struct {
SMqRspHead head;
int64_t reqOffset;
int64_t rspOffset;
STqOffsetVal reqOffsetNew;
STqOffsetVal rspOffsetNew;
STqOffsetVal rspOffset;
int16_t resMsgType;
int32_t metaRspLen;
void* metaRsp;
} SMqMetaRsp;
static FORCE_INLINE int32_t tEncodeSMqMetaRsp(void** buf, const SMqMetaRsp* pRsp) {
int32_t tlen = 0;
tlen += taosEncodeFixedI64(buf, pRsp->reqOffset);
tlen += taosEncodeFixedI64(buf, pRsp->rspOffset);
tlen += taosEncodeFixedI16(buf, pRsp->resMsgType);
tlen += taosEncodeFixedI32(buf, pRsp->metaRspLen);
tlen += taosEncodeBinary(buf, pRsp->metaRsp, pRsp->metaRspLen);
return tlen;
}
static FORCE_INLINE void* tDecodeSMqMetaRsp(const void* buf, SMqMetaRsp* pRsp) {
buf = taosDecodeFixedI64(buf, &pRsp->reqOffset);
buf = taosDecodeFixedI64(buf, &pRsp->rspOffset);
buf = taosDecodeFixedI16(buf, &pRsp->resMsgType);
buf = taosDecodeFixedI32(buf, &pRsp->metaRspLen);
buf = taosDecodeBinary(buf, &pRsp->metaRsp, pRsp->metaRspLen);
return (void*)buf;
}
int32_t tEncodeSMqMetaRsp(SEncoder* pEncoder, const SMqMetaRsp* pRsp);
int32_t tDecodeSMqMetaRsp(SDecoder* pDecoder, SMqMetaRsp* pRsp);
typedef struct {
SMqRspHead head;

13
include/libs/executor/executor.h
View File

@ -41,6 +41,9 @@ typedef struct {
bool initTableReader;
bool initTqReader;
int32_t numOfVgroups;
void* sContext; // SSnapContext*
void* pStateBackend;
} SReadHandle;
@ -181,11 +184,17 @@ int32_t qGetStreamScanStatus(qTaskInfo_t tinfo, uint64_t* uid, int64_t* ts);
int32_t qStreamPrepareTsdbScan(qTaskInfo_t tinfo, uint64_t uid, int64_t ts);
int32_t qStreamPrepareScan(qTaskInfo_t tinfo, const STqOffsetVal* pOffset);
int32_t qStreamPrepareScan(qTaskInfo_t tinfo, STqOffsetVal* pOffset, int8_t subType);
int32_t qStreamExtractOffset(qTaskInfo_t tinfo, STqOffsetVal* pOffset);
void* qStreamExtractMetaMsg(qTaskInfo_t tinfo);
SMqMetaRsp* qStreamExtractMetaMsg(qTaskInfo_t tinfo);
int64_t qStreamExtractPrepareUid(qTaskInfo_t tinfo);
const SSchemaWrapper* qExtractSchemaFromTask(qTaskInfo_t tinfo);
const char* qExtractTbnameFromTask(qTaskInfo_t tinfo);
void* qExtractReaderFromStreamScanner(void* scanner);

3
include/libs/function/function.h
View File

@ -139,9 +139,8 @@ typedef struct SqlFunctionCtx {
struct SExprInfo *pExpr;
struct SDiskbasedBuf *pBuf;
struct SSDataBlock *pSrcBlock;
struct SSDataBlock *pDstBlock; // used by indifinite rows function to set selectivity
struct SSDataBlock *pDstBlock; // used by indefinite rows function to set selectivity
int32_t curBufPage;
bool increase;
bool isStream;
char udfName[TSDB_FUNC_NAME_LEN];

5
include/libs/function/taosudf.h
View File

@ -256,8 +256,9 @@ static FORCE_INLINE int32_t udfColDataSet(SUdfColumn* pColumn, uint32_t currentR
typedef int32_t (*TUdfScalarProcFunc)(SUdfDataBlock* block, SUdfColumn *resultCol);
typedef int32_t (*TUdfAggStartFunc)(SUdfInterBuf *buf);
typedef int32_t (*TUdfAggProcessFunc)(SUdfDataBlock* block, SUdfInterBuf *interBuf, SUdfInterBuf *newInterBuf);
typedef int32_t (*TUdfAggFinishFunc)(SUdfInterBuf* buf, SUdfInterBuf *resultData);
typedef int32_t (*TUdfAggProcessFunc)(SUdfDataBlock *block, SUdfInterBuf *interBuf, SUdfInterBuf *newInterBuf);
typedef int32_t (*TUdfAggMergeFunc)(SUdfInterBuf *inputBuf1, SUdfInterBuf *inputBuf2, SUdfInterBuf *outputBuf);
typedef int32_t (*TUdfAggFinishFunc)(SUdfInterBuf *buf, SUdfInterBuf *resultData);
#ifdef __cplusplus
}

1
include/os/os.h
View File

@ -79,6 +79,7 @@ extern "C" {
#include <wchar.h>
#include <wctype.h>
#include "taoserror.h"
#include "osAtomic.h"
#include "osDef.h"
#include "osDir.h"

5
include/os/osSemaphore.h
View File

@ -23,10 +23,9 @@ extern "C" {
#include <semaphore.h>
#if defined(_TD_DARWIN_64)
#include <dispatch/dispatch.h>
// typedef struct tsem_s *tsem_t;
typedef struct bosal_sem_t *tsem_t;
typedef dispatch_semaphore_t tsem_t;
int tsem_init(tsem_t *sem, int pshared, unsigned int value);
int tsem_wait(tsem_t *sem);

10
include/util/tpagedbuf.h
View File

@ -67,10 +67,9 @@ void* getNewBufPage(SDiskbasedBuf* pBuf, int32_t groupId, int32_t* pageId);
/**
*
* @param pBuf
* @param groupId
* @return
*/
SIDList getDataBufPagesIdList(SDiskbasedBuf* pBuf, int32_t groupId);
SIDList getDataBufPagesIdList(SDiskbasedBuf* pBuf);
/**
* get the specified buffer page by id
@ -101,13 +100,6 @@ void releaseBufPageInfo(SDiskbasedBuf* pBuf, struct SPageInfo* pi);
*/
size_t getTotalBufSize(const SDiskbasedBuf* pBuf);
/**
* get the number of groups in the result buffer
* @param pBuf
* @return
*/
size_t getNumOfBufGroupId(const SDiskbasedBuf* pBuf);
/**
* destroy result buffer
* @param pBuf

200
packaging/MPtestJenkinsfile Normal file
View File

@ -0,0 +1,200 @@
def sync_source(branch_name) {
sh '''
hostname
env
echo ''' + branch_name + '''
'''
sh '''
cd ${TDINTERNAL_ROOT_DIR}
git reset --hard
git fetch || git fetch
git checkout ''' + branch_name + ''' -f
git branch
git pull || git pull
git log | head -n 20
cd ${TDENGINE_ROOT_DIR}
git reset --hard
git fetch || git fetch
git checkout ''' + branch_name + ''' -f
git branch
git pull || git pull
git log | head -n 20
git submodule update --init --recursive
'''
return 1
}
def run_test() {
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
'''
sh '''
export LD_LIBRARY_PATH=${TDINTERNAL_ROOT_DIR}/debug/build/lib
./fulltest.sh
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/tests
./test-all.sh b1fq
'''
}
def build_run() {
sync_source("${BRANCH_NAME}")
}
pipeline {
agent none
parameters {
string (
name:'version',
defaultValue:'3.0.0.1',
description: 'release version number,eg: 3.0.0.1 or 3.0.0.'
)
string (
name:'baseVersion',
defaultValue:'3.0.0.1',
description: 'This number of baseVerison is generally not modified.Now it is 3.0.0.1'
)
}
environment{
WORK_DIR = '/var/lib/jenkins/workspace'
TDINTERNAL_ROOT_DIR = '/var/lib/jenkins/workspace/TDinternal'
TDENGINE_ROOT_DIR = '/var/lib/jenkins/workspace/TDinternal/community'
BRANCH_NAME = '3.0'
TD_SERVER_TAR = "TDengine-server-${version}-Linux-x64.tar.gz"
BASE_TD_SERVER_TAR = "TDengine-server-${baseVersion}-arm64-x64.tar.gz"
TD_SERVER_ARM_TAR = "TDengine-server-${version}-Linux-arm64.tar.gz"
BASE_TD_SERVER_ARM_TAR = "TDengine-server-${baseVersion}-Linux-arm64.tar.gz"
TD_SERVER_LITE_TAR = "TDengine-server-${version}-Linux-x64-Lite.tar.gz"
BASE_TD_SERVER_LITE_TAR = "TDengine-server-${baseVersion}-Linux-x64-Lite.tar.gz"
TD_CLIENT_TAR = "TDengine-client-${version}-Linux-x64.tar.gz"
BASE_TD_CLIENT_TAR = "TDengine-client-${baseVersion}-arm64-x64.tar.gz"
TD_CLIENT_ARM_TAR = "TDengine-client-${version}-Linux-arm64.tar.gz"
BASE_TD_CLIENT_ARM_TAR = "TDengine-client-${baseVersion}-Linux-arm64.tar.gz"
TD_CLIENT_LITE_TAR = "TDengine-client-${version}-Linux-x64-Lite.tar.gz"
BASE_TD_CLIENT_LITE_TAR = "TDengine-client-${baseVersion}-Linux-x64-Lite.tar.gz"
TD_SERVER_RPM = "TDengine-server-${version}-Linux-x64.rpm"
TD_SERVER_DEB = "TDengine-server-${version}-Linux-x64.deb"
TD_SERVER_EXE = "TDengine-server-${version}-Windows-x64.exe"
TD_CLIENT_EXE = "TDengine-client-${version}-Windows-x64.exe"
}
stages {
stage ('RUN') {
stage('get check package scritps'){
agent{label 'ubuntu18'}
steps {
catchError(buildResult: 'FAILURE', stageResult: 'FAILURE') {
script{
sync_source("${BRANCH_NAME}")
}
}
}
}
parallel {
stage('ubuntu16') {
agent{label " ubuntu16 "}
steps {
timeout(time: 3, unit: 'MINUTES'){
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_TAR} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
rmtaos
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_LITE_TAR} ${version} ${BASE_TD_SERVER_LITE_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_DEB} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
}
}
}
stage('ubuntu18') {
agent{label " ubuntu18 "}
steps {
timeout(time: 3, unit: 'MINUTES'){
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_TAR} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
rmtaos
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_LITE_TAR} ${version} ${BASE_TD_SERVER_LITE_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_DEB} ${version} ${BASE_TD_SERVER_DEB} ${baseVersion} server
python3 checkPackageRuning.py
'''
}
}
}
stage('centos7') {
agent{label " centos7_9 "}
steps {
timeout(time: 240, unit: 'MINUTES'){
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_TAR} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
rmtaos
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_LITE_TAR} ${version} ${BASE_TD_SERVER_LITE_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_RPM} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
}
}
}
stage('centos8') {
agent{label " centos8_3 "}
steps {
timeout(time: 240, unit: 'MINUTES'){
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_TAR} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
rmtaos
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_LITE_TAR} ${version} ${BASE_TD_SERVER_LITE_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
sh '''
cd ${TDENGINE_ROOT_DIR}/packaging
bash testpackage.sh ${TD_SERVER_RPM} ${version} ${BASE_TD_SERVER_TAR} ${baseVersion} server
python3 checkPackageRuning.py
'''
}
}
}
}
}
}
}

2
packaging/cfg/taos.cfg
View File

@ -38,7 +38,7 @@
# The interval of dnode reporting status to mnode
# statusInterval 1
# The interval for taos shell to send heartbeat to mnode
# The interval for TDengine CLI to send heartbeat to mnode
# shellActivityTimer 3
# The minimum sliding window time, milli-second

101
packaging/checkPackageRuning.py Executable file
View File

@ -0,0 +1,101 @@
#!/usr/bin/python
###################################################################
# Copyright (c) 2016 by TAOS Technologies, Inc.
# All rights reserved.
#
# This file is proprietary and confidential to TAOS Technologies.
# No part of this file may be reproduced, stored, transmitted,
# disclosed or used in any form or by any means other than as
# expressly provided by the written permission from Jianhui Tao
#
###################################################################
# install pip
# pip install src/connector/python/
# -*- coding: utf-8 -*-
import sys , os
import getopt
import subprocess
# from this import d
import time
# install taospy
out = subprocess.getoutput("pip3 show taospy|grep Version| awk -F ':' '{print $2}' ")
print(out)
if (out == "" ):
os.system("pip install git+https://github.com/taosdata/taos-connector-python.git")
print("install taos python connector")
# start taosd prepare
os.system("rm -rf /var/lib/taos/*")
os.system("systemctl restart taosd ")
# wait a moment ,at least 5 seconds
time.sleep(5)
# prepare data by taosBenchmark
os.system("taosBenchmark -y -n 100 -t 100")
import taos
conn = taos.connect(host="localhost",
user="root",
password="taosdata",
database="test",
port=6030,
config="/etc/taos", # for windows the default value is C:\TDengine\cfg
timezone="Asia/Shanghai") # default your host's timezone
server_version = conn.server_info
print("server_version", server_version)
client_version = conn.client_info
print("client_version", client_version) # 3.0.0.0
# Execute a sql and get its result set. It's useful for SELECT statement
result: taos.TaosResult = conn.query("SELECT count(*) from test.meters")
data = result.fetch_all()
if data[0][0] !=10000:
print(" taosBenchmark work not as expected ")
sys.exit(1)
else:
print(" taosBenchmark work as expected ")
# test taosdump dump out data and dump in data
# dump out datas
os.system("taosdump --version")
os.system("mkdir -p /tmp/dumpdata")
os.system("rm -rf /tmp/dumpdata/*")
# dump data out
print("taosdump dump out data")
os.system("taosdump -o /tmp/dumpdata -D test -y ")
# drop database of test
print("drop database test")
os.system(" taos -s ' drop database test ;' ")
# dump data in
print("taosdump dump data in")
os.system("taosdump -i /tmp/dumpdata -y ")
result = conn.query("SELECT count(*) from test.meters")
data = result.fetch_all()
if data[0][0] !=10000:
print(" taosdump work not as expected ")
sys.exit(1)
else:
print(" taosdump work as expected ")
conn.close()

2
packaging/deb/DEBIAN/prerm
View File

@ -1,6 +1,6 @@
#!/bin/bash
if [ $1 -eq "abort-upgrade" ]; then
if [ "$1"x = "abort-upgrade"x ]; then
exit 0
fi

6
packaging/docker/README.md
View File

@ -47,7 +47,7 @@ taos> show databases;
Query OK, 1 row(s) in set (0.002843s)
```
Since TDengine use container hostname to establish connections, it's a bit more complex to use taos shell and native connectors(such as JDBC-JNI) with TDengine container instance. This is the recommended way to expose ports and use TDengine with docker in simple cases. If you want to use taos shell or taosc/connectors smoothly outside the `tdengine` container, see next use cases that match you need.
Since TDengine use container hostname to establish connections, it's a bit more complex to use TDengine CLI and native connectors(such as JDBC-JNI) with TDengine container instance. This is the recommended way to expose ports and use TDengine with docker in simple cases. If you want to use TDengine CLI or taosc/connectors smoothly outside the `tdengine` container, see next use cases that match you need.
### Start with host network
@ -87,7 +87,7 @@ docker run -d \
This command starts a docker container with TDengine server running and maps the container's TCP ports from 6030 to 6049 to the host's ports from 6030 to 6049 with TCP protocol and UDP ports range 6030-6039 to the host's UDP ports 6030-6039. If the host is already running TDengine server and occupying the same port(s), you need to map the container's port to a different unused port segment. (Please see TDengine 2.0 Port Description for details). In order to support TDengine clients accessing TDengine server services, both TCP and UDP ports need to be exposed by default(unless `rpcForceTcp` is set to `1`).
If you want to use taos shell or native connectors([JDBC-JNI](https://www.taosdata.com/cn/documentation/connector/java), or [driver-go](https://github.com/taosdata/driver-go)), you need to make sure the `TAOS_FQDN` is resolvable at `/etc/hosts` or with custom DNS service.
If you want to use TDengine CLI or native connectors([JDBC-JNI](https://www.taosdata.com/cn/documentation/connector/java), or [driver-go](https://github.com/taosdata/driver-go)), you need to make sure the `TAOS_FQDN` is resolvable at `/etc/hosts` or with custom DNS service.
If you set the `TAOS_FQDN` to host's hostname, it will works as using `hosts` network like previous use case. Otherwise, like in `-e TAOS_FQDN=tdengine`, you can add the hostname record `tdengine` into `/etc/hosts` (use `127.0.0.1` here in host path, if use TDengine client/application in other hosts, you should set the right ip to the host eg. `192.168.10.1`(check the real ip in host with `hostname -i` or `ip route list default`) to make the TDengine endpoint resolvable):
@ -391,7 +391,7 @@ test_td-1_1 /usr/bin/entrypoint.sh taosd Up 6030/tcp, 6031/tcp,
test_td-2_1 /usr/bin/entrypoint.sh taosd Up 6030/tcp, 6031/tcp, 6032/tcp, 6033/tcp, 6034/tcp, 6035/tcp, 6036/tcp, 6037/tcp, 6038/tcp, 6039/tcp, 6040/tcp, 6041/tcp, 6042/tcp
```
Check dnodes with taos shell:
Check dnodes with TDengine CLI:
```bash
$ docker-compose exec td-1 taos -s "show dnodes"

112
packaging/testpackage.sh Executable file
View File

@ -0,0 +1,112 @@
#!/bin/sh
# function installPkgAndCheckFile{
echo "Download package"
packgeName=$1
version=$2
originPackageName=$3
originversion=$4
testFile=$5
subFile="taos.tar.gz"
if [ ${testFile} = "server" ];then
tdPath="TDengine-server-${version}"
originTdpPath="TDengine-server-${originversion}"
installCmd="install.sh"
elif [ ${testFile} = "client" ];then
tdPath="TDengine-client-${version}"
originTdpPath="TDengine-client-${originversion}"
installCmd="install_client.sh"
elif [ ${testFile} = "tools" ];then
tdPath="taosTools-${version}"
originTdpPath="taosTools-${originversion}"
installCmd="install-taostools.sh"
fi
echo "Uninstall all components of TDeingne"
if command -v rmtaos ;then
echo "uninstall all components of TDeingne:rmtaos"
echo " "
else
echo "os doesn't include TDengine "
fi
if command -v rmtaostools ;then
echo "uninstall all components of TDeingne:rmtaostools"
echo " "
else
echo "os doesn't include rmtaostools "
fi
echo "new workroom path"
installPath="/usr/local/src/packageTest"
oriInstallPath="/usr/local/src/packageTest/3.1"
if [ ! -d ${installPath} ] ;then
mkdir -p ${installPath}
else
echo "${installPath} already exists"
fi
if [ ! -d ${oriInstallPath} ] ;then
mkdir -p ${oriInstallPath}
else
echo "${oriInstallPath} already exists"
fi
echo "decompress installPackage"
cd ${installPath}
wget https://www.taosdata.com/assets-download/3.0/${packgeName}
cd ${oriInstallPath}
wget https://www.taosdata.com/assets-download/3.0/${originPackageName}
if [[ ${packgeName} =~ "deb" ]];then
echo "dpkg ${packgeName}" && dpkg -i ${packgeName}
elif [[ ${packgeName} =~ "rpm" ]];then
echo "rpm ${packgeName}" && rpm -ivh ${packgeName}
elif [[ ${packgeName} =~ "tar" ]];then
echo "tar ${packgeName}" && tar -xvf ${packgeName}
cd ${oriInstallPath}
echo "tar -xvf ${originPackageName}" && tar -xvf ${originPackageName}
cd ${installPath}
echo "tar -xvf ${packgeName}" && tar -xvf ${packgeName}
if [ ${testFile} != "tools" ] ;then
cd ${installPath}/${tdPath} && tar vxf ${subFile}
cd ${oriInstallPath}/${originTdpPath} && tar vxf ${subFile}
fi
echo "check installPackage File"
cd ${installPath}
tree ${oriInstallPath}/${originTdpPath} > ${originPackageName}_checkfile
tree ${installPath}/${tdPath} > ${packgeName}_checkfile
diff ${packgeName}_checkfile ${originPackageName}_checkfile > ${installPath}/diffFile.log
diffNumbers=`cat ${installPath}/diffFile.log |wc -l `
if [ ${diffNumbers} != 0 ];then
echo "The number and names of files have changed from the previous installation package"
echo `cat ${installPath}/diffFile.log`
exit -1
fi
cd ${installPath}/${tdPath}
if [ ${testFile} = "server" ];then
bash ${installCmd} -e no
else
bash ${installCmd}
fi
fi
# }
# installPkgAndCheckFile

3
packaging/tools/make_install.sh
View File

@ -381,8 +381,7 @@ function install_header() {
${install_main_dir}/include ||
${csudo}cp -f ${source_dir}/include/client/taos.h ${source_dir}/include/common/taosdef.h ${source_dir}/include/util/taoserror.h ${source_dir}/include/libs/function/taosudf.h \
${install_main_2_dir}/include &&
${csudo}chmod 644 ${install_main_dir}/include/* ||:
${csudo}chmod 644 ${install_main_2_dir}/include/*
${csudo}chmod 644 ${install_main_dir}/include/* || ${csudo}chmod 644 ${install_main_2_dir}/include/*
fi
}

2
source/client/src/clientImpl.c
View File

@ -1975,7 +1975,7 @@ _OVER:
int32_t appendTbToReq(SHashObj* pHash, int32_t pos1, int32_t len1, int32_t pos2, int32_t len2, const char* str,
int32_t acctId, char* db) {
SName name;
SName name = {0};
if (len1 <= 0) {
return -1;

200
source/client/src/clientSml.c
View File

@ -85,8 +85,11 @@ typedef TSDB_SML_PROTOCOL_TYPE SMLProtocolType;
typedef enum {
SCHEMA_ACTION_NULL,
SCHEMA_ACTION_COLUMN,
SCHEMA_ACTION_TAG
SCHEMA_ACTION_CREATE_STABLE,
SCHEMA_ACTION_ADD_COLUMN,
SCHEMA_ACTION_ADD_TAG,
SCHEMA_ACTION_CHANGE_COLUMN_SIZE,
SCHEMA_ACTION_CHANGE_TAG_SIZE,
} ESchemaAction;
typedef struct {
@ -219,7 +222,7 @@ static int32_t smlBuildInvalidDataMsg(SSmlMsgBuf *pBuf, const char *msg1, const
static int32_t smlGenerateSchemaAction(SSchema *colField, SHashObj *colHash, SSmlKv *kv, bool isTag,
ESchemaAction *action, SSmlHandle *info) {
uint16_t *index = (uint16_t *)taosHashGet(colHash, kv->key, kv->keyLen);
uint16_t *index = colHash ? (uint16_t *)taosHashGet(colHash, kv->key, kv->keyLen) : NULL;
if (index) {
if (colField[*index].type != kv->type) {
uError("SML:0x%" PRIx64 " point type and db type mismatch. key: %s. point type: %d, db type: %d", info->id,
@ -232,16 +235,16 @@ static int32_t smlGenerateSchemaAction(SSchema *colField, SHashObj *colHash, SSm
(colField[*index].type == TSDB_DATA_TYPE_NCHAR &&
((colField[*index].bytes - VARSTR_HEADER_SIZE) / TSDB_NCHAR_SIZE < kv->length))) {
if (isTag) {
*action = SCHEMA_ACTION_TAG;
*action = SCHEMA_ACTION_CHANGE_TAG_SIZE;
} else {
*action = SCHEMA_ACTION_COLUMN;
*action = SCHEMA_ACTION_CHANGE_COLUMN_SIZE;
}
}
} else {
if (isTag) {
*action = SCHEMA_ACTION_TAG;
*action = SCHEMA_ACTION_ADD_TAG;
} else {
*action = SCHEMA_ACTION_COLUMN;
*action = SCHEMA_ACTION_ADD_COLUMN;
}
}
return 0;
@ -310,9 +313,31 @@ static int32_t getBytes(uint8_t type, int32_t length){
}
}
static int32_t smlBuildFieldsList(SSmlHandle *info, SSchema *schemaField, SHashObj *schemaHash, SArray *cols, SArray* results, int32_t numOfCols, bool isTag) {
for (int j = 0; j < taosArrayGetSize(cols); ++j) {
SSmlKv *kv = (SSmlKv *)taosArrayGetP(cols, j);
ESchemaAction action = SCHEMA_ACTION_NULL;
smlGenerateSchemaAction(schemaField, schemaHash, kv, isTag, &action, info);
if(action == SCHEMA_ACTION_ADD_COLUMN || action == SCHEMA_ACTION_ADD_TAG){
SField field = {0};
field.type = kv->type;
field.bytes = getBytes(kv->type, kv->length);
memcpy(field.name, kv->key, kv->keyLen);
taosArrayPush(results, &field);
}else if(action == SCHEMA_ACTION_CHANGE_COLUMN_SIZE || action == SCHEMA_ACTION_CHANGE_TAG_SIZE){
uint16_t *index = (uint16_t *)taosHashGet(schemaHash, kv->key, kv->keyLen);
uint16_t newIndex = *index;
if(isTag) newIndex -= numOfCols;
SField *field = (SField *)taosArrayGet(results, newIndex);
field->bytes = getBytes(kv->type, kv->length);
}
}
return TSDB_CODE_SUCCESS;
}
//static int32_t smlSendMetaMsg(SSmlHandle *info, SName *pName, SSmlSTableMeta *sTableData,
// int32_t colVer, int32_t tagVer, int8_t source, uint64_t suid){
static int32_t smlSendMetaMsg(SSmlHandle *info, SName *pName, SSmlSTableMeta *sTableData,
static int32_t smlSendMetaMsg(SSmlHandle *info, SName *pName, SArray* pColumns, SArray* pTags,
STableMeta *pTableMeta, ESchemaAction action){
SRequestObj* pRequest = NULL;
@ -320,6 +345,12 @@ static int32_t smlSendMetaMsg(SSmlHandle *info, SName *pName, SSmlSTableMeta *s
int32_t code = TSDB_CODE_SUCCESS;
SCmdMsgInfo pCmdMsg = {0};
// put front for free
pReq.numOfColumns = taosArrayGetSize(pColumns);
pReq.pColumns = pColumns;
pReq.numOfTags = taosArrayGetSize(pTags);
pReq.pTags = pTags;
code = buildRequest(info->taos->id, "", 0, NULL, false, &pRequest);
if (code != TSDB_CODE_SUCCESS) {
goto end;
@ -330,91 +361,41 @@ static int32_t smlSendMetaMsg(SSmlHandle *info, SName *pName, SSmlSTableMeta *s
goto end;
}
if (action == SCHEMA_ACTION_NULL){
if (action == SCHEMA_ACTION_CREATE_STABLE){
pReq.colVer = 1;
pReq.tagVer = 1;
pReq.suid = 0;
pReq.source = TD_REQ_FROM_APP;
} else if (action == SCHEMA_ACTION_TAG){
} else if (action == SCHEMA_ACTION_ADD_TAG || action == SCHEMA_ACTION_CHANGE_TAG_SIZE){
pReq.colVer = pTableMeta->sversion;
pReq.tagVer = pTableMeta->tversion + 1;
pReq.suid = pTableMeta->uid;
pReq.source = TD_REQ_FROM_TAOX;
} else if (action == SCHEMA_ACTION_COLUMN){
} else if (action == SCHEMA_ACTION_ADD_COLUMN || action == SCHEMA_ACTION_CHANGE_COLUMN_SIZE){
pReq.colVer = pTableMeta->sversion + 1;
pReq.tagVer = pTableMeta->tversion;
pReq.suid = pTableMeta->uid;
pReq.source = TD_REQ_FROM_TAOX;
}
if (pReq.numOfTags == 0){
pReq.numOfTags = 1;
SField field = {0};
field.type = TSDB_DATA_TYPE_NCHAR;
field.bytes = 1;
strcpy(field.name, tsSmlTagName);
taosArrayPush(pReq.pTags, &field);
}
pReq.commentLen = -1;
pReq.igExists = true;
tNameExtractFullName(pName, pReq.name);
if(action == SCHEMA_ACTION_NULL || action == SCHEMA_ACTION_COLUMN){
pReq.numOfColumns = taosArrayGetSize(sTableData->cols);
pReq.pColumns = taosArrayInit(pReq.numOfColumns, sizeof(SField));
for (int i = 0; i < pReq.numOfColumns; i++) {
SSmlKv *kv = (SSmlKv *)taosArrayGetP(sTableData->cols, i);
SField field = {0};
field.type = kv->type;
field.bytes = getBytes(kv->type, kv->length);
memcpy(field.name, kv->key, kv->keyLen);
taosArrayPush(pReq.pColumns, &field);
}
}else if (action == SCHEMA_ACTION_TAG){
pReq.numOfColumns = pTableMeta->tableInfo.numOfColumns;
pReq.pColumns = taosArrayInit(pReq.numOfColumns, sizeof(SField));
for (int i = 0; i < pReq.numOfColumns; i++) {
SSchema *s = &pTableMeta->schema[i];
SField field = {0};
field.type = s->type;
field.bytes = s->bytes;
strcpy(field.name, s->name);
taosArrayPush(pReq.pColumns, &field);
}
}
if(action == SCHEMA_ACTION_NULL || action == SCHEMA_ACTION_TAG){
pReq.numOfTags = taosArrayGetSize(sTableData->tags);
if (pReq.numOfTags == 0){
pReq.numOfTags = 1;
pReq.pTags = taosArrayInit(pReq.numOfTags, sizeof(SField));
SField field = {0};
field.type = TSDB_DATA_TYPE_NCHAR;
field.bytes = 1;
strcpy(field.name, tsSmlTagName);
taosArrayPush(pReq.pTags, &field);
}else{
pReq.pTags = taosArrayInit(pReq.numOfTags, sizeof(SField));
for (int i = 0; i < pReq.numOfTags; i++) {
SSmlKv *kv = (SSmlKv *)taosArrayGetP(sTableData->tags, i);
SField field = {0};
field.type = kv->type;
field.bytes = getBytes(kv->type, kv->length);
memcpy(field.name, kv->key, kv->keyLen);
taosArrayPush(pReq.pTags, &field);
}
}
}else if (action == SCHEMA_ACTION_COLUMN){
pReq.numOfTags = pTableMeta->tableInfo.numOfTags;
pReq.pTags = taosArrayInit(pReq.numOfTags, sizeof(SField));
for (int i = 0; i < pReq.numOfTags; i++) {
SSchema *s = &pTableMeta->schema[i + pTableMeta->tableInfo.numOfColumns];
SField field = {0};
field.type = s->type;
field.bytes = s->bytes;
strcpy(field.name, s->name);
taosArrayPush(pReq.pTags, &field);
}
}
pCmdMsg.epSet = getEpSet_s(&info->taos->pAppInfo->mgmtEp);
pCmdMsg.msgType = TDMT_MND_CREATE_STB;
pCmdMsg.msgLen = tSerializeSMCreateStbReq(NULL, 0, &pReq);
pCmdMsg.pMsg = taosMemoryMalloc(pCmdMsg.msgLen);
if (NULL == pCmdMsg.pMsg) {
tFreeSMCreateStbReq(&pReq);
code = TSDB_CODE_OUT_OF_MEMORY;
goto end;
}
@ -442,7 +423,10 @@ end:
}
static int32_t smlModifyDBSchemas(SSmlHandle *info) {
int32_t code = 0;
int32_t code = 0;
SHashObj *hashTmp = NULL;
STableMeta *pTableMeta = NULL;
SName pName = {TSDB_TABLE_NAME_T, info->taos->acctId, {0}, {0}};
strcpy(pName.dbname, info->pRequest->pDb);
@ -455,7 +439,6 @@ static int32_t smlModifyDBSchemas(SSmlHandle *info) {
SSmlSTableMeta **tableMetaSml = (SSmlSTableMeta **)taosHashIterate(info->superTables, NULL);
while (tableMetaSml) {
SSmlSTableMeta *sTableData = *tableMetaSml;
STableMeta *pTableMeta = NULL;
bool needCheckMeta = false; // for multi thread
size_t superTableLen = 0;
@ -466,14 +449,19 @@ static int32_t smlModifyDBSchemas(SSmlHandle *info) {
code = catalogGetSTableMeta(info->pCatalog, &conn, &pName, &pTableMeta);
if (code == TSDB_CODE_PAR_TABLE_NOT_EXIST || code == TSDB_CODE_MND_STB_NOT_EXIST) {
code = smlSendMetaMsg(info, &pName, sTableData, NULL, SCHEMA_ACTION_NULL);
SArray* pColumns = taosArrayInit(taosArrayGetSize(sTableData->cols), sizeof(SField));
SArray* pTags = taosArrayInit(taosArrayGetSize(sTableData->tags), sizeof(SField));
smlBuildFieldsList(info, NULL, NULL, sTableData->tags, pTags, 0, true);
smlBuildFieldsList(info, NULL, NULL, sTableData->cols, pColumns, 0, false);
code = smlSendMetaMsg(info, &pName, pColumns, pTags, NULL, SCHEMA_ACTION_CREATE_STABLE);
if (code != TSDB_CODE_SUCCESS) {
uError("SML:0x%" PRIx64 " smlSendMetaMsg failed. can not create %s", info->id, superTable);
goto end;
}
info->cost.numOfCreateSTables++;
} else if (code == TSDB_CODE_SUCCESS) {
SHashObj *hashTmp = taosHashInit(pTableMeta->tableInfo.numOfTags,
hashTmp = taosHashInit(pTableMeta->tableInfo.numOfTags,
taosGetDefaultHashFunction(TSDB_DATA_TYPE_BINARY), true, HASH_NO_LOCK);
for (uint16_t i = pTableMeta->tableInfo.numOfColumns;
i < pTableMeta->tableInfo.numOfColumns + pTableMeta->tableInfo.numOfTags; i++) {
@ -483,34 +471,70 @@ static int32_t smlModifyDBSchemas(SSmlHandle *info) {
ESchemaAction action = SCHEMA_ACTION_NULL;
code = smlProcessSchemaAction(info, pTableMeta->schema, hashTmp, sTableData->tags, &action, true);
if (code != TSDB_CODE_SUCCESS) {
taosHashCleanup(hashTmp);
goto end;
}
if (action == SCHEMA_ACTION_TAG){
code = smlSendMetaMsg(info, &pName, sTableData, pTableMeta, action);
if (action != SCHEMA_ACTION_NULL){
SArray* pColumns = taosArrayInit(taosArrayGetSize(sTableData->cols) + pTableMeta->tableInfo.numOfColumns, sizeof(SField));
SArray* pTags = taosArrayInit(taosArrayGetSize(sTableData->tags) + pTableMeta->tableInfo.numOfTags, sizeof(SField));
for (uint16_t i = 0; i < pTableMeta->tableInfo.numOfColumns + pTableMeta->tableInfo.numOfTags; i++) {
SField field = {0};
field.type = pTableMeta->schema[i].type;
field.bytes = pTableMeta->schema[i].bytes;
strcpy(field.name, pTableMeta->schema[i].name);
if(i < pTableMeta->tableInfo.numOfColumns){
taosArrayPush(pColumns, &field);
}else{
taosArrayPush(pTags, &field);
}
}
smlBuildFieldsList(info, pTableMeta->schema, hashTmp, sTableData->tags, pTags, pTableMeta->tableInfo.numOfColumns, true);
code = smlSendMetaMsg(info, &pName, pColumns, pTags, pTableMeta, action);
if (code != TSDB_CODE_SUCCESS) {
uError("SML:0x%" PRIx64 " smlSendMetaMsg failed. can not create %s", info->id, superTable);
goto end;
}
}
taosMemoryFreeClear(pTableMeta);
code = catalogRefreshTableMeta(info->pCatalog, &conn, &pName, -1);
if (code != TSDB_CODE_SUCCESS) {
goto end;
}
code = catalogGetSTableMeta(info->pCatalog, &conn, &pName, &pTableMeta);
if (code != TSDB_CODE_SUCCESS) {
goto end;
}
taosHashClear(hashTmp);
for (uint16_t i = 1; i < pTableMeta->tableInfo.numOfColumns; i++) {
for (uint16_t i = 0; i < pTableMeta->tableInfo.numOfColumns; i++) {
taosHashPut(hashTmp, pTableMeta->schema[i].name, strlen(pTableMeta->schema[i].name), &i, SHORT_BYTES);
}
action = SCHEMA_ACTION_NULL;
code = smlProcessSchemaAction(info, pTableMeta->schema, hashTmp, sTableData->cols, &action, false);
taosHashCleanup(hashTmp);
if (code != TSDB_CODE_SUCCESS) {
goto end;
}
if (action == SCHEMA_ACTION_COLUMN){
code = smlSendMetaMsg(info, &pName, sTableData, pTableMeta, action);
if (action != SCHEMA_ACTION_NULL){
SArray* pColumns = taosArrayInit(taosArrayGetSize(sTableData->cols) + pTableMeta->tableInfo.numOfColumns, sizeof(SField));
SArray* pTags = taosArrayInit(taosArrayGetSize(sTableData->tags) + pTableMeta->tableInfo.numOfTags, sizeof(SField));
for (uint16_t i = 0; i < pTableMeta->tableInfo.numOfColumns + pTableMeta->tableInfo.numOfTags; i++) {
SField field = {0};
field.type = pTableMeta->schema[i].type;
field.bytes = pTableMeta->schema[i].bytes;
strcpy(field.name, pTableMeta->schema[i].name);
if(i < pTableMeta->tableInfo.numOfColumns){
taosArrayPush(pColumns, &field);
}else{
taosArrayPush(pTags, &field);
}
}
smlBuildFieldsList(info, pTableMeta->schema, hashTmp, sTableData->cols, pColumns, pTableMeta->tableInfo.numOfColumns, false);
code = smlSendMetaMsg(info, &pName, pColumns, pTags, pTableMeta, action);
if (code != TSDB_CODE_SUCCESS) {
uError("SML:0x%" PRIx64 " smlSendMetaMsg failed. can not create %s", info->id, superTable);
goto end;
@ -526,7 +550,7 @@ static int32_t smlModifyDBSchemas(SSmlHandle *info) {
uError("SML:0x%" PRIx64 " load table meta error: %s", info->id, tstrerror(code));
goto end;
}
if (pTableMeta) taosMemoryFree(pTableMeta);
taosMemoryFreeClear(pTableMeta);
code = catalogGetSTableMeta(info->pCatalog, &conn, &pName, &pTableMeta);
if (code != TSDB_CODE_SUCCESS) {
@ -551,10 +575,13 @@ static int32_t smlModifyDBSchemas(SSmlHandle *info) {
sTableData->tableMeta = pTableMeta;
tableMetaSml = (SSmlSTableMeta **)taosHashIterate(info->superTables, tableMetaSml);
taosHashCleanup(hashTmp);
}
return 0;
end:
taosHashCleanup(hashTmp);
taosMemoryFreeClear(pTableMeta);
catalogRefreshTableMeta(info->pCatalog, &conn, &pName, 1);
return code;
}
@ -2057,10 +2084,6 @@ static int32_t smlParseInfluxLine(SSmlHandle *info, const char *sql) {
if (info->dataFormat) taosArrayDestroy(cols);
return ret;
}
if (taosArrayGetSize(cols) > TSDB_MAX_COLUMNS) {
smlBuildInvalidDataMsg(&info->msgBuf, "too many columns than 4096", NULL);
return TSDB_CODE_PAR_TOO_MANY_COLUMNS;
}
bool hasTable = true;
SSmlTableInfo *tinfo = NULL;
@ -2094,6 +2117,11 @@ static int32_t smlParseInfluxLine(SSmlHandle *info, const char *sql) {
return TSDB_CODE_PAR_INVALID_TAGS_NUM;
}
if (taosArrayGetSize(cols) + taosArrayGetSize((*oneTable)->tags) > TSDB_MAX_COLUMNS) {
smlBuildInvalidDataMsg(&info->msgBuf, "too many columns than 4096", NULL);
return TSDB_CODE_PAR_TOO_MANY_COLUMNS;
}
(*oneTable)->sTableName = elements.measure;
(*oneTable)->sTableNameLen = elements.measureLen;
if (strlen((*oneTable)->childTableName) == 0) {

126
source/client/src/taosx.c
View File

@ -765,6 +765,29 @@ static int32_t taosCreateTable(TAOS* taos, void* meta, int32_t metaLen) {
}
taosArrayPush(pRequest->tableList, &pName);
// change tag cid to new cid
if(pCreateReq->type == TSDB_CHILD_TABLE){
STableMeta* pTableMeta = NULL;
SName sName = {0};
toName(pTscObj->acctId, pRequest->pDb, pCreateReq->ctb.name, &sName);
code = catalogGetTableMeta(pCatalog, &conn, &sName, &pTableMeta);
if(code != TSDB_CODE_SUCCESS){
uError("taosCreateTable:catalogGetTableMeta failed. table name: %s", pCreateReq->ctb.name);
goto end;
}
for(int32_t i = 0; i < taosArrayGetSize(pCreateReq->ctb.tagName); i++){
char* tName = taosArrayGet(pCreateReq->ctb.tagName, i);
for(int32_t j = pTableMeta->tableInfo.numOfColumns; j < pTableMeta->tableInfo.numOfColumns + pTableMeta->tableInfo.numOfTags; j++){
SSchema *tag = &pTableMeta->schema[j];
if(strcmp(tag->name, tName) == 0 && tag->type != TSDB_DATA_TYPE_JSON){
tTagSetCid((STag *)pCreateReq->ctb.pTag, i, tag->colId);
}
}
}
taosMemoryFreeClear(pTableMeta);
}
SVgroupCreateTableBatch* pTableBatch = taosHashGet(pVgroupHashmap, &pInfo.vgId, sizeof(pInfo.vgId));
if (pTableBatch == NULL) {
SVgroupCreateTableBatch tBatch = {0};
@ -1305,6 +1328,7 @@ static int32_t tmqWriteRaw(TAOS* taos, void* data, int32_t dataLen) {
SQuery* pQuery = NULL;
SMqRspObj rspObj = {0};
SDecoder decoder = {0};
STableMeta* pTableMeta = NULL;
terrno = TSDB_CODE_SUCCESS;
SRequestObj* pRequest = (SRequestObj*)createRequest(*(int64_t*)taos, TSDB_SQL_INSERT);
@ -1361,24 +1385,6 @@ static int32_t tmqWriteRaw(TAOS* taos, void* data, int32_t dataLen) {
goto end;
}
uint16_t fLen = 0;
int32_t rowSize = 0;
int16_t nVar = 0;
for (int i = 0; i < pSW->nCols; i++) {
SSchema* schema = pSW->pSchema + i;
fLen += TYPE_BYTES[schema->type];
rowSize += schema->bytes;
if (IS_VAR_DATA_TYPE(schema->type)) {
nVar++;
}
}
int32_t rows = rspObj.resInfo.numOfRows;
int32_t extendedRowSize = rowSize + TD_ROW_HEAD_LEN - sizeof(TSKEY) + nVar * sizeof(VarDataOffsetT) +
(int32_t)TD_BITMAP_BYTES(pSW->nCols - 1);
int32_t schemaLen = 0;
int32_t submitLen = sizeof(SSubmitBlk) + schemaLen + rows * extendedRowSize;
const char* tbName = (const char*)taosArrayGetP(rspObj.rsp.blockTbName, rspObj.resIter);
if (!tbName) {
uError("WriteRaw: tbname is null");
@ -1398,6 +1404,35 @@ static int32_t tmqWriteRaw(TAOS* taos, void* data, int32_t dataLen) {
goto end;
}
code = catalogGetTableMeta(pCatalog, &conn, &pName, &pTableMeta);
if (code == TSDB_CODE_PAR_TABLE_NOT_EXIST){
uError("WriteRaw:catalogGetTableMeta table not exist. table name: %s", tbName);
code = TSDB_CODE_SUCCESS;
continue;
}
if (code != TSDB_CODE_SUCCESS) {
uError("WriteRaw:catalogGetTableMeta failed. table name: %s", tbName);
goto end;
}
uint16_t fLen = 0;
int32_t rowSize = 0;
int16_t nVar = 0;
for (int i = 0; i < pTableMeta->tableInfo.numOfColumns; i++) {
SSchema* schema = &pTableMeta->schema[i];
fLen += TYPE_BYTES[schema->type];
rowSize += schema->bytes;
if (IS_VAR_DATA_TYPE(schema->type)) {
nVar++;
}
}
int32_t rows = rspObj.resInfo.numOfRows;
int32_t extendedRowSize = rowSize + TD_ROW_HEAD_LEN - sizeof(TSKEY) + nVar * sizeof(VarDataOffsetT) +
(int32_t)TD_BITMAP_BYTES(pTableMeta->tableInfo.numOfColumns - 1);
int32_t schemaLen = 0;
int32_t submitLen = sizeof(SSubmitBlk) + schemaLen + rows * extendedRowSize;
SSubmitReq* subReq = NULL;
SSubmitBlk* blk = NULL;
void* hData = taosHashGet(pVgHash, &vgData.vg.vgId, sizeof(vgData.vg.vgId));
@ -1430,23 +1465,25 @@ static int32_t tmqWriteRaw(TAOS* taos, void* data, int32_t dataLen) {
blk = POINTER_SHIFT(vgData.data, sizeof(SSubmitReq));
}
STableMeta* pTableMeta = NULL;
code = catalogGetTableMeta(pCatalog, &conn, &pName, &pTableMeta);
if (code != TSDB_CODE_SUCCESS) {
uError("WriteRaw:catalogGetTableMeta failed. table name: %s", tbName);
goto end;
}
// pSW->pSchema should be same as pTableMeta->schema
// ASSERT(pSW->nCols == pTableMeta->tableInfo.numOfColumns);
uint64_t suid = (TSDB_NORMAL_TABLE == pTableMeta->tableType ? 0 : pTableMeta->suid);
uint64_t uid = pTableMeta->uid;
taosMemoryFreeClear(pTableMeta);
int16_t sver = pTableMeta->sversion;
void* blkSchema = POINTER_SHIFT(blk, sizeof(SSubmitBlk));
STSRow* rowData = POINTER_SHIFT(blkSchema, schemaLen);
SRowBuilder rb = {0};
tdSRowInit(&rb, pSW->version);
tdSRowSetTpInfo(&rb, pSW->nCols, fLen);
int32_t dataLen = 0;
tdSRowInit(&rb, sver);
tdSRowSetTpInfo(&rb, pTableMeta->tableInfo.numOfColumns, fLen);
int32_t totalLen = 0;
SHashObj* schemaHash = taosHashInit(16, taosGetDefaultHashFunction(TSDB_DATA_TYPE_BINARY), false, HASH_NO_LOCK);
for (int i = 0; i < pSW->nCols; i++) {
SSchema* schema = &pSW->pSchema[i];
taosHashPut(schemaHash, schema->name, strlen(schema->name), &i, sizeof(int32_t));
}
for (int32_t j = 0; j < rows; j++) {
tdSRowResetBuf(&rb, rowData);
@ -1455,33 +1492,41 @@ static int32_t tmqWriteRaw(TAOS* taos, void* data, int32_t dataLen) {
rspObj.resInfo.current += 1;
int32_t offset = 0;
for (int32_t k = 0; k < pSW->nCols; k++) {
const SSchema* pColumn = &pSW->pSchema[k];
char* data = rspObj.resInfo.row[k];
if (!data) {
for (int32_t k = 0; k < pTableMeta->tableInfo.numOfColumns; k++) {
const SSchema* pColumn = &pTableMeta->schema[k];
int32_t* index = taosHashGet(schemaHash, pColumn->name, strlen(pColumn->name));
if(!index){
tdAppendColValToRow(&rb, pColumn->colId, pColumn->type, TD_VTYPE_NULL, NULL, false, offset, k);
} else {
if (IS_VAR_DATA_TYPE(pColumn->type)) {
data -= VARSTR_HEADER_SIZE;
}else{
char* colData = rspObj.resInfo.row[*index];
if (!colData) {
tdAppendColValToRow(&rb, pColumn->colId, pColumn->type, TD_VTYPE_NULL, NULL, false, offset, k);
} else {
if (IS_VAR_DATA_TYPE(pColumn->type)) {
colData -= VARSTR_HEADER_SIZE;
}
tdAppendColValToRow(&rb, pColumn->colId, pColumn->type, TD_VTYPE_NORM, colData, true, offset, k);
}
tdAppendColValToRow(&rb, pColumn->colId, pColumn->type, TD_VTYPE_NORM, data, true, offset, k);
}
offset += TYPE_BYTES[pColumn->type];
}
tdSRowEnd(&rb);
int32_t rowLen = TD_ROW_LEN(rowData);
rowData = POINTER_SHIFT(rowData, rowLen);
dataLen += rowLen;
totalLen += rowLen;
}
taosHashCleanup(schemaHash);
blk->uid = htobe64(uid);
blk->suid = htobe64(suid);
blk->sversion = htonl(pSW->version);
blk->sversion = htonl(sver);
blk->schemaLen = htonl(schemaLen);
blk->numOfRows = htonl(rows);
blk->dataLen = htonl(dataLen);
subReq->length += sizeof(SSubmitBlk) + schemaLen + dataLen;
blk->dataLen = htonl(totalLen);
subReq->length += sizeof(SSubmitBlk) + schemaLen + totalLen;
subReq->numOfBlocks++;
taosMemoryFreeClear(pTableMeta);
}
pQuery = (SQuery*)nodesMakeNode(QUERY_NODE_QUERY);
@ -1535,6 +1580,7 @@ end:
qDestroyQuery(pQuery);
destroyRequest(pRequest);
taosHashCleanup(pVgHash);
taosMemoryFreeClear(pTableMeta);
return code;
}

8
source/client/src/tmq.c
View File

@ -1132,7 +1132,10 @@ int32_t tmqPollCb(void* param, SDataBuf* pMsg, int32_t code) {
memcpy(&pRspWrapper->dataRsp, pMsg->pData, sizeof(SMqRspHead));
} else {
ASSERT(rspType == TMQ_MSG_TYPE__POLL_META_RSP);
tDecodeSMqMetaRsp(POINTER_SHIFT(pMsg->pData, sizeof(SMqRspHead)), &pRspWrapper->metaRsp);
SDecoder decoder;
tDecoderInit(&decoder, POINTER_SHIFT(pMsg->pData, sizeof(SMqRspHead)), pMsg->len - sizeof(SMqRspHead));
tDecodeSMqMetaRsp(&decoder, &pRspWrapper->metaRsp);
tDecoderClear(&decoder);
memcpy(&pRspWrapper->metaRsp, pMsg->pData, sizeof(SMqRspHead));
}
@ -1581,8 +1584,7 @@ void* tmqHandleAllRsp(tmq_t* tmq, int64_t timeout, bool pollIfReset) {
SMqClientVg* pVg = pollRspWrapper->vgHandle;
/*printf("vgId:%d, offset %" PRId64 " up to %" PRId64 "\n", pVg->vgId, pVg->currentOffset,
* rspMsg->msg.rspOffset);*/
pVg->currentOffset.version = pollRspWrapper->metaRsp.rspOffset;
pVg->currentOffset.type = TMQ_OFFSET__LOG;
pVg->currentOffset = pollRspWrapper->metaRsp.rspOffset;
atomic_store_32(&pVg->vgStatus, TMQ_VG_STATUS__IDLE);
// build rsp
SMqMetaRspObj* pRsp = tmqBuildMetaRspFromWrapper(pollRspWrapper);

49
source/client/test/smlTest.cpp
View File

@ -692,3 +692,52 @@ TEST(testCase, smlParseTelnetLine_diff_json_type2_Test) {
ASSERT_NE(ret, 0);
smlDestroyInfo(info);
}
TEST(testCase, sml_col_4096_Test) {
SSmlHandle *info = smlBuildSmlInfo(NULL, NULL, TSDB_SML_LINE_PROTOCOL, TSDB_SML_TIMESTAMP_NANO_SECONDS);
ASSERT_NE(info, nullptr);
const char *sql[] = {
"spgwgvldxv,id=spgwgvldxv_1,t0=f c0=t,c1=t,c2=t,c3=t,c4=t,c5=t,c6=t,c7=t,c8=t,c9=t,c10=t,c11=t,c12=t,c13=t,c14=t,c15=t,c16=t,c17=t,c18=t,c19=t,c20=t,c21=t,c22=t,c23=t,c24=t,c25=t,c26=t,c27=t,c28=t,c29=t,c30=t,c31=t,c32=t,c33=t,c34=t,c35=t,c36=t,c37=t,c38=t,c39=t,c40=t,c41=t,c42=t,c43=t,c44=t,c45=t,c46=t,c47=t,c48=t,c49=t,c50=t,c51=t,c52=t,c53=t,c54=t,c55=t,c56=t,c57=t,c58=t,c59=t,c60=t,c61=t,c62=t,c63=t,c64=t,c65=t,c66=t,c67=t,c68=t,c69=t,c70=t,c71=t,c72=t,c73=t,c74=t,c75=t,c76=t,c77=t,c78=t,c79=t,c80=t,c81=t,c82=t,c83=t,c84=t,c85=t,c86=t,c87=t,c88=t,c89=t,c90=t,c91=t,c92=t,c93=t,c94=t,c95=t,c96=t,c97=t,c98=t,c99=t,c100=t,"
"c101=t,c102=t,c103=t,c104=t,c105=t,c106=t,c107=t,c108=t,c109=t,c110=t,c111=t,c112=t,c113=t,c114=t,c115=t,c116=t,c117=t,c118=t,c119=t,c120=t,c121=t,c122=t,c123=t,c124=t,c125=t,c126=t,c127=t,c128=t,c129=t,c130=t,c131=t,c132=t,c133=t,c134=t,c135=t,c136=t,c137=t,c138=t,c139=t,c140=t,c141=t,c142=t,c143=t,c144=t,c145=t,c146=t,c147=t,c148=t,c149=t,c150=t,c151=t,c152=t,c153=t,c154=t,c155=t,c156=t,c157=t,c158=t,c159=t,c160=t,c161=t,c162=t,c163=t,c164=t,c165=t,c166=t,c167=t,c168=t,c169=t,c170=t,c171=t,c172=t,c173=t,c174=t,c175=t,c176=t,c177=t,c178=t,c179=t,c180=t,c181=t,c182=t,c183=t,c184=t,c185=t,c186=t,c187=t,c188=t,c189=t,"
"c190=t,c191=t,c192=t,c193=t,c194=t,c195=t,c196=t,c197=t,c198=t,c199=t,c200=t,c201=t,c202=t,c203=t,c204=t,c205=t,c206=t,c207=t,c208=t,c209=t,c210=t,c211=t,c212=t,c213=t,c214=t,c215=t,c216=t,c217=t,c218=t,c219=t,c220=t,c221=t,c222=t,c223=t,c224=t,c225=t,c226=t,c227=t,c228=t,c229=t,c230=t,c231=t,c232=t,c233=t,c234=t,c235=t,c236=t,c237=t,c238=t,c239=t,c240=t,c241=t,c242=t,c243=t,c244=t,c245=t,c246=t,c247=t,c248=t,c249=t,c250=t,c251=t,c252=t,c253=t,c254=t,c255=t,c256=t,c257=t,c258=t,c259=t,c260=t,c261=t,c262=t,c263=t,c264=t,c265=t,c266=t,c267=t,c268=t,c269=t,c270=t,c271=t,c272=t,c273=t,c274=t,c275=t,c276=t,c277=t,c278=t,"
"c279=t,c280=t,c281=t,c282=t,c283=t,c284=t,c285=t,c286=t,c287=t,c288=t,c289=t,c290=t,c291=t,c292=t,c293=t,c294=t,c295=t,c296=t,c297=t,c298=t,c299=t,c300=t,c301=t,c302=t,c303=t,c304=t,c305=t,c306=t,c307=t,c308=t,c309=t,c310=t,c311=t,c312=t,c313=t,c314=t,c315=t,c316=t,c317=t,c318=t,c319=t,c320=t,c321=t,c322=t,c323=t,c324=t,c325=t,c326=t,c327=t,c328=t,c329=t,c330=t,c331=t,c332=t,c333=t,c334=t,c335=t,c336=t,c337=t,c338=t,c339=t,c340=t,c341=t,c342=t,c343=t,c344=t,c345=t,c346=t,c347=t,c348=t,c349=t,c350=t,c351=t,c352=t,c353=t,c354=t,c355=t,c356=t,c357=t,c358=t,c359=t,c360=t,c361=t,c362=t,c363=t,c364=t,c365=t,c366=t,c367=t,c368=t,c369=t,c370=t,c371=t,c372=t,c373=t,c374=t,c375=t,c376=t,c377=t,c378=t,c379=t,c380=t,c381=t,c382=t,c383=t,c384=t,c385=t,c386=t,c387=t,c388=t,c389=t,c390=t,c391=t,c392=t,c393=t,c394=t,c395=t,c396=t,c397=t,c398=t,c399=t,c400=t,c401=t,c402=t,c403=t,c404=t,c405=t,c406=t,c407=t,c408=t,c409=t,c410=t,c411=t,c412=t,c413=t,c414=t,c415=t,c416=t,c417=t,c418=t,c419=t,c420=t,c421=t,c422=t,c423=t,c424=t,c425=t,c426=t,c427=t,c428=t,c429=t,c430=t,c431=t,c432=t,c433=t,c434=t,c435=t,c436=t,c437=t,c438=t,c439=t,c440=t,c441=t,c442=t,c443=t,c444=t,c445=t,c446=t,"
"c447=t,c448=t,c449=t,c450=t,c451=t,c452=t,c453=t,c454=t,c455=t,c456=t,c457=t,c458=t,c459=t,c460=t,c461=t,c462=t,c463=t,c464=t,c465=t,c466=t,c467=t,c468=t,c469=t,c470=t,c471=t,c472=t,c473=t,c474=t,c475=t,c476=t,c477=t,c478=t,c479=t,c480=t,c481=t,c482=t,c483=t,c484=t,c485=t,c486=t,c487=t,c488=t,c489=t,c490=t,c491=t,c492=t,c493=t,c494=t,c495=t,c496=t,c497=t,c498=t,c499=t,c500=t,c501=t,c502=t,c503=t,c504=t,c505=t,c506=t,c507=t,c508=t,c509=t,c510=t,c511=t,c512=t,c513=t,c514=t,c515=t,c516=t,c517=t,c518=t,c519=t,c520=t,c521=t,c522=t,c523=t,c524=t,c525=t,c526=t,c527=t,c528=t,c529=t,c530=t,c531=t,c532=t,c533=t,c534=t,c535=t,c536=t,c537=t,c538=t,c539=t,c540=t,c541=t,c542=t,c543=t,c544=t,c545=t,c546=t,c547=t,c548=t,c549=t,c550=t,c551=t,c552=t,c553=t,c554=t,c555=t,c556=t,c557=t,c558=t,c559=t,c560=t,c561=t,c562=t,c563=t,c564=t,c565=t,c566=t,c567=t,c568=t,c569=t,c570=t,c571=t,c572=t,c573=t,c574=t,c575=t,c576=t,c577=t,c578=t,c579=t,c580=t,c581=t,c582=t,c583=t,c584=t,c585=t,c586=t,c587=t,c588=t,c589=t,c590=t,c591=t,c592=t,c593=t,c594=t,c595=t,c596=t,c597=t,c598=t,c599=t,c600=t,c601=t,c602=t,c603=t,c604=t,c605=t,c606=t,c607=t,c608=t,c609=t,c610=t,c611=t,c612=t,c613=t,c614=t,"
"c615=t,c616=t,c617=t,c618=t,c619=t,c620=t,c621=t,c622=t,c623=t,c624=t,c625=t,c626=t,c627=t,c628=t,c629=t,c630=t,c631=t,c632=t,c633=t,c634=t,c635=t,c636=t,c637=t,c638=t,c639=t,c640=t,c641=t,c642=t,c643=t,c644=t,c645=t,c646=t,c647=t,c648=t,c649=t,c650=t,c651=t,c652=t,c653=t,c654=t,c655=t,c656=t,c657=t,c658=t,c659=t,c660=t,c661=t,c662=t,c663=t,c664=t,c665=t,c666=t,c667=t,c668=t,c669=t,c670=t,c671=t,c672=t,c673=t,c674=t,c675=t,c676=t,c677=t,c678=t,c679=t,c680=t,c681=t,c682=t,c683=t,c684=t,c685=t,c686=t,c687=t,c688=t,c689=t,c690=t,c691=t,c692=t,c693=t,c694=t,c695=t,c696=t,c697=t,c698=t,c699=t,c700=t,c701=t,c702=t,c703=t,c704=t,c705=t,c706=t,c707=t,c708=t,c709=t,c710=t,c711=t,c712=t,c713=t,c714=t,c715=t,c716=t,c717=t,c718=t,c719=t,c720=t,c721=t,c722=t,c723=t,c724=t,c725=t,c726=t,c727=t,c728=t,c729=t,c730=t,c731=t,c732=t,c733=t,c734=t,c735=t,c736=t,c737=t,c738=t,c739=t,c740=t,c741=t,c742=t,c743=t,c744=t,c745=t,c746=t,c747=t,c748=t,c749=t,c750=t,c751=t,c752=t,c753=t,c754=t,c755=t,c756=t,c757=t,c758=t,c759=t,c760=t,c761=t,c762=t,c763=t,c764=t,c765=t,c766=t,c767=t,c768=t,c769=t,c770=t,c771=t,c772=t,c773=t,c774=t,c775=t,c776=t,c777=t,c778=t,c779=t,c780=t,c781=t,c782=t,"
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"c2872=t,c2873=t,c2874=t,c2875=t,c2876=t,c2877=t,c2878=t,c2879=t,c2880=t,c2881=t,c2882=t,c2883=t,c2884=t,c2885=t,c2886=t,c2887=t,c2888=t,c2889=t,c2890=t,c2891=t,c2892=t,c2893=t,c2894=t,c2895=t,c2896=t,c2897=t,c2898=t,c2899=t,c2900=t,c2901=t,c2902=t,c2903=t,c2904=t,c2905=t,c2906=t,c2907=t,c2908=t,c2909=t,c2910=t,c2911=t,c2912=t,c2913=t,c2914=t,c2915=t,c2916=t,c2917=t,c2918=t,c2919=t,c2920=t,c2921=t,c2922=t,c2923=t,c2924=t,c2925=t,c2926=t,c2927=t,c2928=t,c2929=t,c2930=t,c2931=t,c2932=t,c2933=t,c2934=t,c2935=t,c2936=t,c2937=t,c2938=t,c2939=t,c2940=t,c2941=t,c2942=t,c2943=t,c2944=t,c2945=t,c2946=t,c2947=t,c2948=t,c2949=t,c2950=t,c2951=t,c2952=t,c2953=t,c2954=t,c2955=t,c2956=t,c2957=t,c2958=t,c2959=t,c2960=t,c2961=t,c2962=t,c2963=t,c2964=t,c2965=t,c2966=t,c2967=t,c2968=t,c2969=t,c2970=t,c2971=t,c2972=t,c2973=t,c2974=t,c2975=t,c2976=t,c2977=t,c2978=t,c2979=t,c2980=t,c2981=t,c2982=t,c2983=t,c2984=t,c2985=t,c2986=t,c2987=t,c2988=t,c2989=t,c2990=t,c2991=t,c2992=t,c2993=t,c2994=t,c2995=t,c2996=t,c2997=t,c2998=t,c2999=t,c3000=t,c3001=t,c3002=t,c3003=t,c3004=t,c3005=t,c3006=t,c3007=t,c3008=t,c3009=t,c3010=t,c3011=t,c3012=t,c3013=t,c3014=t,c3015=t,c3016=t,c3017=t,c3018=t,"
"c3019=t,c3020=t,c3021=t,c3022=t,c3023=t,c3024=t,c3025=t,c3026=t,c3027=t,c3028=t,c3029=t,c3030=t,c3031=t,c3032=t,c3033=t,c3034=t,c3035=t,c3036=t,c3037=t,c3038=t,c3039=t,c3040=t,c3041=t,c3042=t,c3043=t,c3044=t,c3045=t,c3046=t,c3047=t,c3048=t,c3049=t,c3050=t,c3051=t,c3052=t,c3053=t,c3054=t,c3055=t,c3056=t,c3057=t,c3058=t,c3059=t,c3060=t,c3061=t,c3062=t,c3063=t,c3064=t,c3065=t,c3066=t,c3067=t,c3068=t,c3069=t,c3070=t,c3071=t,c3072=t,c3073=t,c3074=t,c3075=t,c3076=t,c3077=t,c3078=t,c3079=t,c3080=t,c3081=t,c3082=t,c3083=t,c3084=t,c3085=t,c3086=t,c3087=t,c3088=t,c3089=t,c3090=t,c3091=t,c3092=t,c3093=t,c3094=t,c3095=t,c3096=t,c3097=t,c3098=t,c3099=t,c3100=t,c3101=t,c3102=t,c3103=t,c3104=t,c3105=t,c3106=t,c3107=t,c3108=t,c3109=t,c3110=t,c3111=t,c3112=t,c3113=t,c3114=t,c3115=t,c3116=t,c3117=t,c3118=t,c3119=t,c3120=t,c3121=t,c3122=t,c3123=t,c3124=t,c3125=t,c3126=t,c3127=t,c3128=t,c3129=t,c3130=t,c3131=t,c3132=t,c3133=t,c3134=t,c3135=t,c3136=t,c3137=t,c3138=t,c3139=t,c3140=t,c3141=t,c3142=t,c3143=t,c3144=t,c3145=t,c3146=t,c3147=t,c3148=t,c3149=t,c3150=t,c3151=t,c3152=t,c3153=t,c3154=t,c3155=t,c3156=t,c3157=t,c3158=t,c3159=t,c3160=t,c3161=t,c3162=t,c3163=t,c3164=t,c3165=t,"
"c3166=t,c3167=t,c3168=t,c3169=t,c3170=t,c3171=t,c3172=t,c3173=t,c3174=t,c3175=t,c3176=t,c3177=t,c3178=t,c3179=t,c3180=t,c3181=t,c3182=t,c3183=t,c3184=t,c3185=t,c3186=t,c3187=t,c3188=t,c3189=t,c3190=t,c3191=t,c3192=t,c3193=t,c3194=t,c3195=t,c3196=t,c3197=t,c3198=t,c3199=t,c3200=t,c3201=t,c3202=t,c3203=t,c3204=t,c3205=t,c3206=t,c3207=t,c3208=t,c3209=t,c3210=t,c3211=t,c3212=t,c3213=t,c3214=t,c3215=t,c3216=t,c3217=t,c3218=t,c3219=t,c3220=t,c3221=t,c3222=t,c3223=t,c3224=t,c3225=t,c3226=t,c3227=t,c3228=t,c3229=t,c3230=t,c3231=t,c3232=t,c3233=t,c3234=t,c3235=t,c3236=t,c3237=t,c3238=t,c3239=t,c3240=t,c3241=t,c3242=t,c3243=t,c3244=t,c3245=t,c3246=t,c3247=t,c3248=t,c3249=t,c3250=t,c3251=t,c3252=t,c3253=t,c3254=t,c3255=t,c3256=t,c3257=t,c3258=t,c3259=t,c3260=t,c3261=t,c3262=t,c3263=t,c3264=t,c3265=t,c3266=t,c3267=t,c3268=t,c3269=t,c3270=t,c3271=t,c3272=t,c3273=t,c3274=t,c3275=t,c3276=t,c3277=t,c3278=t,c3279=t,c3280=t,c3281=t,c3282=t,c3283=t,c3284=t,c3285=t,c3286=t,c3287=t,c3288=t,c3289=t,c3290=t,c3291=t,c3292=t,c3293=t,c3294=t,c3295=t,c3296=t,c3297=t,c3298=t,c3299=t,c3300=t,c3301=t,c3302=t,c3303=t,c3304=t,c3305=t,c3306=t,c3307=t,c3308=t,c3309=t,c3310=t,c3311=t,c3312=t,"
"c3313=t,c3314=t,c3315=t,c3316=t,c3317=t,c3318=t,c3319=t,c3320=t,c3321=t,c3322=t,c3323=t,c3324=t,c3325=t,c3326=t,c3327=t,c3328=t,c3329=t,c3330=t,c3331=t,c3332=t,c3333=t,c3334=t,c3335=t,c3336=t,c3337=t,c3338=t,c3339=t,c3340=t,c3341=t,c3342=t,c3343=t,c3344=t,c3345=t,c3346=t,c3347=t,c3348=t,c3349=t,c3350=t,c3351=t,c3352=t,c3353=t,c3354=t,c3355=t,c3356=t,c3357=t,c3358=t,c3359=t,c3360=t,c3361=t,c3362=t,c3363=t,c3364=t,c3365=t,c3366=t,c3367=t,c3368=t,c3369=t,c3370=t,c3371=t,c3372=t,c3373=t,c3374=t,c3375=t,c3376=t,c3377=t,c3378=t,c3379=t,c3380=t,c3381=t,c3382=t,c3383=t,c3384=t,c3385=t,c3386=t,c3387=t,c3388=t,c3389=t,c3390=t,c3391=t,c3392=t,c3393=t,c3394=t,c3395=t,c3396=t,c3397=t,c3398=t,c3399=t,c3400=t,c3401=t,c3402=t,c3403=t,c3404=t,c3405=t,c3406=t,c3407=t,c3408=t,c3409=t,c3410=t,c3411=t,c3412=t,c3413=t,c3414=t,c3415=t,c3416=t,c3417=t,c3418=t,c3419=t,c3420=t,c3421=t,c3422=t,c3423=t,c3424=t,c3425=t,c3426=t,c3427=t,c3428=t,c3429=t,c3430=t,c3431=t,c3432=t,c3433=t,c3434=t,c3435=t,c3436=t,c3437=t,c3438=t,c3439=t,c3440=t,c3441=t,c3442=t,c3443=t,c3444=t,c3445=t,c3446=t,c3447=t,c3448=t,c3449=t,c3450=t,c3451=t,c3452=t,c3453=t,c3454=t,c3455=t,c3456=t,c3457=t,c3458=t,c3459=t,"
"c3460=t,c3461=t,c3462=t,c3463=t,c3464=t,c3465=t,c3466=t,c3467=t,c3468=t,c3469=t,c3470=t,c3471=t,c3472=t,c3473=t,c3474=t,c3475=t,c3476=t,c3477=t,c3478=t,c3479=t,c3480=t,c3481=t,c3482=t,c3483=t,c3484=t,c3485=t,c3486=t,c3487=t,c3488=t,c3489=t,c3490=t,c3491=t,c3492=t,c3493=t,c3494=t,c3495=t,c3496=t,c3497=t,c3498=t,c3499=t,c3500=t,c3501=t,c3502=t,c3503=t,c3504=t,c3505=t,c3506=t,c3507=t,c3508=t,c3509=t,c3510=t,c3511=t,c3512=t,c3513=t,"
"c3514=t,c3515=t,c3516=t,c3517=t,c3518=t,c3519=t,c3520=t,c3521=t,c3522=t,c3523=t,c3524=t,c3525=t,c3526=t,c3527=t,c3528=t,c3529=t,c3530=t,c3531=t,c3532=t,c3533=t,c3534=t,c3535=t,c3536=t,c3537=t,c3538=t,c3539=t,c3540=t,c3541=t,c3542=t,c3543=t,c3544=t,c3545=t,c3546=t,c3547=t,c3548=t,c3549=t,c3550=t,c3551=t,c3552=t,c3553=t,c3554=t,c3555=t,c3556=t,c3557=t,c3558=t,c3559=t,c3560=t,c3561=t,c3562=t,c3563=t,c3564=t,c3565=t,c3566=t,c3567=t,c3568=t,c3569=t,c3570=t,c3571=t,c3572=t,c3573=t,c3574=t,c3575=t,c3576=t,c3577=t,c3578=t,c3579=t,c3580=t,c3581=t,c3582=t,c3583=t,c3584=t,c3585=t,c3586=t,c3587=t,c3588=t,c3589=t,c3590=t,c3591=t,c3592=t,c3593=t,c3594=t,c3595=t,c3596=t,c3597=t,c3598=t,c3599=t,c3600=t,c3601=t,c3602=t,c3603=t,c3604=t,c3605=t,c3606=t,c3607=t,c3608=t,c3609=t,c3610=t,c3611=t,c3612=t,c3613=t,c3614=t,c3615=t,c3616=t,c3617=t,c3618=t,c3619=t,c3620=t,c3621=t,c3622=t,c3623=t,c3624=t,c3625=t,c3626=t,c3627=t,c3628=t,c3629=t,c3630=t,c3631=t,c3632=t,c3633=t,c3634=t,c3635=t,c3636=t,c3637=t,c3638=t,c3639=t,c3640=t,c3641=t,c3642=t,c3643=t,c3644=t,c3645=t,c3646=t,c3647=t,c3648=t,c3649=t,c3650=t,c3651=t,c3652=t,c3653=t,c3654=t,c3655=t,c3656=t,c3657=t,c3658=t,c3659=t,c3660=t,"
"c3661=t,c3662=t,c3663=t,c3664=t,c3665=t,c3666=t,c3667=t,c3668=t,c3669=t,c3670=t,c3671=t,c3672=t,c3673=t,c3674=t,c3675=t,c3676=t,c3677=t,c3678=t,c3679=t,c3680=t,c3681=t,c3682=t,c3683=t,c3684=t,c3685=t,c3686=t,c3687=t,c3688=t,c3689=t,c3690=t,c3691=t,c3692=t,c3693=t,c3694=t,c3695=t,c3696=t,c3697=t,c3698=t,c3699=t,c3700=t,c3701=t,c3702=t,c3703=t,c3704=t,c3705=t,c3706=t,c3707=t,c3708=t,c3709=t,c3710=t,c3711=t,c3712=t,c3713=t,c3714=t,c3715=t,c3716=t,c3717=t,c3718=t,c3719=t,c3720=t,c3721=t,c3722=t,c3723=t,c3724=t,c3725=t,c3726=t,c3727=t,c3728=t,c3729=t,c3730=t,c3731=t,c3732=t,c3733=t,c3734=t,c3735=t,c3736=t,c3737=t,c3738=t,c3739=t,c3740=t,c3741=t,c3742=t,c3743=t,c3744=t,c3745=t,c3746=t,c3747=t,c3748=t,c3749=t,c3750=t,c3751=t,c3752=t,c3753=t,c3754=t,c3755=t,c3756=t,c3757=t,c3758=t,c3759=t,c3760=t,c3761=t,c3762=t,c3763=t,c3764=t,c3765=t,c3766=t,c3767=t,c3768=t,c3769=t,c3770=t,c3771=t,c3772=t,c3773=t,c3774=t,c3775=t,c3776=t,c3777=t,c3778=t,c3779=t,c3780=t,c3781=t,c3782=t,c3783=t,c3784=t,c3785=t,c3786=t,c3787=t,c3788=t,c3789=t,c3790=t,c3791=t,c3792=t,c3793=t,c3794=t,c3795=t,c3796=t,c3797=t,c3798=t,c3799=t,c3800=t,c3801=t,c3802=t,c3803=t,c3804=t,c3805=t,c3806=t,c3807=t,"
"c3808=t,c3809=t,c3810=t,c3811=t,c3812=t,c3813=t,c3814=t,c3815=t,c3816=t,c3817=t,c3818=t,c3819=t,c3820=t,c3821=t,c3822=t,c3823=t,c3824=t,c3825=t,c3826=t,c3827=t,c3828=t,c3829=t,c3830=t,c3831=t,c3832=t,c3833=t,c3834=t,c3835=t,c3836=t,c3837=t,c3838=t,c3839=t,c3840=t,c3841=t,c3842=t,c3843=t,c3844=t,c3845=t,c3846=t,c3847=t,c3848=t,c3849=t,c3850=t,c3851=t,c3852=t,c3853=t,c3854=t,c3855=t,c3856=t,c3857=t,c3858=t,c3859=t,c3860=t,c3861=t,c3862=t,c3863=t,c3864=t,c3865=t,c3866=t,c3867=t,c3868=t,c3869=t,c3870=t,c3871=t,c3872=t,c3873=t,c3874=t,c3875=t,c3876=t,c3877=t,c3878=t,c3879=t,c3880=t,c3881=t,c3882=t,c3883=t,c3884=t,c3885=t,c3886=t,c3887=t,c3888=t,c3889=t,c3890=t,c3891=t,c3892=t,c3893=t,c3894=t,c3895=t,c3896=t,c3897=t,c3898=t,c3899=t,c3900=t,c3901=t,c3902=t,c3903=t,c3904=t,c3905=t,c3906=t,c3907=t,c3908=t,c3909=t,c3910=t,c3911=t,c3912=t,c3913=t,c3914=t,c3915=t,c3916=t,c3917=t,c3918=t,c3919=t,c3920=t,c3921=t,c3922=t,c3923=t,c3924=t,c3925=t,c3926=t,c3927=t,c3928=t,c3929=t,c3930=t,c3931=t,c3932=t,c3933=t,c3934=t,c3935=t,c3936=t,c3937=t,c3938=t,c3939=t,c3940=t,c3941=t,c3942=t,c3943=t,c3944=t,c3945=t,c3946=t,c3947=t,c3948=t,c3949=t,c3950=t,c3951=t,c3952=t,c3953=t,c3954=t,"
"c3955=t,c3956=t,c3957=t,c3958=t,c3959=t,c3960=t,c3961=t,c3962=t,c3963=t,c3964=t,c3965=t,c3966=t,c3967=t,c3968=t,c3969=t,c3970=t,c3971=t,c3972=t,c3973=t,c3974=t,c3975=t,c3976=t,c3977=t,c3978=t,c3979=t,c3980=t,c3981=t,c3982=t,c3983=t,c3984=t,c3985=t,c3986=t,c3987=t,c3988=t,c3989=t,c3990=t,c3991=t,c3992=t,c3993=t,c3994=t,c3995=t,c3996=t,c3997=t,c3998=t,c3999=t,c4000=t,c4001=t,c4002=t,c4003=t,c4004=t,c4005=t,c4006=t,c4007=t,c4008=t,c4009=t,c4010=t,c4011=t,c4012=t,c4013=t,c4014=t,c4015=t,c4016=t,c4017=t,c4018=t,c4019=t,c4020=t,c4021=t,c4022=t,c4023=t,c4024=t,c4025=t,c4026=t,c4027=t,c4028=t,c4029=t,c4030=t,c4031=t,c4032=t,c4033=t,c4034=t,c4035=t,c4036=t,c4037=t,c4038=t,c4039=t,c4040=t,c4041=t,c4042=t,c4043=t,c4044=t,c4045=t,c4046=t,c4047=t,c4048=t,c4049=t,c4050=t,c4051=t,c4052=t,c4053=t,c4054=t,c4055=t,c4056=t,c4057=t,c4058=t,c4059=t,c4060=t,c4061=t,c4062=t,c4063=t,c4064=t,c4065=t,c4066=t,c4067=t,c4068=t,c4069=t,c4070=t,c4071=t,c4072=t,c4073=t,c4074=t,c4075=t,c4076=t,c4077=t,c4078=t,c4079=t,c4080=t,c4081=t,c4082=t,c4083=t,c4084=t,c4085=t,c4086=t,c4087=t,c4088=t,c4089=t,c4090=t,c4091=t,c4092=t,c4093=t 1626006833640000000"
};
int ret = TSDB_CODE_SUCCESS;
for(int i = 0; i < sizeof(sql)/sizeof(sql[0]); i++){
ret = smlParseInfluxLine(info, sql[i]);
if(ret != TSDB_CODE_SUCCESS) break;
}
ASSERT_NE(ret, 0);
smlDestroyInfo(info);
}

2
source/common/src/systable.c
View File

@ -350,7 +350,7 @@ static const SSysTableMeta perfsMeta[] = {
{TSDB_PERFS_TABLE_SUBSCRIPTIONS, subscriptionSchema, tListLen(subscriptionSchema), false},
// {TSDB_PERFS_TABLE_OFFSETS, offsetSchema, tListLen(offsetSchema)},
{TSDB_PERFS_TABLE_TRANS, transSchema, tListLen(transSchema), false},
{TSDB_PERFS_TABLE_SMAS, smaSchema, tListLen(smaSchema), false},
// {TSDB_PERFS_TABLE_SMAS, smaSchema, tListLen(smaSchema), false},
{TSDB_PERFS_TABLE_STREAMS, streamSchema, tListLen(streamSchema), false},
{TSDB_PERFS_TABLE_APPS, appSchema, tListLen(appSchema), false}};
// clang-format on

5
source/common/src/tdatablock.c
View File

@ -1228,6 +1228,7 @@ void blockDataFreeRes(SSDataBlock* pBlock) {
}
taosArrayDestroy(pBlock->pDataBlock);
pBlock->pDataBlock = NULL;
taosMemoryFreeClear(pBlock->pBlockAgg);
memset(&pBlock->info, 0, sizeof(SDataBlockInfo));
}
@ -1706,8 +1707,8 @@ static char* formatTimestamp(char* buf, int64_t val, int precision) {
}
void blockDebugShowDataBlock(SSDataBlock* pBlock, const char* flag) {
SArray* dataBlocks = taosArrayInit(1, sizeof(SSDataBlock));
taosArrayPush(dataBlocks, pBlock);
SArray* dataBlocks = taosArrayInit(1, sizeof(SSDataBlock*));
taosArrayPush(dataBlocks, &pBlock);
blockDebugShowDataBlocks(dataBlocks, flag);
taosArrayDestroy(dataBlocks);
}

20
source/common/src/tdataformat.c
View File

@ -1064,6 +1064,26 @@ _err:
return code;
}
void tTagSetCid(const STag *pTag, int16_t iTag, int16_t cid) {
uint8_t *p = NULL;
int8_t isLarge = pTag->flags & TD_TAG_LARGE;
int16_t offset = 0;
if (isLarge) {
p = (uint8_t *)&((int16_t *)pTag->idx)[pTag->nTag];
} else {
p = (uint8_t *)&pTag->idx[pTag->nTag];
}
if (isLarge) {
offset = ((int16_t *)pTag->idx)[iTag];
} else {
offset = pTag->idx[iTag];
}
tPutI16v(p + offset, cid);
}
#if 1 // ===================================================================================================================
int tdInitTSchemaBuilder(STSchemaBuilder *pBuilder, schema_ver_t version) {
if (pBuilder == NULL) return -1;

27
source/common/src/tmsg.c
View File

@ -5675,7 +5675,7 @@ void tFreeSMCreateStbRsp(SMCreateStbRsp *pRsp) {
int32_t tEncodeSTqOffsetVal(SEncoder *pEncoder, const STqOffsetVal *pOffsetVal) {
if (tEncodeI8(pEncoder, pOffsetVal->type) < 0) return -1;
if (pOffsetVal->type == TMQ_OFFSET__SNAPSHOT_DATA) {
if (pOffsetVal->type == TMQ_OFFSET__SNAPSHOT_DATA || pOffsetVal->type == TMQ_OFFSET__SNAPSHOT_META) {
if (tEncodeI64(pEncoder, pOffsetVal->uid) < 0) return -1;
if (tEncodeI64(pEncoder, pOffsetVal->ts) < 0) return -1;
} else if (pOffsetVal->type == TMQ_OFFSET__LOG) {
@ -5690,7 +5690,7 @@ int32_t tEncodeSTqOffsetVal(SEncoder *pEncoder, const STqOffsetVal *pOffsetVal)
int32_t tDecodeSTqOffsetVal(SDecoder *pDecoder, STqOffsetVal *pOffsetVal) {
if (tDecodeI8(pDecoder, &pOffsetVal->type) < 0) return -1;
if (pOffsetVal->type == TMQ_OFFSET__SNAPSHOT_DATA) {
if (pOffsetVal->type == TMQ_OFFSET__SNAPSHOT_DATA || pOffsetVal->type == TMQ_OFFSET__SNAPSHOT_META) {
if (tDecodeI64(pDecoder, &pOffsetVal->uid) < 0) return -1;
if (tDecodeI64(pDecoder, &pOffsetVal->ts) < 0) return -1;
} else if (pOffsetVal->type == TMQ_OFFSET__LOG) {
@ -5712,10 +5712,8 @@ int32_t tFormatOffset(char *buf, int32_t maxLen, const STqOffsetVal *pVal) {
snprintf(buf, maxLen, "offset(reset to latest)");
} else if (pVal->type == TMQ_OFFSET__LOG) {
snprintf(buf, maxLen, "offset(log) ver:%" PRId64, pVal->version);
} else if (pVal->type == TMQ_OFFSET__SNAPSHOT_DATA) {
} else if (pVal->type == TMQ_OFFSET__SNAPSHOT_DATA || pVal->type == TMQ_OFFSET__SNAPSHOT_META) {
snprintf(buf, maxLen, "offset(ss data) uid:%" PRId64 ", ts:%" PRId64, pVal->uid, pVal->ts);
} else if (pVal->type == TMQ_OFFSET__SNAPSHOT_META) {
snprintf(buf, maxLen, "offset(ss meta) uid:%" PRId64 ", ts:%" PRId64, pVal->uid, pVal->ts);
} else {
ASSERT(0);
}
@ -5729,9 +5727,7 @@ bool tOffsetEqual(const STqOffsetVal *pLeft, const STqOffsetVal *pRight) {
} else if (pLeft->type == TMQ_OFFSET__SNAPSHOT_DATA) {
return pLeft->uid == pRight->uid && pLeft->ts == pRight->ts;
} else if (pLeft->type == TMQ_OFFSET__SNAPSHOT_META) {
ASSERT(0);
// TODO
return pLeft->uid == pRight->uid && pLeft->ts == pRight->ts;
return pLeft->uid == pRight->uid;
} else {
ASSERT(0);
/*ASSERT(pLeft->type == TMQ_OFFSET__RESET_NONE || pLeft->type == TMQ_OFFSET__RESET_EARLIEAST ||*/
@ -5816,6 +5812,21 @@ int32_t tDecodeDeleteRes(SDecoder *pCoder, SDeleteRes *pRes) {
if (tDecodeCStrTo(pCoder, pRes->tsColName) < 0) return -1;
return 0;
}
int32_t tEncodeSMqMetaRsp(SEncoder* pEncoder, const SMqMetaRsp* pRsp) {
if (tEncodeSTqOffsetVal(pEncoder, &pRsp->rspOffset) < 0) return -1;
if(tEncodeI16(pEncoder, pRsp->resMsgType)) return -1;
if(tEncodeBinary(pEncoder, pRsp->metaRsp, pRsp->metaRspLen)) return -1;
return 0;
}
int32_t tDecodeSMqMetaRsp(SDecoder* pDecoder, SMqMetaRsp* pRsp) {
if (tDecodeSTqOffsetVal(pDecoder, &pRsp->rspOffset) < 0) return -1;
if (tDecodeI16(pDecoder, &pRsp->resMsgType) < 0) return -1;
if (tDecodeBinaryAlloc(pDecoder, &pRsp->metaRsp, (uint64_t*)&pRsp->metaRspLen) < 0) return -1;
return 0;
}
int32_t tEncodeSMqDataRsp(SEncoder *pEncoder, const SMqDataRsp *pRsp) {
if (tEncodeSTqOffsetVal(pEncoder, &pRsp->reqOffset) < 0) return -1;
if (tEncodeSTqOffsetVal(pEncoder, &pRsp->rspOffset) < 0) return -1;

14
source/dnode/mnode/impl/src/mndMnode.c
View File

@ -89,14 +89,14 @@ static int32_t mndCreateDefaultMnode(SMnode *pMnode) {
if (pRaw == NULL) return -1;
sdbSetRawStatus(pRaw, SDB_STATUS_READY);
mDebug("mnode:%d, will be created when deploying, raw:%p", mnodeObj.id, pRaw);
mInfo("mnode:%d, will be created when deploying, raw:%p", mnodeObj.id, pRaw);
STrans *pTrans = mndTransCreate(pMnode, TRN_POLICY_RETRY, TRN_CONFLICT_GLOBAL, NULL);
if (pTrans == NULL) {
mError("mnode:%d, failed to create since %s", mnodeObj.id, terrstr());
return -1;
}
mDebug("trans:%d, used to create mnode:%d", pTrans->id, mnodeObj.id);
mInfo("trans:%d, used to create mnode:%d", pTrans->id, mnodeObj.id);
if (mndTransAppendCommitlog(pTrans, pRaw) != 0) {
mError("trans:%d, failed to append commit log since %s", pTrans->id, terrstr());
@ -365,7 +365,7 @@ static int32_t mndCreateMnode(SMnode *pMnode, SRpcMsg *pReq, SDnodeObj *pDnode,
STrans *pTrans = mndTransCreate(pMnode, TRN_POLICY_RETRY, TRN_CONFLICT_GLOBAL, pReq);
if (pTrans == NULL) goto _OVER;
mndTransSetSerial(pTrans);
mDebug("trans:%d, used to create mnode:%d", pTrans->id, pCreate->dnodeId);
mInfo("trans:%d, used to create mnode:%d", pTrans->id, pCreate->dnodeId);
if (mndSetCreateMnodeRedoLogs(pMnode, pTrans, &mnodeObj) != 0) goto _OVER;
if (mndSetCreateMnodeCommitLogs(pMnode, pTrans, &mnodeObj) != 0) goto _OVER;
@ -392,7 +392,7 @@ static int32_t mndProcessCreateMnodeReq(SRpcMsg *pReq) {
goto _OVER;
}
mDebug("mnode:%d, start to create", createReq.dnodeId);
mInfo("mnode:%d, start to create", createReq.dnodeId);
if (mndCheckOperPrivilege(pMnode, pReq->info.conn.user, MND_OPER_CREATE_MNODE) != 0) {
goto _OVER;
}
@ -574,7 +574,7 @@ static int32_t mndDropMnode(SMnode *pMnode, SRpcMsg *pReq, SMnodeObj *pObj) {
pTrans = mndTransCreate(pMnode, TRN_POLICY_RETRY, TRN_CONFLICT_GLOBAL, pReq);
if (pTrans == NULL) goto _OVER;
mndTransSetSerial(pTrans);
mDebug("trans:%d, used to drop mnode:%d", pTrans->id, pObj->id);
mInfo("trans:%d, used to drop mnode:%d", pTrans->id, pObj->id);
if (mndSetDropMnodeInfoToTrans(pMnode, pTrans, pObj) != 0) goto _OVER;
if (mndTransPrepare(pMnode, pTrans) != 0) goto _OVER;
@ -597,7 +597,7 @@ static int32_t mndProcessDropMnodeReq(SRpcMsg *pReq) {
goto _OVER;
}
mDebug("mnode:%d, start to drop", dropReq.dnodeId);
mInfo("mnode:%d, start to drop", dropReq.dnodeId);
if (mndCheckOperPrivilege(pMnode, pReq->info.conn.user, MND_OPER_DROP_MNODE) != 0) {
goto _OVER;
}
@ -732,7 +732,7 @@ static int32_t mndProcessAlterMnodeReq(SRpcMsg *pReq) {
}
}
mTrace("trans:-1, sync reconfig will be proposed");
mInfo("trans:-1, sync reconfig will be proposed");
SSyncMgmt *pMgmt = &pMnode->syncMgmt;
pMgmt->standby = 0;

3
source/dnode/mnode/impl/src/mndSma.c
View File

@ -38,7 +38,6 @@ static SSdbRow *mndSmaActionDecode(SSdbRaw *pRaw);
static int32_t mndSmaActionInsert(SSdb *pSdb, SSmaObj *pSma);
static int32_t mndSmaActionDelete(SSdb *pSdb, SSmaObj *pSpSmatb);
static int32_t mndSmaActionUpdate(SSdb *pSdb, SSmaObj *pOld, SSmaObj *pNew);
static int32_t mndSmaGetVgEpSet(SMnode *pMnode, SDbObj *pDb, SVgEpSet **ppVgEpSet, int32_t *numOfVgroups);
static int32_t mndProcessCreateSmaReq(SRpcMsg *pReq);
static int32_t mndProcessDropSmaReq(SRpcMsg *pReq);
static int32_t mndProcessGetSmaReq(SRpcMsg *pReq);
@ -841,6 +840,7 @@ static int32_t mndDropSma(SMnode *pMnode, SRpcMsg *pReq, SDbObj *pDb, SSmaObj *p
_OVER:
mndTransDrop(pTrans);
mndReleaseStream(pMnode, pStream);
mndReleaseVgroup(pMnode, pVgroup);
mndReleaseStb(pMnode, pStb);
return code;
@ -961,6 +961,7 @@ _OVER:
mError("sma:%s, failed to drop since %s", dropReq.name, terrstr());
}
mndReleaseSma(pMnode, pSma);
mndReleaseDb(pMnode, pDb);
return code;
}

2
source/dnode/mnode/impl/src/mndStb.c
View File

@ -536,7 +536,7 @@ int32_t mndCheckCreateStbReq(SMCreateStbReq *pCreate) {
return -1;
}
if (pCreate->numOfColumns < TSDB_MIN_COLUMNS || pCreate->numOfColumns > TSDB_MAX_COLUMNS) {
if (pCreate->numOfColumns < TSDB_MIN_COLUMNS || pCreate->numOfTags + pCreate->numOfColumns > TSDB_MAX_COLUMNS) {
terrno = TSDB_CODE_PAR_INVALID_COLUMNS_NUM;
return -1;
}

28
source/dnode/mnode/impl/src/mndSync.c
View File

@ -50,7 +50,7 @@ void mndSyncCommitMsg(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SFsmCbMeta cbM
int32_t transId = sdbGetIdFromRaw(pMnode->pSdb, pRaw);
pMgmt->errCode = cbMeta.code;
mDebug("trans:%d, is proposed, saved:%d code:0x%x, apply index:%" PRId64 " term:%" PRIu64 " config:%" PRId64
mInfo("trans:%d, is proposed, saved:%d code:0x%x, apply index:%" PRId64 " term:%" PRIu64 " config:%" PRId64
" role:%s raw:%p",
transId, pMgmt->transId, cbMeta.code, cbMeta.index, cbMeta.term, cbMeta.lastConfigIndex, syncStr(cbMeta.state),
pRaw);
@ -68,7 +68,7 @@ void mndSyncCommitMsg(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SFsmCbMeta cbM
if (pMgmt->errCode != 0) {
mError("trans:%d, failed to propose since %s, post sem", transId, tstrerror(pMgmt->errCode));
} else {
mDebug("trans:%d, is proposed and post sem", transId, tstrerror(pMgmt->errCode));
mInfo("trans:%d, is proposed and post sem", transId, tstrerror(pMgmt->errCode));
}
pMgmt->transId = 0;
taosWUnLockLatch(&pMgmt->lock);
@ -88,7 +88,7 @@ void mndSyncCommitMsg(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SFsmCbMeta cbM
}
int32_t mndSyncGetSnapshot(struct SSyncFSM *pFsm, SSnapshot *pSnapshot, void *pReaderParam, void **ppReader) {
mDebug("start to read snapshot from sdb in atomic way");
mInfo("start to read snapshot from sdb in atomic way");
SMnode *pMnode = pFsm->data;
return sdbStartRead(pMnode->pSdb, (SSdbIter **)ppReader, &pSnapshot->lastApplyIndex, &pSnapshot->lastApplyTerm,
&pSnapshot->lastConfigIndex);
@ -118,7 +118,7 @@ void mndReConfig(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SReConfigCbMeta cbM
SSyncMgmt *pMgmt = &pMnode->syncMgmt;
pMgmt->errCode = cbMeta.code;
mDebug("trans:-1, sync reconfig is proposed, saved:%d code:0x%x, index:%" PRId64 " term:%" PRId64, pMgmt->transId,
mInfo("trans:-1, sync reconfig is proposed, saved:%d code:0x%x, index:%" PRId64 " term:%" PRId64, pMgmt->transId,
cbMeta.code, cbMeta.index, cbMeta.term);
taosWLockLatch(&pMgmt->lock);
@ -126,7 +126,7 @@ void mndReConfig(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SReConfigCbMeta cbM
if (pMgmt->errCode != 0) {
mError("trans:-1, failed to propose sync reconfig since %s, post sem", tstrerror(pMgmt->errCode));
} else {
mDebug("trans:-1, sync reconfig is proposed, saved:%d code:0x%x, index:%" PRId64 " term:%" PRId64 " post sem",
mInfo("trans:-1, sync reconfig is proposed, saved:%d code:0x%x, index:%" PRId64 " term:%" PRId64 " post sem",
pMgmt->transId, cbMeta.code, cbMeta.index, cbMeta.term);
}
pMgmt->transId = 0;
@ -136,13 +136,13 @@ void mndReConfig(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SReConfigCbMeta cbM
}
int32_t mndSnapshotStartRead(struct SSyncFSM *pFsm, void *pParam, void **ppReader) {
mDebug("start to read snapshot from sdb");
mInfo("start to read snapshot from sdb");
SMnode *pMnode = pFsm->data;
return sdbStartRead(pMnode->pSdb, (SSdbIter **)ppReader, NULL, NULL, NULL);
}
int32_t mndSnapshotStopRead(struct SSyncFSM *pFsm, void *pReader) {
mDebug("stop to read snapshot from sdb");
mInfo("stop to read snapshot from sdb");
SMnode *pMnode = pFsm->data;
return sdbStopRead(pMnode->pSdb, pReader);
}
@ -174,12 +174,12 @@ int32_t mndSnapshotDoWrite(struct SSyncFSM *pFsm, void *pWriter, void *pBuf, int
void mndLeaderTransfer(struct SSyncFSM *pFsm, const SRpcMsg *pMsg, SFsmCbMeta cbMeta) {
SMnode *pMnode = pFsm->data;
atomic_store_8(&(pMnode->syncMgmt.leaderTransferFinish), 1);
mDebug("vgId:1, mnode leader transfer finish");
mInfo("vgId:1, mnode leader transfer finish");
}
static void mndBecomeFollower(struct SSyncFSM *pFsm) {
SMnode *pMnode = pFsm->data;
mDebug("vgId:1, become follower and post sem");
mInfo("vgId:1, become follower and post sem");
taosWLockLatch(&pMnode->syncMgmt.lock);
if (pMnode->syncMgmt.transId != 0) {
@ -190,7 +190,7 @@ static void mndBecomeFollower(struct SSyncFSM *pFsm) {
}
static void mndBecomeLeader(struct SSyncFSM *pFsm) {
mDebug("vgId:1, become leader");
mInfo("vgId:1, become leader");
SMnode *pMnode = pFsm->data;
}
@ -228,7 +228,7 @@ int32_t mndInitSync(SMnode *pMnode) {
syncInfo.isStandBy = pMgmt->standby;
syncInfo.snapshotStrategy = SYNC_STRATEGY_STANDARD_SNAPSHOT;
mDebug("start to open mnode sync, standby:%d", pMgmt->standby);
mInfo("start to open mnode sync, standby:%d", pMgmt->standby);
if (pMgmt->standby || pMgmt->replica.id > 0) {
SSyncCfg *pCfg = &syncInfo.syncCfg;
pCfg->replicaNum = 1;
@ -236,7 +236,7 @@ int32_t mndInitSync(SMnode *pMnode) {
SNodeInfo *pNode = &pCfg->nodeInfo[0];
tstrncpy(pNode->nodeFqdn, pMgmt->replica.fqdn, sizeof(pNode->nodeFqdn));
pNode->nodePort = pMgmt->replica.port;
mDebug("mnode ep:%s:%u", pNode->nodeFqdn, pNode->nodePort);
mInfo("mnode ep:%s:%u", pNode->nodeFqdn, pNode->nodePort);
}
tsem_init(&pMgmt->syncSem, 0, 0);
@ -284,7 +284,7 @@ int32_t mndSyncPropose(SMnode *pMnode, SSdbRaw *pRaw, int32_t transId) {
return -1;
} else {
pMgmt->transId = transId;
mDebug("trans:%d, will be proposed", pMgmt->transId);
mInfo("trans:%d, will be proposed", pMgmt->transId);
taosWUnLockLatch(&pMgmt->lock);
}
@ -314,7 +314,7 @@ void mndSyncStart(SMnode *pMnode) {
SSyncMgmt *pMgmt = &pMnode->syncMgmt;
syncSetMsgCb(pMgmt->sync, &pMnode->msgCb);
syncStart(pMgmt->sync);
mDebug("mnode sync started, id:%" PRId64 " standby:%d", pMgmt->sync, pMgmt->standby);
mInfo("mnode sync started, id:%" PRId64 " standby:%d", pMgmt->sync, pMgmt->standby);
}
void mndSyncStop(SMnode *pMnode) {

76
source/dnode/mnode/impl/src/mndTrans.c
View File

@ -456,11 +456,11 @@ static const char *mndTransStr(ETrnStage stage) {
}
static void mndTransTestStartFunc(SMnode *pMnode, void *param, int32_t paramLen) {
mDebug("test trans start, param:%s, len:%d", (char *)param, paramLen);
mInfo("test trans start, param:%s, len:%d", (char *)param, paramLen);
}
static void mndTransTestStopFunc(SMnode *pMnode, void *param, int32_t paramLen) {
mDebug("test trans stop, param:%s, len:%d", (char *)param, paramLen);
mInfo("test trans stop, param:%s, len:%d", (char *)param, paramLen);
}
static TransCbFp mndTransGetCbFp(ETrnFunc ftype) {
@ -707,7 +707,7 @@ int32_t mndSetRpcInfoForDbTrans(SMnode *pMnode, SRpcMsg *pMsg, EOperType oper, c
if (pTrans->oper == oper) {
if (strcasecmp(dbname, pTrans->dbname1) == 0) {
mDebug("trans:%d, db:%s oper:%d matched with input", pTrans->id, dbname, oper);
mInfo("trans:%d, db:%s oper:%d matched with input", pTrans->id, dbname, oper);
if (pTrans->pRpcArray == NULL) {
pTrans->pRpcArray = taosArrayInit(1, sizeof(SRpcHandleInfo));
}
@ -746,7 +746,7 @@ static int32_t mndTransSync(SMnode *pMnode, STrans *pTrans) {
}
sdbSetRawStatus(pRaw, SDB_STATUS_READY);
mDebug("trans:%d, sync to other mnodes, stage:%s", pTrans->id, mndTransStr(pTrans->stage));
mInfo("trans:%d, sync to other mnodes, stage:%s", pTrans->id, mndTransStr(pTrans->stage));
int32_t code = mndSyncPropose(pMnode, pRaw, pTrans->id);
if (code != 0) {
mError("trans:%d, failed to sync since %s", pTrans->id, terrstr());
@ -755,7 +755,7 @@ static int32_t mndTransSync(SMnode *pMnode, STrans *pTrans) {
}
sdbFreeRaw(pRaw);
mDebug("trans:%d, sync finished", pTrans->id);
mInfo("trans:%d, sync finished", pTrans->id);
return 0;
}
@ -821,12 +821,12 @@ int32_t mndTransPrepare(SMnode *pMnode, STrans *pTrans) {
return -1;
}
mDebug("trans:%d, prepare transaction", pTrans->id);
mInfo("trans:%d, prepare transaction", pTrans->id);
if (mndTransSync(pMnode, pTrans) != 0) {
mError("trans:%d, failed to prepare since %s", pTrans->id, terrstr());
return -1;
}
mDebug("trans:%d, prepare finished", pTrans->id);
mInfo("trans:%d, prepare finished", pTrans->id);
STrans *pNew = mndAcquireTrans(pMnode, pTrans->id);
if (pNew == NULL) {
@ -847,22 +847,22 @@ int32_t mndTransPrepare(SMnode *pMnode, STrans *pTrans) {
}
static int32_t mndTransCommit(SMnode *pMnode, STrans *pTrans) {
mDebug("trans:%d, commit transaction", pTrans->id);
mInfo("trans:%d, commit transaction", pTrans->id);
if (mndTransSync(pMnode, pTrans) != 0) {
mError("trans:%d, failed to commit since %s", pTrans->id, terrstr());
return -1;
}
mDebug("trans:%d, commit finished", pTrans->id);
mInfo("trans:%d, commit finished", pTrans->id);
return 0;
}
static int32_t mndTransRollback(SMnode *pMnode, STrans *pTrans) {
mDebug("trans:%d, rollback transaction", pTrans->id);
mInfo("trans:%d, rollback transaction", pTrans->id);
if (mndTransSync(pMnode, pTrans) != 0) {
mError("trans:%d, failed to rollback since %s", pTrans->id, terrstr());
return -1;
}
mDebug("trans:%d, rollback finished", pTrans->id);
mInfo("trans:%d, rollback finished", pTrans->id);
return 0;
}
@ -894,7 +894,7 @@ static void mndTransSendRpcRsp(SMnode *pMnode, STrans *pTrans) {
for (int32_t i = 0; i < size; ++i) {
SRpcHandleInfo *pInfo = taosArrayGet(pTrans->pRpcArray, i);
if (pInfo->handle != NULL) {
mDebug("trans:%d, send rsp, code:0x%x stage:%s app:%p", pTrans->id, code, mndTransStr(pTrans->stage),
mInfo("trans:%d, send rsp, code:0x%x stage:%s app:%p", pTrans->id, code, mndTransStr(pTrans->stage),
pInfo->ahandle);
if (code == TSDB_CODE_RPC_NETWORK_UNAVAIL) {
code = TSDB_CODE_MND_TRANS_NETWORK_UNAVAILL;
@ -902,13 +902,13 @@ static void mndTransSendRpcRsp(SMnode *pMnode, STrans *pTrans) {
SRpcMsg rspMsg = {.code = code, .info = *pInfo};
if (pTrans->originRpcType == TDMT_MND_CREATE_DB) {
mDebug("trans:%d, origin msgtype:%s", pTrans->id, TMSG_INFO(pTrans->originRpcType));
mInfo("trans:%d, origin msgtype:%s", pTrans->id, TMSG_INFO(pTrans->originRpcType));
SDbObj *pDb = mndAcquireDb(pMnode, pTrans->dbname1);
if (pDb != NULL) {
for (int32_t j = 0; j < 12; j++) {
bool ready = mndIsDbReady(pMnode, pDb);
if (!ready) {
mDebug("trans:%d, db:%s not ready yet, wait %d times", pTrans->id, pTrans->dbname1, j);
mInfo("trans:%d, db:%s not ready yet, wait %d times", pTrans->id, pTrans->dbname1, j);
taosMsleep(1000);
} else {
break;
@ -978,7 +978,7 @@ int32_t mndTransProcessRsp(SRpcMsg *pRsp) {
pAction->errCode = pRsp->code;
}
mDebug("trans:%d, %s:%d response is received, code:0x%x, accept:0x%x retry:0x%x", transId,
mInfo("trans:%d, %s:%d response is received, code:0x%x, accept:0x%x retry:0x%x", transId,
mndTransStr(pAction->stage), action, pRsp->code, pAction->acceptableCode, pAction->retryCode);
mndTransExecute(pMnode, pTrans);
@ -994,10 +994,10 @@ static void mndTransResetAction(SMnode *pMnode, STrans *pTrans, STransAction *pA
if (pAction->errCode == TSDB_CODE_RPC_REDIRECT || pAction->errCode == TSDB_CODE_SYN_NEW_CONFIG_ERROR ||
pAction->errCode == TSDB_CODE_SYN_INTERNAL_ERROR || pAction->errCode == TSDB_CODE_SYN_NOT_LEADER) {
pAction->epSet.inUse = (pAction->epSet.inUse + 1) % pAction->epSet.numOfEps;
mDebug("trans:%d, %s:%d execute status is reset and set epset inuse:%d", pTrans->id, mndTransStr(pAction->stage),
mInfo("trans:%d, %s:%d execute status is reset and set epset inuse:%d", pTrans->id, mndTransStr(pAction->stage),
pAction->id, pAction->epSet.inUse);
} else {
mDebug("trans:%d, %s:%d execute status is reset", pTrans->id, mndTransStr(pAction->stage), pAction->id);
mInfo("trans:%d, %s:%d execute status is reset", pTrans->id, mndTransStr(pAction->stage), pAction->id);
}
pAction->errCode = 0;
}
@ -1024,7 +1024,7 @@ static int32_t mndTransWriteSingleLog(SMnode *pMnode, STrans *pTrans, STransActi
pAction->rawWritten = true;
pAction->errCode = 0;
code = 0;
mDebug("trans:%d, %s:%d write to sdb, type:%s status:%s", pTrans->id, mndTransStr(pAction->stage), pAction->id,
mInfo("trans:%d, %s:%d write to sdb, type:%s status:%s", pTrans->id, mndTransStr(pAction->stage), pAction->id,
sdbTableName(pAction->pRaw->type), sdbStatusName(pAction->pRaw->status));
pTrans->lastAction = pAction->id;
@ -1073,7 +1073,7 @@ static int32_t mndTransSendSingleMsg(SMnode *pMnode, STrans *pTrans, STransActio
pAction->msgSent = 1;
pAction->msgReceived = 0;
pAction->errCode = 0;
mDebug("trans:%d, %s:%d is sent, %s", pTrans->id, mndTransStr(pAction->stage), pAction->id, detail);
mInfo("trans:%d, %s:%d is sent, %s", pTrans->id, mndTransStr(pAction->stage), pAction->id, detail);
pTrans->lastAction = pAction->id;
pTrans->lastMsgType = pAction->msgType;
@ -1100,7 +1100,7 @@ static int32_t mndTransSendSingleMsg(SMnode *pMnode, STrans *pTrans, STransActio
static int32_t mndTransExecNullMsg(SMnode *pMnode, STrans *pTrans, STransAction *pAction) {
pAction->rawWritten = 0;
pAction->errCode = 0;
mDebug("trans:%d, %s:%d confirm action executed", pTrans->id, mndTransStr(pAction->stage), pAction->id);
mInfo("trans:%d, %s:%d confirm action executed", pTrans->id, mndTransStr(pAction->stage), pAction->id);
pTrans->lastAction = pAction->id;
pTrans->lastMsgType = pAction->msgType;
@ -1160,7 +1160,7 @@ static int32_t mndTransExecuteActions(SMnode *pMnode, STrans *pTrans, SArray *pA
pTrans->lastMsgType = 0;
memset(&pTrans->lastEpset, 0, sizeof(pTrans->lastEpset));
pTrans->lastErrorNo = 0;
mDebug("trans:%d, all %d actions execute successfully", pTrans->id, numOfActions);
mInfo("trans:%d, all %d actions execute successfully", pTrans->id, numOfActions);
return 0;
} else {
mError("trans:%d, all %d actions executed, code:0x%x", pTrans->id, numOfActions, errCode & 0XFFFF);
@ -1175,7 +1175,7 @@ static int32_t mndTransExecuteActions(SMnode *pMnode, STrans *pTrans, SArray *pA
return errCode;
}
} else {
mDebug("trans:%d, %d of %d actions executed", pTrans->id, numOfExecuted, numOfActions);
mInfo("trans:%d, %d of %d actions executed", pTrans->id, numOfExecuted, numOfActions);
return TSDB_CODE_ACTION_IN_PROGRESS;
}
}
@ -1221,7 +1221,7 @@ static int32_t mndTransExecuteRedoActionsSerial(SMnode *pMnode, STrans *pTrans)
code = pAction->errCode;
mndTransResetAction(pMnode, pTrans, pAction);
} else {
mDebug("trans:%d, %s:%d execute successfully", pTrans->id, mndTransStr(pAction->stage), action);
mInfo("trans:%d, %s:%d execute successfully", pTrans->id, mndTransStr(pAction->stage), action);
}
} else {
code = TSDB_CODE_ACTION_IN_PROGRESS;
@ -1230,7 +1230,7 @@ static int32_t mndTransExecuteRedoActionsSerial(SMnode *pMnode, STrans *pTrans)
if (pAction->errCode != 0 && pAction->errCode != pAction->acceptableCode) {
code = pAction->errCode;
} else {
mDebug("trans:%d, %s:%d write successfully", pTrans->id, mndTransStr(pAction->stage), action);
mInfo("trans:%d, %s:%d write successfully", pTrans->id, mndTransStr(pAction->stage), action);
}
} else {
}
@ -1254,7 +1254,7 @@ static int32_t mndTransExecuteRedoActionsSerial(SMnode *pMnode, STrans *pTrans)
if (code == 0) {
pTrans->code = 0;
pTrans->redoActionPos++;
mDebug("trans:%d, %s:%d is executed and need sync to other mnodes", pTrans->id, mndTransStr(pAction->stage),
mInfo("trans:%d, %s:%d is executed and need sync to other mnodes", pTrans->id, mndTransStr(pAction->stage),
pAction->id);
code = mndTransSync(pMnode, pTrans);
if (code != 0) {
@ -1263,17 +1263,17 @@ static int32_t mndTransExecuteRedoActionsSerial(SMnode *pMnode, STrans *pTrans)
mndTransStr(pAction->stage), pAction->id, terrstr());
}
} else if (code == TSDB_CODE_ACTION_IN_PROGRESS) {
mDebug("trans:%d, %s:%d is in progress and wait it finish", pTrans->id, mndTransStr(pAction->stage), pAction->id);
mInfo("trans:%d, %s:%d is in progress and wait it finish", pTrans->id, mndTransStr(pAction->stage), pAction->id);
break;
} else if (code == pAction->retryCode) {
mDebug("trans:%d, %s:%d receive code:0x%x and retry", pTrans->id, mndTransStr(pAction->stage), pAction->id, code);
mInfo("trans:%d, %s:%d receive code:0x%x and retry", pTrans->id, mndTransStr(pAction->stage), pAction->id, code);
taosMsleep(300);
action--;
continue;
} else {
terrno = code;
pTrans->code = code;
mDebug("trans:%d, %s:%d receive code:0x%x and wait another schedule, failedTimes:%d", pTrans->id,
mInfo("trans:%d, %s:%d receive code:0x%x and wait another schedule, failedTimes:%d", pTrans->id,
mndTransStr(pAction->stage), pAction->id, code, pTrans->failedTimes);
break;
}
@ -1285,7 +1285,7 @@ static int32_t mndTransExecuteRedoActionsSerial(SMnode *pMnode, STrans *pTrans)
static bool mndTransPerformPrepareStage(SMnode *pMnode, STrans *pTrans) {
bool continueExec = true;
pTrans->stage = TRN_STAGE_REDO_ACTION;
mDebug("trans:%d, stage from prepare to redoAction", pTrans->id);
mInfo("trans:%d, stage from prepare to redoAction", pTrans->id);
return continueExec;
}
@ -1304,10 +1304,10 @@ static bool mndTransPerformRedoActionStage(SMnode *pMnode, STrans *pTrans) {
if (code == 0) {
pTrans->code = 0;
pTrans->stage = TRN_STAGE_COMMIT;
mDebug("trans:%d, stage from redoAction to commit", pTrans->id);
mInfo("trans:%d, stage from redoAction to commit", pTrans->id);
continueExec = true;
} else if (code == TSDB_CODE_ACTION_IN_PROGRESS) {
mDebug("trans:%d, stage keep on redoAction since %s", pTrans->id, tstrerror(code));
mInfo("trans:%d, stage keep on redoAction since %s", pTrans->id, tstrerror(code));
continueExec = false;
} else {
pTrans->failedTimes++;
@ -1347,7 +1347,7 @@ static bool mndTransPerformCommitStage(SMnode *pMnode, STrans *pTrans) {
if (code == 0) {
pTrans->code = 0;
pTrans->stage = TRN_STAGE_COMMIT_ACTION;
mDebug("trans:%d, stage from commit to commitAction", pTrans->id);
mInfo("trans:%d, stage from commit to commitAction", pTrans->id);
continueExec = true;
} else {
pTrans->code = terrno;
@ -1366,7 +1366,7 @@ static bool mndTransPerformCommitActionStage(SMnode *pMnode, STrans *pTrans) {
if (code == 0) {
pTrans->code = 0;
pTrans->stage = TRN_STAGE_FINISHED;
mDebug("trans:%d, stage from commitAction to finished", pTrans->id);
mInfo("trans:%d, stage from commitAction to finished", pTrans->id);
continueExec = true;
} else {
pTrans->code = terrno;
@ -1384,10 +1384,10 @@ static bool mndTransPerformUndoActionStage(SMnode *pMnode, STrans *pTrans) {
if (code == 0) {
pTrans->stage = TRN_STAGE_FINISHED;
mDebug("trans:%d, stage from undoAction to finished", pTrans->id);
mInfo("trans:%d, stage from undoAction to finished", pTrans->id);
continueExec = true;
} else if (code == TSDB_CODE_ACTION_IN_PROGRESS) {
mDebug("trans:%d, stage keep on undoAction since %s", pTrans->id, tstrerror(code));
mInfo("trans:%d, stage keep on undoAction since %s", pTrans->id, tstrerror(code));
continueExec = false;
} else {
pTrans->failedTimes++;
@ -1406,7 +1406,7 @@ static bool mndTransPerformRollbackStage(SMnode *pMnode, STrans *pTrans) {
if (code == 0) {
pTrans->stage = TRN_STAGE_UNDO_ACTION;
mDebug("trans:%d, stage from rollback to undoAction", pTrans->id);
mInfo("trans:%d, stage from rollback to undoAction", pTrans->id);
continueExec = true;
} else {
pTrans->failedTimes++;
@ -1431,7 +1431,7 @@ static bool mndTransPerfromFinishedStage(SMnode *pMnode, STrans *pTrans) {
mError("trans:%d, failed to write sdb since %s", pTrans->id, terrstr());
}
mDebug("trans:%d, execute finished, code:0x%x, failedTimes:%d", pTrans->id, pTrans->code, pTrans->failedTimes);
mInfo("trans:%d, execute finished, code:0x%x, failedTimes:%d", pTrans->id, pTrans->code, pTrans->failedTimes);
return continueExec;
}
@ -1439,7 +1439,7 @@ void mndTransExecute(SMnode *pMnode, STrans *pTrans) {
bool continueExec = true;
while (continueExec) {
mDebug("trans:%d, continue to execute, stage:%s", pTrans->id, mndTransStr(pTrans->stage));
mInfo("trans:%d, continue to execute, stage:%s", pTrans->id, mndTransStr(pTrans->stage));
pTrans->lastExecTime = taosGetTimestampMs();
switch (pTrans->stage) {
case TRN_STAGE_PREPARE:

43
source/dnode/vnode/inc/vnode.h
View File

@ -128,8 +128,10 @@ typedef struct STsdbReader STsdbReader;
#define TIMEWINDOW_RANGE_CONTAINED 1
#define TIMEWINDOW_RANGE_EXTERNAL 2
#define LASTROW_RETRIEVE_TYPE_ALL 0x1
#define LASTROW_RETRIEVE_TYPE_SINGLE 0x2
#define CACHESCAN_RETRIEVE_TYPE_ALL 0x1
#define CACHESCAN_RETRIEVE_TYPE_SINGLE 0x2
#define CACHESCAN_RETRIEVE_LAST_ROW 0x4
#define CACHESCAN_RETRIEVE_LAST 0x8
int32_t tsdbSetTableId(STsdbReader *pReader, int64_t uid);
int32_t tsdbReaderOpen(SVnode *pVnode, SQueryTableDataCond *pCond, SArray *pTableList, STsdbReader **ppReader,
@ -146,15 +148,40 @@ void *tsdbGetIdx(SMeta *pMeta);
void *tsdbGetIvtIdx(SMeta *pMeta);
uint64_t getReaderMaxVersion(STsdbReader *pReader);
int32_t tsdbLastRowReaderOpen(void *pVnode, int32_t type, SArray *pTableIdList, int32_t numOfCols, void **pReader);
int32_t tsdbRetrieveLastRow(void *pReader, SSDataBlock *pResBlock, const int32_t *slotIds, SArray *pTableUids);
int32_t tsdbLastrowReaderClose(void *pReader);
int32_t tsdbCacherowsReaderOpen(void *pVnode, int32_t type, SArray *pTableIdList, int32_t numOfCols, void **pReader);
int32_t tsdbRetrieveCacheRows(void *pReader, SSDataBlock *pResBlock, const int32_t *slotIds, SArray *pTableUids);
int32_t tsdbCacherowsReaderClose(void *pReader);
int32_t tsdbGetTableSchema(SVnode *pVnode, int64_t uid, STSchema **pSchema, int64_t *suid);
void tsdbCacheSetCapacity(SVnode *pVnode, size_t capacity);
size_t tsdbCacheGetCapacity(SVnode *pVnode);
// tq
typedef struct SMetaTableInfo{
int64_t suid;
int64_t uid;
SSchemaWrapper *schema;
char tbName[TSDB_TABLE_NAME_LEN];
}SMetaTableInfo;
typedef struct SIdInfo{
int64_t version;
int32_t index;
}SIdInfo;
typedef struct SSnapContext {
SMeta *pMeta;
int64_t snapVersion;
TBC *pCur;
int64_t suid;
int8_t subType;
SHashObj *idVersion;
SHashObj *suidInfo;
SArray *idList;
int32_t index;
bool withMeta;
bool queryMetaOrData; // true-get meta, false-get data
}SSnapContext;
typedef struct STqReader {
int64_t ver;
@ -205,6 +232,12 @@ int32_t vnodeSnapWriterOpen(SVnode *pVnode, int64_t sver, int64_t ever, SVSnapWr
int32_t vnodeSnapWriterClose(SVSnapWriter *pWriter, int8_t rollback, SSnapshot *pSnapshot);
int32_t vnodeSnapWrite(SVSnapWriter *pWriter, uint8_t *pData, uint32_t nData);
int32_t buildSnapContext(SMeta* pMeta, int64_t snapVersion, int64_t suid, int8_t subType, bool withMeta, SSnapContext** ctxRet);
int32_t getMetafromSnapShot(SSnapContext* ctx, void **pBuf, int32_t *contLen, int16_t *type, int64_t *uid);
SMetaTableInfo getUidfromSnapShot(SSnapContext* ctx);
int32_t setForSnapShot(SSnapContext* ctx, int64_t uid);
int32_t destroySnapContext(SSnapContext* ctx);
// structs
struct STsdbCfg {
int8_t precision;

16
source/dnode/vnode/src/inc/tq.h
View File

@ -68,27 +68,27 @@ typedef struct {
typedef struct {
char* qmsg;
qTaskInfo_t task;
} STqExecCol;
typedef struct {
int64_t suid;
int64_t suid;
} STqExecTb;
typedef struct {
SHashObj* pFilterOutTbUid;
SHashObj* pFilterOutTbUid;
} STqExecDb;
typedef struct {
int8_t subType;
STqReader* pExecReader;
qTaskInfo_t task;
union {
STqExecCol execCol;
STqExecTb execTb;
STqExecDb execDb;
};
int32_t numOfCols; // number of out pout column, temporarily used
// int32_t numOfCols; // number of out pout column, temporarily used
SSchemaWrapper* pSchemaWrapper; // columns that are involved in query
} STqExecHandle;
@ -101,7 +101,6 @@ typedef struct {
int64_t snapshotVer;
// TODO remove
SWalReader* pWalReader;
SWalRef* pRef;
@ -141,7 +140,7 @@ int32_t tEncodeSTqHandle(SEncoder* pEncoder, const STqHandle* pHandle);
int32_t tDecodeSTqHandle(SDecoder* pDecoder, STqHandle* pHandle);
// tqRead
int64_t tqScan(STQ* pTq, const STqHandle* pHandle, SMqDataRsp* pRsp, STqOffsetVal* offset);
int64_t tqScan(STQ* pTq, const STqHandle* pHandle, SMqDataRsp* pRsp, SMqMetaRsp* pMetaRsp, STqOffsetVal* offset);
int64_t tqFetchLog(STQ* pTq, STqHandle* pHandle, int64_t* fetchOffset, SWalCkHead** pHeadWithCkSum);
// tqExec
@ -182,6 +181,11 @@ static FORCE_INLINE void tqOffsetResetToData(STqOffsetVal* pOffsetVal, int64_t u
pOffsetVal->ts = ts;
}
static FORCE_INLINE void tqOffsetResetToMeta(STqOffsetVal* pOffsetVal, int64_t uid) {
pOffsetVal->type = TMQ_OFFSET__SNAPSHOT_META;
pOffsetVal->uid = uid;
}
static FORCE_INLINE void tqOffsetResetToLog(STqOffsetVal* pOffsetVal, int64_t ver) {
pOffsetVal->type = TMQ_OFFSET__LOG;
pOffsetVal->version = ver;

31
source/dnode/vnode/src/meta/metaQuery.c
View File

@ -887,6 +887,37 @@ const void *metaGetTableTagVal(void *pTag, int16_t type, STagVal *val) {
if (!find) {
return NULL;
}
#ifdef TAG_FILTER_DEBUG
if (IS_VAR_DATA_TYPE(val->type)) {
char* buf = taosMemoryCalloc(val->nData + 1, 1);
memcpy(buf, val->pData, val->nData);
metaDebug("metaTag table val varchar index:%d cid:%d type:%d value:%s", 1, val->cid, val->type, buf);
taosMemoryFree(buf);
} else {
double dval = 0;
GET_TYPED_DATA(dval, double, val->type, &val->i64);
metaDebug("metaTag table val number index:%d cid:%d type:%d value:%f", 1, val->cid, val->type, dval);
}
SArray* pTagVals = NULL;
tTagToValArray((STag*)pTag, &pTagVals);
for (int i = 0; i < taosArrayGetSize(pTagVals); i++) {
STagVal* pTagVal = (STagVal*)taosArrayGet(pTagVals, i);
if (IS_VAR_DATA_TYPE(pTagVal->type)) {
char* buf = taosMemoryCalloc(pTagVal->nData + 1, 1);
memcpy(buf, pTagVal->pData, pTagVal->nData);
metaDebug("metaTag table varchar index:%d cid:%d type:%d value:%s", i, pTagVal->cid, pTagVal->type, buf);
taosMemoryFree(buf);
} else {
double dval = 0;
GET_TYPED_DATA(dval, double, pTagVal->type, &pTagVal->i64);
metaDebug("metaTag table number index:%d cid:%d type:%d value:%f", i, pTagVal->cid, pTagVal->type, dval);
}
}
#endif
return val;
}

431
source/dnode/vnode/src/meta/metaSnapshot.c
View File

@ -195,3 +195,434 @@ _err:
metaError("vgId:%d, vnode snapshot meta write failed since %s", TD_VID(pMeta->pVnode), tstrerror(code));
return code;
}
typedef struct STableInfoForChildTable{
char *tableName;
SSchemaWrapper *schemaRow;
SSchemaWrapper *tagRow;
}STableInfoForChildTable;
static void destroySTableInfoForChildTable(void* data) {
STableInfoForChildTable* pData = (STableInfoForChildTable*)data;
taosMemoryFree(pData->tableName);
tDeleteSSchemaWrapper(pData->schemaRow);
tDeleteSSchemaWrapper(pData->tagRow);
}
static void MoveToSnapShotVersion(SSnapContext* ctx){
tdbTbcClose(ctx->pCur);
tdbTbcOpen(ctx->pMeta->pTbDb, &ctx->pCur, NULL);
STbDbKey key = {.version = ctx->snapVersion, .uid = INT64_MAX};
int c = 0;
tdbTbcMoveTo(ctx->pCur, &key, sizeof(key), &c);
if(c < 0){
tdbTbcMoveToPrev(ctx->pCur);
}
}
static int32_t MoveToPosition(SSnapContext* ctx, int64_t ver, int64_t uid){
tdbTbcClose(ctx->pCur);
tdbTbcOpen(ctx->pMeta->pTbDb, &ctx->pCur, NULL);
STbDbKey key = {.version = ver, .uid = uid};
int c = 0;
tdbTbcMoveTo(ctx->pCur, &key, sizeof(key), &c);
return c;
}
static void MoveToFirst(SSnapContext* ctx){
tdbTbcClose(ctx->pCur);
tdbTbcOpen(ctx->pMeta->pTbDb, &ctx->pCur, NULL);
tdbTbcMoveToFirst(ctx->pCur);
}
static void saveSuperTableInfoForChildTable(SMetaEntry *me, SHashObj *suidInfo){
STableInfoForChildTable* data = (STableInfoForChildTable*)taosHashGet(suidInfo, &me->uid, sizeof(tb_uid_t));
if(data){
return;
}
STableInfoForChildTable dataTmp = {0};
dataTmp.tableName = strdup(me->name);
dataTmp.schemaRow = tCloneSSchemaWrapper(&me->stbEntry.schemaRow);
dataTmp.tagRow = tCloneSSchemaWrapper(&me->stbEntry.schemaTag);
taosHashPut(suidInfo, &me->uid, sizeof(tb_uid_t), &dataTmp, sizeof(STableInfoForChildTable));
}
int32_t buildSnapContext(SMeta* pMeta, int64_t snapVersion, int64_t suid, int8_t subType, bool withMeta, SSnapContext** ctxRet){
SSnapContext* ctx = taosMemoryCalloc(1, sizeof(SSnapContext));
if(ctx == NULL) return -1;
*ctxRet = ctx;
ctx->pMeta = pMeta;
ctx->snapVersion = snapVersion;
ctx->suid = suid;
ctx->subType = subType;
ctx->queryMetaOrData = withMeta;
ctx->withMeta = withMeta;
ctx->idVersion = taosHashInit(100, taosGetDefaultHashFunction(TSDB_DATA_TYPE_BIGINT), true, HASH_NO_LOCK);
if(ctx->idVersion == NULL){
return -1;
}
ctx->suidInfo = taosHashInit(100, taosGetDefaultHashFunction(TSDB_DATA_TYPE_BIGINT), true, HASH_NO_LOCK);
if(ctx->suidInfo == NULL){
return -1;
}
taosHashSetFreeFp(ctx->suidInfo, destroySTableInfoForChildTable);
ctx->index = 0;
ctx->idList = taosArrayInit(100, sizeof(int64_t));
void *pKey = NULL;
void *pVal = NULL;
int vLen = 0, kLen = 0;
metaDebug("tmqsnap init snapVersion:%" PRIi64, ctx->snapVersion);
MoveToFirst(ctx);
while(1){
int32_t ret = tdbTbcNext(ctx->pCur, &pKey, &kLen, &pVal, &vLen);
if (ret < 0) break;
STbDbKey *tmp = (STbDbKey*)pKey;
if (tmp->version > ctx->snapVersion) break;
SIdInfo* idData = (SIdInfo*)taosHashGet(ctx->idVersion, &tmp->uid, sizeof(tb_uid_t));
if(idData) {
continue;
}
if (tdbTbGet(pMeta->pUidIdx, &tmp->uid, sizeof(tb_uid_t), NULL, NULL) < 0) { // check if table exist for now, need optimize later
continue;
}
SDecoder dc = {0};
SMetaEntry me = {0};
tDecoderInit(&dc, pVal, vLen);
metaDecodeEntry(&dc, &me);
if(ctx->subType == TOPIC_SUB_TYPE__TABLE){
if ((me.uid != ctx->suid && me.type == TSDB_SUPER_TABLE) ||
(me.ctbEntry.suid != ctx->suid && me.type == TSDB_CHILD_TABLE)){
tDecoderClear(&dc);
continue;
}
}
taosArrayPush(ctx->idList, &tmp->uid);
metaDebug("tmqsnap init idlist name:%s, uid:%" PRIi64, me.name, tmp->uid);
SIdInfo info = {0};
taosHashPut(ctx->idVersion, &tmp->uid, sizeof(tb_uid_t), &info, sizeof(SIdInfo));
tDecoderClear(&dc);
}
taosHashClear(ctx->idVersion);
MoveToSnapShotVersion(ctx);
while(1){
int32_t ret = tdbTbcPrev(ctx->pCur, &pKey, &kLen, &pVal, &vLen);
if (ret < 0) break;
STbDbKey *tmp = (STbDbKey*)pKey;
SIdInfo* idData = (SIdInfo*)taosHashGet(ctx->idVersion, &tmp->uid, sizeof(tb_uid_t));
if(idData){
continue;
}
SIdInfo info = {.version = tmp->version, .index = 0};
taosHashPut(ctx->idVersion, &tmp->uid, sizeof(tb_uid_t), &info, sizeof(SIdInfo));
SDecoder dc = {0};
SMetaEntry me = {0};
tDecoderInit(&dc, pVal, vLen);
metaDecodeEntry(&dc, &me);
if(ctx->subType == TOPIC_SUB_TYPE__TABLE){
if ((me.uid != ctx->suid && me.type == TSDB_SUPER_TABLE) ||
(me.ctbEntry.suid != ctx->suid && me.type == TSDB_CHILD_TABLE)){
tDecoderClear(&dc);
continue;
}
}
if ((ctx->subType == TOPIC_SUB_TYPE__DB && me.type == TSDB_SUPER_TABLE)
|| (ctx->subType == TOPIC_SUB_TYPE__TABLE && me.uid == ctx->suid)) {
saveSuperTableInfoForChildTable(&me, ctx->suidInfo);
}
tDecoderClear(&dc);
}
for(int i = 0; i < taosArrayGetSize(ctx->idList); i++){
int64_t *uid = taosArrayGet(ctx->idList, i);
SIdInfo* idData = (SIdInfo*)taosHashGet(ctx->idVersion, uid, sizeof(int64_t));
ASSERT(idData);
idData->index = i;
metaDebug("tmqsnap init idVersion uid:%" PRIi64 " version:%" PRIi64 " index:%d", *uid, idData->version, idData->index);
}
return TDB_CODE_SUCCESS;
}
int32_t destroySnapContext(SSnapContext* ctx){
tdbTbcClose(ctx->pCur);
taosArrayDestroy(ctx->idList);
taosHashCleanup(ctx->idVersion);
taosHashCleanup(ctx->suidInfo);
taosMemoryFree(ctx);
return 0;
}
static int32_t buildNormalChildTableInfo(SVCreateTbReq *req, void **pBuf, int32_t *contLen){
int32_t ret = 0;
SVCreateTbBatchReq reqs = {0};
reqs.pArray = taosArrayInit(1, sizeof(struct SVCreateTbReq));
if (NULL == reqs.pArray){
ret = -1;
goto end;
}
taosArrayPush(reqs.pArray, req);
reqs.nReqs = 1;
tEncodeSize(tEncodeSVCreateTbBatchReq, &reqs, *contLen, ret);
if(ret < 0){
ret = -1;
goto end;
}
*contLen += sizeof(SMsgHead);
*pBuf = taosMemoryMalloc(*contLen);
if (NULL == *pBuf) {
ret = -1;
goto end;
}
SEncoder coder = {0};
tEncoderInit(&coder, POINTER_SHIFT(*pBuf, sizeof(SMsgHead)), *contLen);
if (tEncodeSVCreateTbBatchReq(&coder, &reqs) < 0) {
taosMemoryFreeClear(*pBuf);
tEncoderClear(&coder);
ret = -1;
goto end;
}
tEncoderClear(&coder);
end:
taosArrayDestroy(reqs.pArray);
return ret;
}
static int32_t buildSuperTableInfo(SVCreateStbReq *req, void **pBuf, int32_t *contLen){
int32_t ret = 0;
tEncodeSize(tEncodeSVCreateStbReq, req, *contLen, ret);
if (ret < 0) {
return -1;
}
*contLen += sizeof(SMsgHead);
*pBuf = taosMemoryMalloc(*contLen);
if (NULL == *pBuf) {
return -1;
}
SEncoder encoder = {0};
tEncoderInit(&encoder, POINTER_SHIFT(*pBuf, sizeof(SMsgHead)), *contLen);
if (tEncodeSVCreateStbReq(&encoder, req) < 0) {
taosMemoryFreeClear(*pBuf);
tEncoderClear(&encoder);
return -1;
}
tEncoderClear(&encoder);
return 0;
}
int32_t setForSnapShot(SSnapContext* ctx, int64_t uid){
int c = 0;
if(uid == 0){
ctx->index = 0;
return c;
}
SIdInfo* idInfo = (SIdInfo*)taosHashGet(ctx->idVersion, &uid, sizeof(tb_uid_t));
if(!idInfo){
return -1;
}
ctx->index = idInfo->index;
return c;
}
int32_t getMetafromSnapShot(SSnapContext* ctx, void **pBuf, int32_t *contLen, int16_t *type, int64_t *uid){
int32_t ret = 0;
void *pKey = NULL;
void *pVal = NULL;
int vLen = 0, kLen = 0;
while(1){
if(ctx->index >= taosArrayGetSize(ctx->idList)){
metaDebug("tmqsnap get meta end");
ctx->index = 0;
ctx->queryMetaOrData = false; // change to get data
return 0;
}
int64_t* uidTmp = taosArrayGet(ctx->idList, ctx->index);
ctx->index++;
SIdInfo* idInfo = (SIdInfo*)taosHashGet(ctx->idVersion, uidTmp, sizeof(tb_uid_t));
ASSERT(idInfo);
*uid = *uidTmp;
ret = MoveToPosition(ctx, idInfo->version, *uidTmp);
if(ret == 0){
break;
}
metaDebug("tmqsnap get meta not exist uid:%" PRIi64 " version:%" PRIi64, *uid, idInfo->version);
}
tdbTbcGet(ctx->pCur, (const void**)&pKey, &kLen, (const void**)&pVal, &vLen);
SDecoder dc = {0};
SMetaEntry me = {0};
tDecoderInit(&dc, pVal, vLen);
metaDecodeEntry(&dc, &me);
metaDebug("tmqsnap get meta uid:%" PRIi64 " name:%s index:%d", *uid, me.name, ctx->index-1);
if ((ctx->subType == TOPIC_SUB_TYPE__DB && me.type == TSDB_SUPER_TABLE)
|| (ctx->subType == TOPIC_SUB_TYPE__TABLE && me.uid == ctx->suid)) {
SVCreateStbReq req = {0};
req.name = me.name;
req.suid = me.uid;
req.schemaRow = me.stbEntry.schemaRow;
req.schemaTag = me.stbEntry.schemaTag;
req.schemaRow.version = 1;
req.schemaTag.version = 1;
ret = buildSuperTableInfo(&req, pBuf, contLen);
*type = TDMT_VND_CREATE_STB;
} else if ((ctx->subType == TOPIC_SUB_TYPE__DB && me.type == TSDB_CHILD_TABLE)
|| (ctx->subType == TOPIC_SUB_TYPE__TABLE && me.type == TSDB_CHILD_TABLE && me.ctbEntry.suid == ctx->suid)) {
STableInfoForChildTable* data = (STableInfoForChildTable*)taosHashGet(ctx->suidInfo, &me.ctbEntry.suid, sizeof(tb_uid_t));
ASSERT(data);
SVCreateTbReq req = {0};
req.type = TSDB_CHILD_TABLE;
req.name = me.name;
req.uid = me.uid;
req.commentLen = -1;
req.ctb.suid = me.ctbEntry.suid;
req.ctb.tagNum = data->tagRow->nCols;
req.ctb.name = data->tableName;
SArray* tagName = taosArrayInit(req.ctb.tagNum, TSDB_COL_NAME_LEN);
STag* p = (STag*)me.ctbEntry.pTags;
if(tTagIsJson(p)){
if (p->nTag != 0) {
SSchema* schema = &data->tagRow->pSchema[0];
taosArrayPush(tagName, schema->name);
}
}else{
SArray* pTagVals = NULL;
if (tTagToValArray((const STag*)p, &pTagVals) != 0) {
ASSERT(0);
}
int16_t nCols = taosArrayGetSize(pTagVals);
for (int j = 0; j < nCols; ++j) {
STagVal* pTagVal = (STagVal*)taosArrayGet(pTagVals, j);
for(int i = 0; i < data->tagRow->nCols; i++){
SSchema *schema = &data->tagRow->pSchema[i];
if(schema->colId == pTagVal->cid){
taosArrayPush(tagName, schema->name);
}
}
}
}
// SIdInfo* sidInfo = (SIdInfo*)taosHashGet(ctx->idVersion, &me.ctbEntry.suid, sizeof(tb_uid_t));
// if(sidInfo->version >= idInfo->version){
// // need parse tag
// STag* p = (STag*)me.ctbEntry.pTags;
// SArray* pTagVals = NULL;
// if (tTagToValArray((const STag*)p, &pTagVals) != 0) {
// }
//
// int16_t nCols = taosArrayGetSize(pTagVals);
// for (int j = 0; j < nCols; ++j) {
// STagVal* pTagVal = (STagVal*)taosArrayGet(pTagVals, j);
// }
// }else{
req.ctb.pTag = me.ctbEntry.pTags;
// }
req.ctb.tagName = tagName;
ret = buildNormalChildTableInfo(&req, pBuf, contLen);
*type = TDMT_VND_CREATE_TABLE;
taosArrayDestroy(tagName);
} else if(ctx->subType == TOPIC_SUB_TYPE__DB){
SVCreateTbReq req = {0};
req.type = TSDB_NORMAL_TABLE;
req.name = me.name;
req.uid = me.uid;
req.commentLen = -1;
req.ntb.schemaRow = me.ntbEntry.schemaRow;
ret = buildNormalChildTableInfo(&req, pBuf, contLen);
*type = TDMT_VND_CREATE_TABLE;
} else{
ASSERT(0);
}
tDecoderClear(&dc);
return ret;
}
SMetaTableInfo getUidfromSnapShot(SSnapContext* ctx){
SMetaTableInfo result = {0};
void *pKey = NULL;
void *pVal = NULL;
int vLen, kLen;
while(1){
if(ctx->index >= taosArrayGetSize(ctx->idList)){
metaDebug("tmqsnap get uid info end");
return result;
}
int64_t* uidTmp = taosArrayGet(ctx->idList, ctx->index);
ctx->index++;
SIdInfo* idInfo = (SIdInfo*)taosHashGet(ctx->idVersion, uidTmp, sizeof(tb_uid_t));
ASSERT(idInfo);
int32_t ret = MoveToPosition(ctx, idInfo->version, *uidTmp);
if(ret != 0) {
metaDebug("tmqsnap getUidfromSnapShot not exist uid:%" PRIi64 " version:%" PRIi64, *uidTmp, idInfo->version);
continue;
}
tdbTbcGet(ctx->pCur, (const void**)&pKey, &kLen, (const void**)&pVal, &vLen);
SDecoder dc = {0};
SMetaEntry me = {0};
tDecoderInit(&dc, pVal, vLen);
metaDecodeEntry(&dc, &me);
metaDebug("tmqsnap get uid info uid:%" PRIi64 " name:%s index:%d", me.uid, me.name, ctx->index-1);
if (ctx->subType == TOPIC_SUB_TYPE__DB && me.type == TSDB_CHILD_TABLE){
STableInfoForChildTable* data = (STableInfoForChildTable*)taosHashGet(ctx->suidInfo, &me.ctbEntry.suid, sizeof(tb_uid_t));
result.uid = me.uid;
result.suid = me.ctbEntry.suid;
result.schema = tCloneSSchemaWrapper(data->schemaRow);
strcpy(result.tbName, me.name);
tDecoderClear(&dc);
break;
} else if (ctx->subType == TOPIC_SUB_TYPE__DB && me.type == TSDB_NORMAL_TABLE) {
result.uid = me.uid;
result.suid = 0;
strcpy(result.tbName, me.name);
result.schema = tCloneSSchemaWrapper(&me.ntbEntry.schemaRow);
tDecoderClear(&dc);
break;
} else if(ctx->subType == TOPIC_SUB_TYPE__TABLE && me.type == TSDB_CHILD_TABLE && me.ctbEntry.suid == ctx->suid) {
STableInfoForChildTable* data = (STableInfoForChildTable*)taosHashGet(ctx->suidInfo, &me.ctbEntry.suid, sizeof(tb_uid_t));
result.uid = me.uid;
result.suid = me.ctbEntry.suid;
strcpy(result.tbName, me.name);
result.schema = tCloneSSchemaWrapper(data->schemaRow);
tDecoderClear(&dc);
break;
} else{
metaDebug("tmqsnap get uid continue");
tDecoderClear(&dc);
continue;
}
}
return result;
}

24
source/dnode/vnode/src/meta/metaTable.c
View File

@ -99,6 +99,7 @@ static int metaSaveJsonVarToIdx(SMeta *pMeta, const SMetaEntry *pCtbEntry, const
memcpy(val, (uint16_t *)&len, VARSTR_HEADER_SIZE);
type = TSDB_DATA_TYPE_VARCHAR;
term = indexTermCreate(suid, ADD_VALUE, type, key, nKey, val, len);
taosMemoryFree(val);
} else if (pTagVal->nData == 0) {
term = indexTermCreate(suid, ADD_VALUE, TSDB_DATA_TYPE_VARCHAR, key, nKey, pTagVal->pData, 0);
}
@ -115,6 +116,7 @@ static int metaSaveJsonVarToIdx(SMeta *pMeta, const SMetaEntry *pCtbEntry, const
indexMultiTermAdd(terms, term);
}
}
taosArrayDestroy(pTagVals);
indexJsonPut(pMeta->pTagIvtIdx, terms, tuid);
indexMultiTermDestroy(terms);
#endif
@ -413,6 +415,25 @@ int metaCreateTable(SMeta *pMeta, int64_t version, SVCreateTbReq *pReq, STableMe
me.ctbEntry.suid = pReq->ctb.suid;
me.ctbEntry.pTags = pReq->ctb.pTag;
#ifdef TAG_FILTER_DEBUG
SArray* pTagVals = NULL;
int32_t code = tTagToValArray((STag*)pReq->ctb.pTag, &pTagVals);
for (int i = 0; i < taosArrayGetSize(pTagVals); i++) {
STagVal* pTagVal = (STagVal*)taosArrayGet(pTagVals, i);
if (IS_VAR_DATA_TYPE(pTagVal->type)) {
char* buf = taosMemoryCalloc(pTagVal->nData + 1, 1);
memcpy(buf, pTagVal->pData, pTagVal->nData);
metaDebug("metaTag table:%s varchar index:%d cid:%d type:%d value:%s", pReq->name, i, pTagVal->cid, pTagVal->type, buf);
taosMemoryFree(buf);
} else {
double val = 0;
GET_TYPED_DATA(val, double, pTagVal->type, &pTagVal->i64);
metaDebug("metaTag table:%s number index:%d cid:%d type:%d value:%f", pReq->name, i, pTagVal->cid, pTagVal->type, val);
}
}
#endif
++pMeta->pVnode->config.vndStats.numOfCTables;
} else {
me.ntbEntry.ctime = pReq->ctime;
@ -532,6 +553,9 @@ static int metaDropTableByUid(SMeta *pMeta, tb_uid_t uid, int *type) {
SDecoder dc = {0};
rc = tdbTbGet(pMeta->pUidIdx, &uid, sizeof(uid), &pData, &nData);
if (rc < 0) {
return -1;
}
int64_t version = ((SUidIdxVal *)pData)[0].version;
tdbTbGet(pMeta->pTbDb, &(STbDbKey){.version = version, .uid = uid}, sizeof(STbDbKey), &pData, &nData);

124
source/dnode/vnode/src/tq/tq.c
View File

@ -100,7 +100,13 @@ void tqClose(STQ* pTq) {
}
int32_t tqSendMetaPollRsp(STQ* pTq, const SRpcMsg* pMsg, const SMqPollReq* pReq, const SMqMetaRsp* pRsp) {
int32_t tlen = sizeof(SMqRspHead) + tEncodeSMqMetaRsp(NULL, pRsp);
int32_t len = 0;
int32_t code = 0;
tEncodeSize(tEncodeSMqMetaRsp, pRsp, len, code);
if (code < 0) {
return -1;
}
int32_t tlen = sizeof(SMqRspHead) + len;
void* buf = rpcMallocCont(tlen);
if (buf == NULL) {
return -1;
@ -111,7 +117,11 @@ int32_t tqSendMetaPollRsp(STQ* pTq, const SRpcMsg* pMsg, const SMqPollReq* pReq,
((SMqRspHead*)buf)->consumerId = pReq->consumerId;
void* abuf = POINTER_SHIFT(buf, sizeof(SMqRspHead));
tEncodeSMqMetaRsp(&abuf, pRsp);
SEncoder encoder = {0};
tEncoderInit(&encoder, abuf, len);
tEncodeSMqMetaRsp(&encoder, pRsp);
tEncoderClear(&encoder);
SRpcMsg resp = {
.info = pMsg->info,
@ -121,9 +131,8 @@ int32_t tqSendMetaPollRsp(STQ* pTq, const SRpcMsg* pMsg, const SMqPollReq* pReq,
};
tmsgSendRsp(&resp);
tqDebug("vgId:%d, from consumer:%" PRId64 ", (epoch %d) send rsp, res msg type %d, reqOffset:%" PRId64
", rspOffset:%" PRId64,
TD_VID(pTq->pVnode), pReq->consumerId, pReq->epoch, pRsp->resMsgType, pRsp->reqOffset, pRsp->rspOffset);
tqDebug("vgId:%d, from consumer:%" PRId64 ", (epoch %d) send rsp, res msg type %d, offset type:%d",
TD_VID(pTq->pVnode), pReq->consumerId, pReq->epoch, pRsp->resMsgType, pRsp->rspOffset.type);
return 0;
}
@ -202,7 +211,7 @@ int32_t tqProcessOffsetCommitReq(STQ* pTq, int64_t version, char* msg, int32_t m
}
tDecoderClear(&decoder);
if (offset.val.type == TMQ_OFFSET__SNAPSHOT_DATA) {
if (offset.val.type == TMQ_OFFSET__SNAPSHOT_DATA || offset.val.type == TMQ_OFFSET__SNAPSHOT_META) {
tqDebug("receive offset commit msg to %s on vgId:%d, offset(type:snapshot) uid:%" PRId64 ", ts:%" PRId64,
offset.subKey, TD_VID(pTq->pVnode), offset.val.uid, offset.val.ts);
} else if (offset.val.type == TMQ_OFFSET__LOG) {
@ -297,7 +306,6 @@ static int32_t tqInitDataRsp(SMqDataRsp* pRsp, const SMqPollReq* pReq, int8_t su
int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
SMqPollReq* pReq = pMsg->pCont;
int64_t consumerId = pReq->consumerId;
int64_t timeout = pReq->timeout;
int32_t reqEpoch = pReq->epoch;
int32_t code = 0;
STqOffsetVal reqOffset = pReq->reqOffset;
@ -349,12 +357,11 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
TD_VID(pTq->pVnode), formatBuf);
} else {
if (reqOffset.type == TMQ_OFFSET__RESET_EARLIEAST) {
if (pReq->useSnapshot && pHandle->execHandle.subType == TOPIC_SUB_TYPE__COLUMN) {
if (!pHandle->fetchMeta) {
tqOffsetResetToData(&fetchOffsetNew, 0, 0);
if (pReq->useSnapshot){
if (pHandle->fetchMeta){
tqOffsetResetToMeta(&fetchOffsetNew, 0);
} else {
// reset to meta
ASSERT(0);
tqOffsetResetToData(&fetchOffsetNew, 0, 0);
}
} else {
tqOffsetResetToLog(&fetchOffsetNew, walGetFirstVer(pTq->pVnode->pWal));
@ -378,28 +385,34 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
}
}
// 3.query
if (pHandle->execHandle.subType == TOPIC_SUB_TYPE__COLUMN) {
/*if (fetchOffsetNew.type == TMQ_OFFSET__LOG) {*/
/*fetchOffsetNew.version++;*/
/*}*/
if (tqScan(pTq, pHandle, &dataRsp, &fetchOffsetNew) < 0) {
ASSERT(0);
code = -1;
if(pHandle->execHandle.subType == TOPIC_SUB_TYPE__COLUMN || fetchOffsetNew.type != TMQ_OFFSET__LOG){
SMqMetaRsp metaRsp = {0};
tqScan(pTq, pHandle, &dataRsp, &metaRsp, &fetchOffsetNew);
if(metaRsp.metaRspLen > 0){
if (tqSendMetaPollRsp(pTq, pMsg, pReq, &metaRsp) < 0) {
code = -1;
}
tqDebug("tmq poll: consumer %ld, subkey %s, vg %d, send meta offset type:%d,uid:%ld,version:%ld", consumerId, pHandle->subKey,
TD_VID(pTq->pVnode), metaRsp.rspOffset.type, metaRsp.rspOffset.uid, metaRsp.rspOffset.version);
taosMemoryFree(metaRsp.metaRsp);
goto OVER;
}
if (dataRsp.blockNum == 0) {
// TODO add to async task pool
/*dataRsp.rspOffset.version--;*/
if (dataRsp.blockNum > 0){
if (tqSendDataRsp(pTq, pMsg, pReq, &dataRsp) < 0) {
code = -1;
}
goto OVER;
}else{
fetchOffsetNew = dataRsp.rspOffset;
}
if (tqSendDataRsp(pTq, pMsg, pReq, &dataRsp) < 0) {
code = -1;
}
goto OVER;
tqDebug("tmq poll: consumer %ld, subkey %s, vg %d, send data blockNum:%d, offset type:%d,uid:%ld,version:%ld", consumerId, pHandle->subKey,
TD_VID(pTq->pVnode), dataRsp.blockNum, dataRsp.rspOffset.type, dataRsp.rspOffset.uid, dataRsp.rspOffset.version);
}
if (pHandle->execHandle.subType != TOPIC_SUB_TYPE__COLUMN) {
ASSERT(fetchOffsetNew.type == TMQ_OFFSET__LOG);
if (pHandle->execHandle.subType != TOPIC_SUB_TYPE__COLUMN && fetchOffsetNew.type == TMQ_OFFSET__LOG) {
int64_t fetchVer = fetchOffsetNew.version + 1;
pCkHead = taosMemoryMalloc(sizeof(SWalCkHead) + 2048);
if (pCkHead == NULL) {
@ -413,7 +426,7 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
consumerEpoch = atomic_load_32(&pHandle->epoch);
if (consumerEpoch > reqEpoch) {
tqWarn("tmq poll: consumer %" PRId64 " (epoch %d), subkey %s, vg %d offset %" PRId64
", found new consumer epoch %d, discard req epoch %d",
", found new consumer epoch %d, discard req epoch %d",
consumerId, pReq->epoch, pHandle->subKey, TD_VID(pTq->pVnode), fetchVer, consumerEpoch, reqEpoch);
break;
}
@ -422,7 +435,6 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
// TODO add push mgr
tqOffsetResetToLog(&dataRsp.rspOffset, fetchVer);
ASSERT(dataRsp.rspOffset.version >= dataRsp.reqOffset.version);
if (tqSendDataRsp(pTq, pMsg, pReq, &dataRsp) < 0) {
code = -1;
}
@ -444,8 +456,6 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
// TODO continue scan until meeting batch requirement
if (dataRsp.blockNum > 0 /* threshold */) {
tqOffsetResetToLog(&dataRsp.rspOffset, fetchVer);
ASSERT(dataRsp.rspOffset.version >= dataRsp.reqOffset.version);
if (tqSendDataRsp(pTq, pMsg, pReq, &dataRsp) < 0) {
code = -1;
}
@ -459,11 +469,7 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
ASSERT(IS_META_MSG(pHead->msgType));
tqDebug("fetch meta msg, ver:%" PRId64 ", type:%d", pHead->version, pHead->msgType);
SMqMetaRsp metaRsp = {0};
/*metaRsp.reqOffset = pReq->reqOffset.version;*/
metaRsp.rspOffset = fetchVer;
/*metaRsp.rspOffsetNew.version = fetchVer;*/
tqOffsetResetToLog(&metaRsp.reqOffsetNew, pReq->reqOffset.version);
tqOffsetResetToLog(&metaRsp.rspOffsetNew, fetchVer);
tqOffsetResetToLog(&metaRsp.rspOffset, fetchVer);
metaRsp.resMsgType = pHead->msgType;
metaRsp.metaRspLen = pHead->bodyLen;
metaRsp.metaRsp = pHead->body;
@ -477,6 +483,11 @@ int32_t tqProcessPollReq(STQ* pTq, SRpcMsg* pMsg) {
}
}
// send empty to client
if (tqSendDataRsp(pTq, pMsg, pReq, &dataRsp) < 0) {
code = -1;
}
OVER:
if (pCkHead) taosMemoryFree(pCkHead);
// TODO wrap in destroy func
@ -561,6 +572,7 @@ int32_t tqProcessVgChangeReq(STQ* pTq, int64_t version, char* msg, int32_t msgLe
pHandle->execHandle.subType = req.subType;
pHandle->fetchMeta = req.withMeta;
// TODO version should be assigned and refed during preprocess
SWalRef* pRef = walRefCommittedVer(pTq->pVnode->pWal);
if (pRef == NULL) {
@ -570,36 +582,42 @@ int32_t tqProcessVgChangeReq(STQ* pTq, int64_t version, char* msg, int32_t msgLe
int64_t ver = pRef->refVer;
pHandle->pRef = pRef;
SReadHandle handle = {
.meta = pTq->pVnode->pMeta,
.vnode = pTq->pVnode,
.initTableReader = true,
.initTqReader = true,
.version = ver,
};
pHandle->snapshotVer = ver;
if (pHandle->execHandle.subType == TOPIC_SUB_TYPE__COLUMN) {
pHandle->execHandle.execCol.qmsg = req.qmsg;
pHandle->snapshotVer = ver;
req.qmsg = NULL;
SReadHandle handle = {
.meta = pTq->pVnode->pMeta,
.vnode = pTq->pVnode,
.initTableReader = true,
.initTqReader = true,
.version = ver,
};
pHandle->execHandle.execCol.task =
qCreateQueueExecTaskInfo(pHandle->execHandle.execCol.qmsg, &handle, &pHandle->execHandle.numOfCols,
pHandle->execHandle.task =
qCreateQueueExecTaskInfo(pHandle->execHandle.execCol.qmsg, &handle, NULL,
&pHandle->execHandle.pSchemaWrapper);
ASSERT(pHandle->execHandle.execCol.task);
ASSERT(pHandle->execHandle.task);
void* scanner = NULL;
qExtractStreamScanner(pHandle->execHandle.execCol.task, &scanner);
qExtractStreamScanner(pHandle->execHandle.task, &scanner);
ASSERT(scanner);
pHandle->execHandle.pExecReader = qExtractReaderFromStreamScanner(scanner);
ASSERT(pHandle->execHandle.pExecReader);
} else if (pHandle->execHandle.subType == TOPIC_SUB_TYPE__DB) {
pHandle->pWalReader = walOpenReader(pTq->pVnode->pWal, NULL);
pHandle->execHandle.pExecReader = tqOpenReader(pTq->pVnode);
pHandle->execHandle.execDb.pFilterOutTbUid =
taosHashInit(64, taosGetDefaultHashFunction(TSDB_DATA_TYPE_BIGINT), false, HASH_NO_LOCK);
buildSnapContext(handle.meta, handle.version, 0, pHandle->execHandle.subType, pHandle->fetchMeta, (SSnapContext **)(&handle.sContext));
pHandle->execHandle.task =
qCreateQueueExecTaskInfo(NULL, &handle, NULL, NULL);
} else if (pHandle->execHandle.subType == TOPIC_SUB_TYPE__TABLE) {
pHandle->pWalReader = walOpenReader(pTq->pVnode->pWal, NULL);
pHandle->execHandle.execTb.suid = req.suid;
SArray* tbUidList = taosArrayInit(0, sizeof(int64_t));
vnodeGetCtbIdList(pTq->pVnode, req.suid, tbUidList);
tqDebug("vgId:%d, tq try to get all ctb, suid:%" PRId64, pTq->pVnode->config.vgId, req.suid);
@ -610,6 +628,10 @@ int32_t tqProcessVgChangeReq(STQ* pTq, int64_t version, char* msg, int32_t msgLe
pHandle->execHandle.pExecReader = tqOpenReader(pTq->pVnode);
tqReaderSetTbUidList(pHandle->execHandle.pExecReader, tbUidList);
taosArrayDestroy(tbUidList);
buildSnapContext(handle.meta, handle.version, req.suid, pHandle->execHandle.subType, pHandle->fetchMeta, (SSnapContext **)(&handle.sContext));
pHandle->execHandle.task =
qCreateQueueExecTaskInfo(NULL, &handle, NULL, NULL);
}
taosHashPut(pTq->pHandle, req.subKey, strlen(req.subKey), pHandle, sizeof(STqHandle));
tqDebug("try to persist handle %s consumer %" PRId64, req.subKey, pHandle->consumerId);

92
source/dnode/vnode/src/tq/tqExec.c
View File

@ -60,18 +60,18 @@ static int32_t tqAddTbNameToRsp(const STQ* pTq, int64_t uid, SMqDataRsp* pRsp) {
return 0;
}
int64_t tqScan(STQ* pTq, const STqHandle* pHandle, SMqDataRsp* pRsp, STqOffsetVal* pOffset) {
int64_t tqScan(STQ* pTq, const STqHandle* pHandle, SMqDataRsp* pRsp, SMqMetaRsp* pMetaRsp, STqOffsetVal* pOffset) {
const STqExecHandle* pExec = &pHandle->execHandle;
qTaskInfo_t task = pExec->execCol.task;
qTaskInfo_t task = pExec->task;
if (qStreamPrepareScan(task, pOffset) < 0) {
if (qStreamPrepareScan(task, pOffset, pHandle->execHandle.subType) < 0) {
tqDebug("prepare scan failed, return");
if (pOffset->type == TMQ_OFFSET__LOG) {
pRsp->rspOffset = *pOffset;
return 0;
} else {
tqOffsetResetToLog(pOffset, pHandle->snapshotVer);
if (qStreamPrepareScan(task, pOffset) < 0) {
if (qStreamPrepareScan(task, pOffset, pHandle->execHandle.subType) < 0) {
tqDebug("prepare scan failed, return");
pRsp->rspOffset = *pOffset;
return 0;
@ -83,24 +83,34 @@ int64_t tqScan(STQ* pTq, const STqHandle* pHandle, SMqDataRsp* pRsp, STqOffsetVa
while (1) {
SSDataBlock* pDataBlock = NULL;
uint64_t ts = 0;
tqDebug("task start to execute");
tqDebug("tmqsnap task start to execute");
if (qExecTask(task, &pDataBlock, &ts) < 0) {
ASSERT(0);
}
tqDebug("task execute end, get %p", pDataBlock);
tqDebug("tmqsnap task execute end, get %p", pDataBlock);
if (pDataBlock != NULL) {
if (pRsp->withTbName) {
int64_t uid = 0;
if (pOffset->type == TMQ_OFFSET__LOG) {
int64_t uid = pExec->pExecReader->msgIter.uid;
uid = pExec->pExecReader->msgIter.uid;
if (tqAddTbNameToRsp(pTq, uid, pRsp) < 0) {
continue;
}
} else {
pRsp->withTbName = 0;
char* tbName = strdup(qExtractTbnameFromTask(task));
taosArrayPush(pRsp->blockTbName, &tbName);
}
}
tqAddBlockDataToRsp(pDataBlock, pRsp, pExec->numOfCols);
if(pRsp->withSchema){
if (pOffset->type == TMQ_OFFSET__LOG) {
tqAddBlockSchemaToRsp(pExec, pRsp);
}else{
SSchemaWrapper* pSW = tCloneSSchemaWrapper(qExtractSchemaFromTask(task));
taosArrayPush(pRsp->blockSchema, &pSW);
}
}
tqAddBlockDataToRsp(pDataBlock, pRsp, taosArrayGetSize(pDataBlock->pDataBlock));
pRsp->blockNum++;
if (pOffset->type == TMQ_OFFSET__LOG) {
continue;
@ -110,39 +120,51 @@ int64_t tqScan(STQ* pTq, const STqHandle* pHandle, SMqDataRsp* pRsp, STqOffsetVa
}
}
if (pRsp->blockNum == 0 && pOffset->type == TMQ_OFFSET__SNAPSHOT_DATA) {
tqDebug("vgId: %d, tsdb consume over, switch to wal, ver %" PRId64, TD_VID(pTq->pVnode),
pHandle->snapshotVer + 1);
tqOffsetResetToLog(pOffset, pHandle->snapshotVer);
qStreamPrepareScan(task, pOffset);
continue;
}
void* meta = qStreamExtractMetaMsg(task);
if (meta != NULL) {
// tq add meta to rsp
}
if (qStreamExtractOffset(task, &pRsp->rspOffset) < 0) {
ASSERT(0);
}
ASSERT(pRsp->rspOffset.type != 0);
#if 0
if (pRsp->reqOffset.type == TMQ_OFFSET__LOG) {
if (pRsp->blockNum > 0) {
ASSERT(pRsp->rspOffset.version > pRsp->reqOffset.version);
} else {
ASSERT(pRsp->rspOffset.version >= pRsp->reqOffset.version);
if(pHandle->execHandle.subType == TOPIC_SUB_TYPE__COLUMN){
if (pRsp->blockNum == 0 && pOffset->type == TMQ_OFFSET__SNAPSHOT_DATA) {
tqDebug("vgId: %d, tsdb consume over, switch to wal, ver %" PRId64, TD_VID(pTq->pVnode),
pHandle->snapshotVer + 1);
tqOffsetResetToLog(pOffset, pHandle->snapshotVer);
qStreamPrepareScan(task, pOffset, pHandle->execHandle.subType);
continue;
}
}else{
if (pDataBlock == NULL && pOffset->type == TMQ_OFFSET__SNAPSHOT_DATA){
if(qStreamExtractPrepareUid(task) != 0){
continue;
}
tqDebug("tmqsnap vgId: %d, tsdb consume over, switch to wal, ver %" PRId64, TD_VID(pTq->pVnode),
pHandle->snapshotVer + 1);
break;
}
if (pRsp->blockNum > 0){
tqDebug("tmqsnap task exec exited, get data");
break;
}
SMqMetaRsp* tmp = qStreamExtractMetaMsg(task);
if(tmp->rspOffset.type == TMQ_OFFSET__SNAPSHOT_DATA){
tqOffsetResetToData(pOffset, tmp->rspOffset.uid, tmp->rspOffset.ts);
qStreamPrepareScan(task, pOffset, pHandle->execHandle.subType);
tmp->rspOffset.type = TMQ_OFFSET__SNAPSHOT_META;
tqDebug("tmqsnap task exec change to get data");
continue;
}
*pMetaRsp = *tmp;
tqDebug("tmqsnap task exec exited, get meta");
}
#endif
tqDebug("task exec exited");
break;
}
if (qStreamExtractOffset(task, &pRsp->rspOffset) < 0) {
ASSERT(0);
}
ASSERT(pRsp->rspOffset.type != 0);
return 0;
}

31
source/dnode/vnode/src/tq/tqMeta.c
View File

@ -249,27 +249,34 @@ int32_t tqMetaRestoreHandle(STQ* pTq) {
}
walRefVer(handle.pRef, handle.snapshotVer);
if (handle.execHandle.subType == TOPIC_SUB_TYPE__COLUMN) {
SReadHandle reader = {
.meta = pTq->pVnode->pMeta,
.vnode = pTq->pVnode,
.initTableReader = true,
.initTqReader = true,
.version = handle.snapshotVer,
};
SReadHandle reader = {
.meta = pTq->pVnode->pMeta,
.vnode = pTq->pVnode,
.initTableReader = true,
.initTqReader = true,
.version = handle.snapshotVer,
};
handle.execHandle.execCol.task = qCreateQueueExecTaskInfo(
handle.execHandle.execCol.qmsg, &reader, &handle.execHandle.numOfCols, &handle.execHandle.pSchemaWrapper);
ASSERT(handle.execHandle.execCol.task);
if (handle.execHandle.subType == TOPIC_SUB_TYPE__COLUMN) {
handle.execHandle.task = qCreateQueueExecTaskInfo(
handle.execHandle.execCol.qmsg, &reader, NULL, &handle.execHandle.pSchemaWrapper);
ASSERT(handle.execHandle.task);
void* scanner = NULL;
qExtractStreamScanner(handle.execHandle.execCol.task, &scanner);
qExtractStreamScanner(handle.execHandle.task, &scanner);
ASSERT(scanner);
handle.execHandle.pExecReader = qExtractReaderFromStreamScanner(scanner);
ASSERT(handle.execHandle.pExecReader);
} else {
handle.pWalReader = walOpenReader(pTq->pVnode->pWal, NULL);
handle.execHandle.execDb.pFilterOutTbUid =
taosHashInit(64, taosGetDefaultHashFunction(TSDB_DATA_TYPE_BIGINT), false, HASH_NO_LOCK);
// handle.execHandle.pExecReader = tqOpenReader(pTq->pVnode);
buildSnapContext(reader.meta, reader.version, 0, handle.execHandle.subType, handle.fetchMeta, (SSnapContext **)(&reader.sContext));
handle.execHandle.task =
qCreateQueueExecTaskInfo(NULL, &reader, NULL, NULL);
}
tqDebug("tq restore %s consumer %" PRId64 " vgId:%d", handle.subKey, handle.consumerId, TD_VID(pTq->pVnode));
taosHashPut(pTq->pHandle, pKey, kLen, &handle, sizeof(STqHandle));

4
source/dnode/vnode/src/tq/tqRead.c
View File

@ -68,7 +68,7 @@ int64_t tqFetchLog(STQ* pTq, STqHandle* pHandle, int64_t* fetchOffset, SWalCkHea
offset++;
}
}
END:
END:
taosThreadMutexUnlock(&pHandle->pWalReader->mutex);
return code;
}
@ -398,7 +398,7 @@ int32_t tqUpdateTbUidList(STQ* pTq, const SArray* tbUidList, bool isAdd) {
if (pIter == NULL) break;
STqHandle* pExec = (STqHandle*)pIter;
if (pExec->execHandle.subType == TOPIC_SUB_TYPE__COLUMN) {
int32_t code = qUpdateQualifiedTableId(pExec->execHandle.execCol.task, tbUidList, isAdd);
int32_t code = qUpdateQualifiedTableId(pExec->execHandle.task, tbUidList, isAdd);
ASSERT(code == 0);
} else if (pExec->execHandle.subType == TOPIC_SUB_TYPE__DB) {
if (!isAdd) {

2
source/dnode/vnode/src/tsdb/tsdbCache.c
View File

@ -476,7 +476,7 @@ static int32_t getNextRowFromFSLast(void *iter, TSDBROW **ppRow) {
if (code) goto _err;
if (!state->aBlockL) {
state->aBlockL = taosArrayInit(0, sizeof(SBlockIdx));
state->aBlockL = taosArrayInit(0, sizeof(SBlockL));
} else {
taosArrayClear(state->aBlockL);
}

80
source/dnode/vnode/src/tsdb/tsdbCacheRead.c
View File

@ -18,7 +18,7 @@
#include "tcommon.h"
#include "tsdb.h"
typedef struct SLastrowReader {
typedef struct SCacheRowsReader {
SVnode* pVnode;
STSchema* pSchema;
uint64_t uid;
@ -27,9 +27,9 @@ typedef struct SLastrowReader {
int32_t type;
int32_t tableIndex; // currently returned result tables
SArray* pTableList; // table id list
} SLastrowReader;
} SCacheRowsReader;
static void saveOneRow(STSRow* pRow, SSDataBlock* pBlock, SLastrowReader* pReader, const int32_t* slotIds) {
static void saveOneRow(STSRow* pRow, SSDataBlock* pBlock, SCacheRowsReader* pReader, const int32_t* slotIds) {
ASSERT(pReader->numOfCols <= taosArrayGetSize(pBlock->pDataBlock));
int32_t numOfRows = pBlock->info.rows;
@ -61,8 +61,10 @@ static void saveOneRow(STSRow* pRow, SSDataBlock* pBlock, SLastrowReader* pReade
pBlock->info.rows += 1;
}
int32_t tsdbLastRowReaderOpen(void* pVnode, int32_t type, SArray* pTableIdList, int32_t numOfCols, void** pReader) {
SLastrowReader* p = taosMemoryCalloc(1, sizeof(SLastrowReader));
int32_t tsdbCacherowsReaderOpen(void* pVnode, int32_t type, SArray* pTableIdList, int32_t numOfCols, void** pReader) {
*pReader = NULL;
SCacheRowsReader* p = taosMemoryCalloc(1, sizeof(SCacheRowsReader));
if (p == NULL) {
return TSDB_CODE_OUT_OF_MEMORY;
}
@ -81,9 +83,17 @@ int32_t tsdbLastRowReaderOpen(void* pVnode, int32_t type, SArray* pTableIdList,
p->pTableList = pTableIdList;
p->transferBuf = taosMemoryCalloc(p->pSchema->numOfCols, POINTER_BYTES);
if (p->transferBuf == NULL) {
return TSDB_CODE_OUT_OF_MEMORY;
}
for (int32_t i = 0; i < p->pSchema->numOfCols; ++i) {
if (IS_VAR_DATA_TYPE(p->pSchema->columns[i].type)) {
p->transferBuf[i] = taosMemoryMalloc(p->pSchema->columns[i].bytes);
if (p->transferBuf[i] == NULL) {
tsdbCacherowsReaderClose(p);
return TSDB_CODE_OUT_OF_MEMORY;
}
}
}
@ -91,8 +101,8 @@ int32_t tsdbLastRowReaderOpen(void* pVnode, int32_t type, SArray* pTableIdList,
return TSDB_CODE_SUCCESS;
}
int32_t tsdbLastrowReaderClose(void* pReader) {
SLastrowReader* p = pReader;
int32_t tsdbCacherowsReaderClose(void* pReader) {
SCacheRowsReader* p = pReader;
if (p->pSchema != NULL) {
for (int32_t i = 0; i < p->pSchema->numOfCols; ++i) {
@ -107,28 +117,56 @@ int32_t tsdbLastrowReaderClose(void* pReader) {
return TSDB_CODE_SUCCESS;
}
int32_t tsdbRetrieveLastRow(void* pReader, SSDataBlock* pResBlock, const int32_t* slotIds, SArray* pTableUidList) {
static int32_t doExtractCacheRow(SCacheRowsReader* pr, SLRUCache* lruCache, uint64_t uid, STSRow** pRow, LRUHandle** h) {
int32_t code = TSDB_CODE_SUCCESS;
if ((pr->type & CACHESCAN_RETRIEVE_LAST_ROW) == CACHESCAN_RETRIEVE_LAST_ROW) {
code = tsdbCacheGetLastrowH(lruCache, uid, pr->pVnode->pTsdb, h);
if (code != TSDB_CODE_SUCCESS) {
return code;
}
// no data in the table of Uid
if (*h != NULL) {
*pRow = (STSRow*)taosLRUCacheValue(lruCache, *h);
}
} else {
code = tsdbCacheGetLastH(lruCache, uid, pr->pVnode->pTsdb, h);
if (code != TSDB_CODE_SUCCESS) {
return code;
}
// no data in the table of Uid
if (*h != NULL) {
SArray* pLast = (SArray*)taosLRUCacheValue(lruCache, *h);
tsdbCacheLastArray2Row(pLast, pRow, pr->pSchema);
}
}
return code;
}
int32_t tsdbRetrieveCacheRows(void* pReader, SSDataBlock* pResBlock, const int32_t* slotIds, SArray* pTableUidList) {
if (pReader == NULL || pResBlock == NULL) {
return TSDB_CODE_INVALID_PARA;
}
SLastrowReader* pr = pReader;
SCacheRowsReader* pr = pReader;
int32_t code = TSDB_CODE_SUCCESS;
SLRUCache* lruCache = pr->pVnode->pTsdb->lruCache;
LRUHandle* h = NULL;
STSRow* pRow = NULL;
size_t numOfTables = taosArrayGetSize(pr->pTableList);
// retrieve the only one last row of all tables in the uid list.
if (pr->type == LASTROW_RETRIEVE_TYPE_SINGLE) {
if ((pr->type & CACHESCAN_RETRIEVE_TYPE_SINGLE) == CACHESCAN_RETRIEVE_TYPE_SINGLE) {
int64_t lastKey = INT64_MIN;
bool internalResult = false;
for (int32_t i = 0; i < numOfTables; ++i) {
STableKeyInfo* pKeyInfo = taosArrayGet(pr->pTableList, i);
int32_t code = tsdbCacheGetLastrowH(lruCache, pKeyInfo->uid, pr->pVnode->pTsdb, &h);
// int32_t code = tsdbCacheGetLastH(lruCache, pKeyInfo->uid, pr->pVnode->pTsdb, &h);
if (code != TSDB_CODE_SUCCESS) {
code = doExtractCacheRow(pr, lruCache, pKeyInfo->uid, &pRow, &h);
if (code != TSDB_CODE_SUCCESS) {
return code;
}
@ -136,9 +174,6 @@ int32_t tsdbRetrieveLastRow(void* pReader, SSDataBlock* pResBlock, const int32_t
continue;
}
pRow = (STSRow*)taosLRUCacheValue(lruCache, h);
// SArray* pLast = (SArray*)taosLRUCacheValue(lruCache, h);
// tsdbCacheLastArray2Row(pLast, &pRow, pr->pSchema);
if (pRow->ts > lastKey) {
// Set result row into the same rowIndex repeatly, so we need to check if the internal result row has already
// appended or not.
@ -155,25 +190,18 @@ int32_t tsdbRetrieveLastRow(void* pReader, SSDataBlock* pResBlock, const int32_t
tsdbCacheRelease(lruCache, h);
}
} else if (pr->type == LASTROW_RETRIEVE_TYPE_ALL) {
} else if ((pr->type & CACHESCAN_RETRIEVE_TYPE_ALL) == CACHESCAN_RETRIEVE_TYPE_ALL) {
for (int32_t i = pr->tableIndex; i < numOfTables; ++i) {
STableKeyInfo* pKeyInfo = taosArrayGet(pr->pTableList, i);
int32_t code = tsdbCacheGetLastrowH(lruCache, pKeyInfo->uid, pr->pVnode->pTsdb, &h);
// int32_t code = tsdbCacheGetLastH(lruCache, pKeyInfo->uid, pr->pVnode->pTsdb, &h);
if (code != TSDB_CODE_SUCCESS) {
code = doExtractCacheRow(pr, lruCache, pKeyInfo->uid, &pRow, &h);
if (code != TSDB_CODE_SUCCESS) {
return code;
}
// no data in the table of Uid
if (h == NULL) {
continue;
}
pRow = (STSRow*)taosLRUCacheValue(lruCache, h);
// SArray* pLast = (SArray*)taosLRUCacheValue(lruCache, h);
// tsdbCacheLastArray2Row(pLast, &pRow, pr->pSchema);
saveOneRow(pRow, pResBlock, pr, slotIds);
taosArrayPush(pTableUidList, &pKeyInfo->uid);

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