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Merge branch 'enh/3.0' into enh/rocksdbSstateMerge

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yihaoDeng 2023-05-15 01:52:42 +00:00
parent 41ebd07472 9e8cc7d18c
commit 9c0d2c87c6
258 changed files with 14697 additions and 6043 deletions
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4
README-CN.md
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@ -52,7 +52,7 @@ TDengine 还提供一组辅助工具软件 taosTools，目前它包含 taosBench
### Ubuntu 18.04 及以上版本 & Debian：
```bash
sudo apt-get install -y gcc cmake build-essential git libssl-dev
sudo apt-get install -y gcc cmake build-essential git libssl-dev libgflags2.2 libgflags-dev
```
#### 为 taos-tools 安装编译需要的软件
@ -352,4 +352,4 @@ TDengine 提供了丰富的应用程序开发接口，其中包括 C/C++、Java
# 加入技术交流群
TDengine 官方社群「物联网大数据群」对外开放，欢迎您加入讨论。搜索微信号 "tdengine"，加小 T 为好友，即可入群。
TDengine 官方社群「物联网大数据群」对外开放，欢迎您加入讨论。搜索微信号 "tdengine1"，加小 T 为好友，即可入群。

2
README.md
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@ -60,7 +60,7 @@ To build TDengine, use [CMake](https://cmake.org/) 3.0.2 or higher versions in t
### Ubuntu 18.04 and above or Debian
```bash
sudo apt-get install -y gcc cmake build-essential git libssl-dev
sudo apt-get install -y gcc cmake build-essential git libssl-dev libgflags2.2 libgflags-dev
```
#### Install build dependencies for taosTools

2
cmake/cmake.define
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@ -1,6 +1,6 @@
cmake_minimum_required(VERSION 3.0)
set(CMAKE_VERBOSE_MAKEFILE OFF)
set(CMAKE_VERBOSE_MAKEFILE ON)
set(TD_BUILD_TAOSA_INTERNAL FALSE)
#set output directory

4
contrib/CMakeLists.txt
View File

@ -242,6 +242,10 @@ if(${BUILD_WITH_ROCKSDB})
option(WITH_PERF_CONTEXT "" OFF)
endif(${TD_DARWIN})
if(${TD_WINDOWS})
option(WITH_JNI "" ON)
endif(${TD_WINDOWS})
if(${TD_WINDOWS})
option(WITH_MD_LIBRARY "build with MD" OFF)
set(SYSTEM_LIBS ${SYSTEM_LIBS} shlwapi.lib rpcrt4.lib)

4
contrib/test/rocksdb/CMakeLists.txt
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@ -1,6 +1,8 @@
message("contrib test/rocksdb:" ${BUILD_DEPENDENCY_TESTS})
add_executable(rocksdbTest "")
target_sources(rocksdbTest
PRIVATE
"${CMAKE_CURRENT_SOURCE_DIR}/main.c"
)
target_link_libraries(rocksdbTest rocksdb)
target_link_libraries(rocksdbTest rocksdb)

19
contrib/test/rocksdb/main.c
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@ -116,9 +116,20 @@ int main(int argc, char const *argv[]) {
rocksdb_options_set_create_if_missing(opt, 1);
rocksdb_options_set_create_missing_column_families(opt, 1);
const char *cfName[] = {"default", "cf1"};
int len = sizeof(cfName) / sizeof(cfName[0]);
// Read
rocksdb_readoptions_t *readoptions = rocksdb_readoptions_create();
// rocksdb_readoptions_set_snapshot(readoptions, rocksdb_create_snapshot(db));
int len = 1;
char buf[256] = {0};
size_t vallen = 0;
char *val = rocksdb_get(db, readoptions, "key", 3, &vallen, &err);
snprintf(buf, vallen + 5, "val:%s", val);
printf("%ld %ld %s\n", strlen(val), vallen, buf);
char **cfName = calloc(len, sizeof(char *));
for (int i = 0; i < len; i++) {
cfName[i] = "test";
}
const rocksdb_options_t **cfOpt = malloc(len * sizeof(rocksdb_options_t *));
for (int i = 0; i < len; i++) {
cfOpt[i] = rocksdb_options_create_copy(opt);
@ -129,7 +140,7 @@ int main(int argc, char const *argv[]) {
}
rocksdb_column_family_handle_t **cfHandle = malloc(len * sizeof(rocksdb_column_family_handle_t *));
db = rocksdb_open_column_families(opt, path, len, cfName, cfOpt, cfHandle, &err);
db = rocksdb_open_column_families(opt, path, len, (const char *const *)cfName, cfOpt, cfHandle, &err);
{
rocksdb_readoptions_t *rOpt = rocksdb_readoptions_create();
@ -302,4 +313,4 @@ int main(int argc, char const *argv[]) {
// rocksdb_close(db);
return 0;
}
}

13
docs/en/02-intro/index.md
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@ -44,7 +44,7 @@ For more details on features, please read through the entire documentation.
## Competitive Advantages
By making full use of [characteristics of time series data](https://tdengine.com/tsdb/characteristics-of-time-series-data/), TDengine differentiates itself from other [time series databases](https://tdengine.com/tsdb), with the following advantages.
By making full use of [characteristics of time series data](https://tdengine.com/tsdb/characteristics-of-time-series-data/), TDengine differentiates itself from other [time series databases](https://tdengine.com/tsdb/), with the following advantages.
- **[High-Performance](https://tdengine.com/tdengine/high-performance-time-series-database/)**: TDengine is the only time-series database to solve the high cardinality issue to support billions of data collection points while out performing other time-series databases for data ingestion, querying and data compression.
@ -123,13 +123,12 @@ As a high-performance, scalable and SQL supported time-series database, TDengine
## Comparison with other databases
- [Writing Performance Comparison of TDengine and InfluxDB ](https://tdengine.com/performance-comparison-of-tdengine-and-influxdb/)
- [Query Performance Comparison of TDengine and InfluxDB](https://tdengine.com/query-performance-comparison-test-report-tdengine-vs-influxdb/)
- [TDengine vs OpenTSDB](https://tdengine.com/performance-tdengine-vs-opentsdb/)
- [TDengine vs Cassandra](https://tdengine.com/performance-tdengine-vs-cassandra/)
- [TDengine vs InfluxDB](https://tdengine.com/performance-tdengine-vs-influxdb/)
- [TDengine vs. InfluxDB](https://tdengine.com/tsdb-comparison-influxdb-vs-tdengine/)
- [TDengine vs. TimescaleDB](https://tdengine.com/tsdb-comparison-timescaledb-vs-tdengine/)
- [TDengine vs. OpenTSDB](https://tdengine.com/performance-tdengine-vs-opentsdb/)
- [TDengine vs. Cassandra](https://tdengine.com/performance-tdengine-vs-cassandra/)
## More readings
- [Introduction to Time-Series Database](https://tdengine.com/tsdb/)
- [Introduction to TDengine competitive advantages](https://tdengine.com/tdengine/)

2
docs/en/05-get-started/01-docker.md
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@ -6,7 +6,7 @@ description: This document describes how to install TDengine in a Docker contain
This document describes how to install TDengine in a Docker container and perform queries and inserts.
- The easiest way to explore TDengine is through [TDengine Cloud](http://cloud.tdengine.com).
- The easiest way to explore TDengine is through [TDengine Cloud](https://cloud.tdengine.com).
- To get started with TDengine in a non-containerized environment, see [Quick Install from Package](../../get-started/package).
- If you want to view the source code, build TDengine yourself, or contribute to the project, see the [TDengine GitHub repository](https://github.com/taosdata/TDengine).

6
docs/en/05-get-started/03-package.md
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@ -10,7 +10,7 @@ import PkgListV3 from "/components/PkgListV3";
This document describes how to install TDengine on Linux/Windows/macOS and perform queries and inserts.
- The easiest way to explore TDengine is through [TDengine Cloud](http://cloud.tdengine.com).
- The easiest way to explore TDengine is through [TDengine Cloud](https://cloud.tdengine.com).
- To get started with TDengine on Docker, see [Quick Install on Docker](../../get-started/docker).
- If you want to view the source code, build TDengine yourself, or contribute to the project, see the [TDengine GitHub repository](https://github.com/taosdata/TDengine).
@ -102,7 +102,7 @@ sudo apt-get install tdengine
:::tip
This installation method is supported only for Debian and Ubuntu.
::::
:::
</TabItem>
<TabItem label="Windows" value="windows">
@ -208,6 +208,8 @@ The following `launchctl` commands can help you manage TDengine service:
- Check TDengine Server status: `sudo launchctl list | grep taosd`
- Check TDengine Server status details: `launchctl print system/com.tdengine.taosd`
:::info
- Please use `sudo` to run `launchctl` to manage _com.tdengine.taosd_ with administrator privileges.
- The administrator privilege is required for service management to enhance security.

2
docs/en/07-develop/01-connect/index.md
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@ -288,6 +288,6 @@ Prior to establishing connection, please make sure TDengine is already running a
</Tabs>
:::tip
If the connection fails, in most cases it's caused by improper configuration for FQDN or firewall. Please refer to the section "Unable to establish connection" in [FAQ](https://docs.tdengine.com/train-faq/faq).
If the connection fails, in most cases it's caused by improper configuration for FQDN or firewall. Please refer to the section "Unable to establish connection" in [FAQ](../../train-faq/faq).
:::

3
docs/en/07-develop/03-insert-data/_rust_schemaless.mdx Normal file
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@ -0,0 +1,3 @@
```rust
{{#include docs/examples/rust/nativeexample/examples/schemaless_insert_line.rs}}
```

8
docs/en/07-develop/07-tmq.mdx
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@ -23,7 +23,7 @@ By subscribing to a topic, a consumer can obtain the latest data in that topic i
To implement these features, TDengine indexes its write-ahead log (WAL) file for fast random access and provides configurable methods for replacing and retaining this file. You can define a retention period and size for this file. For information, see the CREATE DATABASE statement. In this way, the WAL file is transformed into a persistent storage engine that remembers the order in which events occur. However, note that configuring an overly long retention period for your WAL files makes database compression inefficient. TDengine then uses the WAL file instead of the time-series database as its storage engine for queries in the form of topics. TDengine reads the data from the WAL file; uses a unified query engine instance to perform filtering, transformations, and other operations; and finally pushes the data to consumers.
Tips:The default data subscription is to consume data from the wal. If the wal is deleted, the consumed data will be incomplete. At this time, you can set the parameter experimental.snapshot.enable to true to obtain all data from the tsdb, but in this way, the consumption order of the data cannot be guaranteed. Therefore, it is recommended to set a reasonable retention policy for WAL based on your consumption situation to ensure that you can subscribe all data from WAL.
Tips: Data subscription is to consume data from the wal. If some wal files are deleted according to WAL retention policy, the deleted data can't be consumed any more. So you need to set a reasonable value for parameter `WAL_RETENTION_PERIOD` or `WAL_RETENTION_SIZE` when creating the database and make sure your application consume the data in a timely way to make sure there is no data loss. This behavior is similar to Kafka and other widely used message queue products.
## Data Schema and API
@ -222,7 +222,7 @@ A database including one supertable and two subtables is created as follows:
```sql
DROP DATABASE IF EXISTS tmqdb;
CREATE DATABASE tmqdb;
CREATE DATABASE tmqdb WAL_RETENTION_PERIOD 3600;
CREATE TABLE tmqdb.stb (ts TIMESTAMP, c1 INT, c2 FLOAT, c3 VARCHAR(16)) TAGS(t1 INT, t3 VARCHAR(16));
CREATE TABLE tmqdb.ctb0 USING tmqdb.stb TAGS(0, "subtable0");
CREATE TABLE tmqdb.ctb1 USING tmqdb.stb TAGS(1, "subtable1");
@ -294,7 +294,6 @@ You configure the following parameters when creating a consumer:
| `auto.offset.reset` | enum | Initial offset for the consumer group | Specify `earliest`, `latest`, or `none`(default) |
| `enable.auto.commit` | boolean | Commit automatically; true: user application doesn't need to explicitly commit; false: user application need to handle commit by itself | Default value is true |
| `auto.commit.interval.ms` | integer | Interval for automatic commits, in milliseconds |
| `experimental.snapshot.enable` | boolean | Specify whether to consume data in TSDB; true: both data in WAL and in TSDB can be consumed; false: only data in WAL can be consumed | default value: false |
| `msg.with.table.name` | boolean | Specify whether to deserialize table names from messages | default value: false
The method of specifying these parameters depends on the language used:
@ -312,7 +311,6 @@ tmq_conf_set(conf, "group.id", "cgrpName");
tmq_conf_set(conf, "td.connect.user", "root");
tmq_conf_set(conf, "td.connect.pass", "taosdata");
tmq_conf_set(conf, "auto.offset.reset", "earliest");
tmq_conf_set(conf, "experimental.snapshot.enable", "true");
tmq_conf_set(conf, "msg.with.table.name", "true");
tmq_conf_set_auto_commit_cb(conf, tmq_commit_cb_print, NULL);
@ -368,7 +366,6 @@ conf := &tmq.ConfigMap{
"td.connect.port": "6030",
"client.id": "test_tmq_c",
"enable.auto.commit": "false",
"experimental.snapshot.enable": "true",
"msg.with.table.name": "true",
}
consumer, err := NewConsumer(conf)
@ -416,7 +413,6 @@ Python programs use the following parameters:
| `enable.auto.commit` | string | Commit automatically | pecify `true` or `false` |
| `auto.commit.interval.ms` | string | Interval for automatic commits, in milliseconds | |
| `auto.offset.reset` | string | Initial offset for the consumer group | Specify `earliest`, `latest`, or `none`(default) |
| `experimental.snapshot.enable` | string | Specify whether it's allowed to consume messages from the WAL or from TSDB | Specify `true` or `false` |
| `enable.heartbeat.background` | string | Backend heartbeat; if enabled, the consumer does not go offline even if it has not polled for a long time | Specify `true` or `false` |
</TabItem>

188
docs/en/07-develop/09-udf.md
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@ -6,10 +6,12 @@ description: This document describes how to create user-defined functions (UDF),
The built-in functions of TDengine may not be sufficient for the use cases of every application. In this case, you can define custom functions for use in TDengine queries. These are known as user-defined functions (UDF). A user-defined function takes one column of data or the result of a subquery as its input.
TDengine supports user-defined functions written in C or C++. This document describes the usage of user-defined functions.
User-defined functions can be scalar functions or aggregate functions. Scalar functions, such as `abs`, `sin`, and `concat`, output a value for every row of data. Aggregate functions, such as `avg` and `max` output one value for multiple rows of data.
TDengine supports user-defined functions written in C or Python. This document describes the usage of user-defined functions.
## Implement a UDF in C
When you create a user-defined function, you must implement standard interface functions:
- For scalar functions, implement the `scalarfn` interface function.
- For aggregate functions, implement the `aggfn_start`, `aggfn`, and `aggfn_finish` interface functions.
@ -17,7 +19,7 @@ When you create a user-defined function, you must implement standard interface f
There are strict naming conventions for these interface functions. The names of the start, finish, init, and destroy interfaces must be <udf-name\>_start, <udf-name\>_finish, <udf-name\>_init, and <udf-name\>_destroy, respectively. Replace `scalarfn`, `aggfn`, and `udf` with the name of your user-defined function.
## Implementing a Scalar Function
### Implementing a Scalar Function in C
The implementation of a scalar function is described as follows:
```c
#include "taos.h"
@ -49,7 +51,7 @@ int32_t scalarfn_destroy() {
```
Replace `scalarfn` with the name of your function.
## Implementing an Aggregate Function
### Implementing an Aggregate Function in C
The implementation of an aggregate function is described as follows:
```c
@ -100,7 +102,7 @@ int32_t aggfn_destroy() {
```
Replace `aggfn` with the name of your function.
## Interface Functions
### UDF Interface Definition in C
There are strict naming conventions for interface functions. The names of the start, finish, init, and destroy interfaces must be <udf-name\>_start, <udf-name\>_finish, <udf-name\>_init, and <udf-name\>_destroy, respectively. Replace `scalarfn`, `aggfn`, and `udf` with the name of your user-defined function.
@ -108,8 +110,7 @@ Interface functions return a value that indicates whether the operation was succ
For information about the parameters for interface functions, see Data Model
### Interfaces for Scalar Functions
#### Scalar Interface
`int32_t scalarfn(SUdfDataBlock* inputDataBlock, SUdfColumn *resultColumn)`
Replace `scalarfn` with the name of your function. This function performs scalar calculations on data blocks. You can configure a value through the parameters in the `resultColumn` structure.
@ -118,7 +119,7 @@ The parameters in the function are defined as follows:
- inputDataBlock: The data block to input.
- resultColumn: The column to output. The column to output.
### Interfaces for Aggregate Functions
#### Aggregate Interface
`int32_t aggfn_start(SUdfInterBuf *interBuf)`
@ -126,7 +127,7 @@ The parameters in the function are defined as follows:
`int32_t aggfn_finish(SUdfInterBuf* interBuf, SUdfInterBuf *result)`
Replace `aggfn` with the name of your function. In the function, aggfn_start is called to generate a result buffer. Data is then divided between multiple blocks, and aggfn is called on each block to update the result. Finally, aggfn_finish is called to generate final results from the intermediate results. The final result contains only one or zero data points.
Replace `aggfn` with the name of your function. In the function, aggfn_start is called to generate a result buffer. Data is then divided between multiple blocks, and the `aggfn` function is called on each block to update the result. Finally, aggfn_finish is called to generate the final results from the intermediate results. The final result contains only one or zero data points.
The parameters in the function are defined as follows:
- interBuf: The intermediate result buffer.
@ -135,15 +136,15 @@ The parameters in the function are defined as follows:
- result: The final result.
### Initializing and Terminating User-Defined Functions
#### Initialization and Cleanup Interface
`int32_t udf_init()`
`int32_t udf_destroy()`
Replace `udf`with the name of your function. udf_init initializes the function. udf_destroy terminates the function. If it is not necessary to initialize your function, udf_init is not required. If it is not necessary to terminate your function, udf_destroy is not required.
Replace `udf` with the name of your function. udf_init initializes the function. udf_destroy terminates the function. If it is not necessary to initialize your function, udf_init is not required. If it is not necessary to terminate your function, udf_destroy is not required.
## Data Structure of User-Defined Functions
### Data Structures for UDF in C
```c
typedef struct SUdfColumnMeta {
int16_t type;
@ -193,7 +194,7 @@ typedef struct SUdfInterBuf {
```
The data structure is described as follows:
- The SUdfDataBlock block includes the number of rows (numOfRows) and number of columns (numCols). udfCols[i] (0 <= i <= numCols-1) indicates that each column is of type SUdfColumn.
- The SUdfDataBlock block includes the number of rows (numOfRows) and the number of columns (numCols). udfCols[i] (0 <= i <= numCols-1) indicates that each column is of type SUdfColumn.
- SUdfColumn includes the definition of the data type of the column (colMeta) and the data in the column (colData).
- The member definitions of SUdfColumnMeta are the same as the data type definitions in `taos.h`.
- The data in SUdfColumnData can become longer. varLenCol indicates variable-length data, and fixLenCol indicates fixed-length data.
@ -201,9 +202,9 @@ The data structure is described as follows:
Additional functions are defined in `taosudf.h` to make it easier to work with these structures.
## Compile UDF
### Compiling C UDF
To use your user-defined function in TDengine, first compile it to a dynamically linked library (DLL).
To use your user-defined function in TDengine, first, compile it to a shared library.
For example, the sample UDF `bit_and.c` can be compiled into a DLL as follows:
@ -213,12 +214,9 @@ gcc -g -O0 -fPIC -shared bit_and.c -o libbitand.so
The generated DLL file `libbitand.so` can now be used to implement your function. Note: GCC 7.5 or later is required.
## Manage and Use User-Defined Functions
After compiling your function into a DLL, you add it to TDengine. For more information, see [User-Defined Functions](../12-taos-sql/26-udf.md).
### UDF Sample Code in C
## Sample Code
### Sample scalar function: [bit_and](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/bit_and.c)
#### Scalar function: [bit_and](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/bit_and.c)
The bit_and function implements bitwise addition for multiple columns. If there is only one column, the column is returned. The bit_and function ignores null values.
@ -231,7 +229,7 @@ The bit_and function implements bitwise addition for multiple columns. If there
</details>
### Sample aggregate function: [l2norm](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/l2norm.c)
#### Aggregate function 1: [l2norm](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/l2norm.c)
The l2norm function finds the second-order norm for all data in the input column. This squares the values, takes a cumulative sum, and finds the square root.
@ -243,3 +241,151 @@ The l2norm function finds the second-order norm for all data in the input column
```
</details>
#### Aggregate function 2: [max_vol](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/max_vol.c)
The max_vol function returns a string concatenating the deviceId column, the row number and column number of the maximum voltage and the maximum voltage given several voltage columns as input.
Create Table:
```bash
create table battery(ts timestamp, vol1 float, vol2 float, vol3 float, deviceId varchar(16));
```
Create the UDF:
```bash
create aggregate function max_vol as '/root/udf/libmaxvol.so' outputtype binary(64) bufsize 10240 language 'C';
```
Use the UDF in the query：
```bash
select max_vol(vol1,vol2,vol3,deviceid) from battery;
```
<details>
<summary>max_vol.c</summary>
```c
{{#include tests/script/sh/max_vol.c}}
```
</details>
## Implement a UDF in Python
Implement the specified interface functions when implementing a UDF in Python.
- implement `process` function for the scalar UDF。
- implement `start`, `reduce`, `finish` for the aggregate UDF。
- implement `init` for initialization and `destroy` for termination。
### Implement a Scalar UDF in Python
The implementation of a scalar UDF is described as follows:
```Python
def init():
# initialization
def destroy():
# destroy
def process(input: datablock) -> tuple[output_type]:
# process input datablock,
# datablock.data(row, col) is to access the python object in location(row,col)
# return tuple object consisted of object of type outputtype
```
### Implement an Aggregate UDF in Python
The implementation of an aggregate function is described as follows:
```Python
def init():
#initialization
def destroy():
#destroy
def start() -> bytes:
#return serialize(init_state)
def reduce(inputs: datablock, buf: bytes) -> bytes
# deserialize buf to state
# reduce the inputs and state into new_state.
# use inputs.data(i,j) to access python ojbect of location(i,j)
# serialize new_state into new_state_bytes
return new_state_bytes
def finish(buf: bytes) -> output_type:
#return obj of type outputtype
```
### Python UDF Interface Definition
#### Scalar interface
```Python
def process(input: datablock) -> tuple[output_type]:
```
- `input` is a data block two-dimension matrix-like object, of which method `data(row, col)` returns the Python object located at location (`row`, `col`)
- return a Python tuple object, of which each item is a Python object of type `output_type`
#### Aggregate Interface
```Python
def start() -> bytes:
def reduce(input: datablock, buf: bytes) -> bytes
def finish(buf: bytes) -> output_type:
```
- first `start()` is called to return the initial result in type `bytes`
- then the input data are divided into multiple data blocks and for each block `input`, `reduce` is called with the data block `input` and the current result `buf` bytes and generates a new intermediate result buffer.
- finally, the `finish` function is called on the intermediate result `buf` and outputs 0 or 1 data of type `output_type`
#### Initialization and Cleanup Interface
```Python
def init()
def destroy()
```
Implement `init` for initialization and `destroy` for termination.
### Data Mapping between TDengine SQL and Python UDF
The following table describes the mapping between TDengine SQL data type and Python UDF Data Type. The `NULL` value of all TDengine SQL types is mapped to the `None` value in Python.
| **TDengine SQL Data Type** | **Python Data Type** |
| :-----------------------: | ------------ |
|TINYINT / SMALLINT / INT / BIGINT | int |
|TINYINT UNSIGNED / SMALLINT UNSIGNED / INT UNSIGNED / BIGINT UNSIGNED | int |
|FLOAT / DOUBLE | float |
|BOOL | bool |
|BINARY / VARCHAR / NCHAR | bytes|
|TIMESTAMP | int |
|JSON and other types | Not Supported |
### Installing Python UDF
1. Install Python package `taospyudf` that executes Python UDF
```bash
sudo pip install taospyudf
ldconfig
```
2. If PYTHONPATH is needed to find Python packages when the Python UDF executes, include the PYTHONPATH contents into the udfdLdLibPath variable of the taos.cfg configuration file
### Python UDF Sample Code
#### Scalar Function [pybitand](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/pybitand.py)
The `pybitand` function implements bitwise addition for multiple columns. If there is only one column, the column is returned. The `pybitand` function ignores null values.
<details>
<summary>pybitand.py</summary>
```Python
{{#include tests/script/sh/pybitand.py}}
```
</details>
#### Aggregate Function [pyl2norm](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/pyl2norm.py)
The `pyl2norm` function finds the second-order norm for all data in the input column. This squares the values, takes a cumulative sum, and finds the square root.
<details>
<summary>pyl2norm.py</summary>
```c
{{#include tests/script/sh/pyl2norm.py}}
```
</details>
## Manage and Use UDF
You need to add UDF to TDengine before using it in SQL queries. For more information about how to manage UDF and how to invoke UDF, please see [Manage and Use UDF](../12-taos-sql/26-udf.md).

4
docs/en/12-taos-sql/02-database.md
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@ -72,8 +72,8 @@ database_option: {
- 0: The database can contain multiple supertables.
- 1: The database can contain only one supertable.
- STT_TRIGGER: specifies the number of file merges triggered by flushed files. The default is 8, ranging from 1 to 16. For high-frequency scenarios with few tables, it is recommended to use the default configuration or a smaller value for this parameter; For multi-table low-frequency scenarios, it is recommended to configure this parameter with a larger value.
- TABLE_PREFIX：The prefix length in the table name that is ignored when distributing table to vnode based on table name.
- TABLE_SUFFIX：The suffix length in the table name that is ignored when distributing table to vnode based on table name.
- TABLE_PREFIX： The prefix in the table name that is ignored when distributing a table to a vgroup when it's a positive number, or only the prefix is used when distributing a table to a vgroup, the default value is 0; For example, if the table name v30001, then "0001" is used if TSDB_PREFIX is set to 2 but "v3" is used if TSDB_PREFIX is set to -2; It can help you to control the distribution of tables.
- TABLE_SUFFIX：The suffix in the table name that is ignored when distributing a table to a vgroup when it's a positive number, or only the suffix is used when distributing a table to a vgroup, the default value is 0; For example, if the table name v30001, then "v300" is used if TSDB_SUFFIX is set to 2 but "01" is used if TSDB_SUFFIX is set to -2; It can help you to control the distribution of tables.
- TSDB_PAGESIZE: The page size of the data storage engine in a vnode. The unit is KB. The default is 4 KB. The range is 1 to 16384, that is, 1 KB to 16 MB.
- WAL_RETENTION_PERIOD: specifies the maximum time of which WAL files are to be kept for consumption. This parameter is used for data subscription. Enter a time in seconds. The default value 0. A value of 0 indicates that WAL files are not required to keep for consumption. Alter it with a proper value at first to create topics.
- WAL_RETENTION_SIZE: specifies the maximum total size of which WAL files are to be kept for consumption. This parameter is used for data subscription. Enter a size in KB. The default value is 0. A value of 0 indicates that the total size of WAL files to keep for consumption has no upper limit.

2
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@ -33,7 +33,7 @@ column_definition:
SHOW STABLES [LIKE tb_name_wildcard];
```
The preceding SQL statement shows all supertables in the current TDengine database, including the name, creation time, number of columns, number of tags, and number of subtables for each supertable.
The preceding SQL statement shows all supertables in the current TDengine database.
### View the CREATE Statement for a Supertable

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@ -55,7 +55,7 @@ window_clause: {
| INTERVAL(interval_val [, interval_offset]) [SLIDING (sliding_val)] [WATERMARK(watermark_val)] [FILL(fill_mod_and_val)]
interp_clause:
RANGE(ts_val, ts_val), EVERY(every_val), FILL(fill_mod_and_val)
RANGE(ts_val, ts_val) EVERY(every_val) FILL(fill_mod_and_val)
partition_by_clause:
PARTITION BY expr [, expr] ...

4
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@ -6,7 +6,7 @@ description: Use Tag Index to Improve Query Performance
## Introduction
Prior to TDengine 3.0.3.0 (excluded)，only one index is created by default on the first tag of each super talbe, but it's not allowed to dynamically create index on any other tags. From version 3.0.30, you can dynamically create index on any tag of any type. The index created automatically by TDengine is still valid. Query performance can benefit from indexes if you use properly.
Prior to TDengine 3.0.3.0 (excluded)，only one index is created by default on the first tag of each super table, but it's not allowed to dynamically create index on any other tags. From version 3.0.30, you can dynamically create index on any tag of any type. The index created automatically by TDengine is still valid. Query performance can benefit from indexes if you use properly.
## Syntax
@ -48,4 +48,4 @@ You can also add filter conditions to limit the results.
6. You can' create index on a normal table or a child table.
7. If the unique values of a tag column are too few, it's better not to create index on such tag columns, the benefit would be very small.
7. If the unique values of a tag column are too few, it's better not to create index on such tag columns, the benefit would be very small.

6
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@ -5,9 +5,9 @@ description: This document describes the standard SQL functions available in TDe
toc_max_heading_level: 4
---
## Single Row Functions
## Scalar Functions
Single row functions return a result for each row.
Scalar functions return one result for each row.
### Mathematical Functions
@ -886,7 +886,7 @@ INTERP(expr)
- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1 <= timestamp2. timestamp1 is the starting point of the output time range and must be specified. timestamp2 is the ending point of the output time range and must be specified.
- The number of rows in the result set of `INTERP` is determined by the parameter `EVERY(time_unit)`. Starting from timestamp1, one interpolation is performed for every time interval specified `time_unit` parameter. The parameter `time_unit` must be an integer, with no quotes, with a time unit of: a(millisecond)), s(second), m(minute), h(hour), d(day), or w(week). For example, `EVERY(500a)` will interpolate every 500 milliseconds.
- Interpolation is performed based on `FILL` parameter. For more information about FILL clause, see [FILL Clause](../distinguished/#fill-clause).
- `INTERP` can only be used to interpolate in single timeline. So it must be used with `partition by tbname` when it's used on a STable.
- `INTERP` can be applied to supertable by interpolating primary key sorted data of all its childtables. It can also be used with `partition by tbname` when applied to supertable to generate interpolation on each single timeline.
- Pseudocolumn `_irowts` can be used along with `INTERP` to return the timestamps associated with interpolation points(support after version 3.0.2.0).
- Pseudocolumn `_isfilled` can be used along with `INTERP` to indicate whether the results are original records or data points generated by interpolation algorithm(support after version 3.0.3.0).

31
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@ -13,8 +13,11 @@ Because stream processing is built in to TDengine, you are no longer reliant on
```sql
CREATE STREAM [IF NOT EXISTS] stream_name [stream_options] INTO stb_name SUBTABLE(expression) AS subquery
stream_options: {
TRIGGER [AT_ONCE | WINDOW_CLOSE | MAX_DELAY time]
WATERMARK time
TRIGGER [AT_ONCE | WINDOW_CLOSE | MAX_DELAY time]
WATERMARK time
IGNORE EXPIRED [0|1]
DELETE_MARK time
FILL_HISTORY [0|1]
}
```
@ -141,3 +144,27 @@ The data in expired windows is tagged as expired. TDengine stream processing pro
2. Recalculate the data. In this method, all data in the window is reobtained from the database and recalculated. The latest results are then returned.
In both of these methods, configuring the watermark is essential for obtaining accurate results (if expired data is dropped) and avoiding repeated triggers that affect system performance (if expired data is recalculated).
## Supported functions
All [scalar functions](../function/#scalar-functions) are available in stream processing. All [Aggregate functions](../function/#aggregate-functions) and [Selection functions](../function/#selection-functions) are available in stream processing, except the followings:
- [leastsquares](../function/#leastsquares)
- [percentile](../function/#percentile)
- [top](../function/#top)
- [bottom](../function/#bottom)
- [elapsed](../function/#elapsed)
- [interp](../function/#interp)
- [derivative](../function/#derivative)
- [irate](../function/#irate)
- [twa](../function/#twa)
- [histogram](../function/#histogram)
- [diff](../function/#diff)
- [statecount](../function/#statecount)
- [stateduration](../function/#stateduration)
- [csum](../function/#csum)
- [mavg](../function/#mavg)
- [sample](../function/#sample)
- [tail](../function/#tail)
- [unique](../function/#unique)
- [mode](../function/#mode)

3
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@ -120,6 +120,9 @@ Provides information about user-defined functions.
| 5 | create_time | TIMESTAMP | Creation time |
| 6 | code_len | INT | Length of the source code |
| 7 | bufsize | INT | Buffer size |
| 8 | func_language | BINARY(31) | UDF programming language |
| 9 | func_body | BINARY(16384) | UDF function body |
| 10 | func_version | INT | UDF function version. starting from 0. Increasing by 1 each time it is updated|
## INS_INDEXES

8
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@ -129,6 +129,14 @@ SHOW QNODES;
Shows information about qnodes in the system.
## SHOW QUERIES
```sql
SHOW QUERIES;
```
Shows the queries in progress in the system.
## SHOW SCORES
```sql

32
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@ -7,17 +7,18 @@ description: This document describes the SQL statements related to user-defined
You can create user-defined functions and import them into TDengine.
## Create UDF
SQL command can be executed on the host where the generated UDF DLL resides to load the UDF DLL into TDengine. This operation cannot be done through REST interface or web console. Once created, any client of the current TDengine can use these UDF functions in their SQL commands. UDF are stored in the management node of TDengine. The UDFs loaded in TDengine would be still available after TDengine is restarted.
SQL command can be executed on the host where the generated UDF DLL resides to load the UDF DLL into TDengine. This operation cannot be done through REST interface or web console. Once created, any client of the current TDengine can use these UDF functions in their SQL commands. UDF is stored in the management node of TDengine. The UDFs loaded in TDengine would be still available after TDengine is restarted.
When creating UDF, the type of UDF, i.e. a scalar function or aggregate function must be specified. If the specified type is wrong, the SQL statements using the function would fail with errors. The input data type and output data type must be consistent with the UDF definition.
- Create Scalar Function
```sql
CREATE FUNCTION function_name AS library_path OUTPUTTYPE output_type;
CREATE [OR REPLACE] FUNCTION function_name AS library_path OUTPUTTYPE output_type [LANGUAGE 'C|Python'];
```
- function_name: The scalar function name to be used in SQL statement which must be consistent with the UDF name and is also the name of the compiled DLL (.so file).
- library_path: The absolute path of the DLL file including the name of the shared object file (.so). The path must be quoted with single or double quotes.
- OR REPLACE: if the UDF exists, the UDF properties are modified
- function_name: The scalar function name to be used in the SQL statement
- LANGUAGE 'C|Python': the programming language of UDF. Now C or Python is supported. If this clause is omitted, C is assumed as the programming language.
- library_path: For C programming language, The absolute path of the DLL file including the name of the shared object file (.so). For Python programming language, the absolute path of the Python UDF script. The path must be quoted with single or double quotes.
- output_type: The data type of the results of the UDF.
For example, the following SQL statement can be used to create a UDF from `libbitand.so`.
@ -25,14 +26,20 @@ CREATE FUNCTION function_name AS library_path OUTPUTTYPE output_type;
```sql
CREATE FUNCTION bit_and AS "/home/taos/udf_example/libbitand.so" OUTPUTTYPE INT;
```
For Example, the following SQL statement can be used to modify the existing function `bit_and`. The OUTPUT type is changed to BIGINT and the programming language is changed to Python.
```sql
CREATE OR REPLACE FUNCTION bit_and AS "/home/taos/udf_example/bit_and.py" OUTPUTTYPE BIGINT LANGUAGE 'Python';
```
- Create Aggregate Function
```sql
CREATE AGGREGATE FUNCTION function_name AS library_path OUTPUTTYPE output_type [ BUFSIZE buffer_size ];
```
- function_name: The aggregate function name to be used in SQL statement which must be consistent with the udfNormalFunc name and is also the name of the compiled DLL (.so file).
- library_path: The absolute path of the DLL file including the name of the shared object file (.so). The path must be quoted with single or double quotes.
- OR REPLACE: if the UDF exists, the UDF properties are modified
- function_name: The aggregate function name to be used in the SQL statement
- LANGUAGE 'C|Python': the programming language of the UDF. Now C or Python is supported. If this clause is omitted, C is assumed as the programming language.
- library_path: For C programming language, The absolute path of the DLL file including the name of the shared object file (.so). For Python programming language, the absolute path of the Python UDF script. The path must be quoted with single or double quotes.
- output_type: The output data type, the value is the literal string of the supported TDengine data type.
- buffer_size: The size of the intermediate buffer in bytes. This parameter is optional.
@ -41,6 +48,11 @@ CREATE AGGREGATE FUNCTION function_name AS library_path OUTPUTTYPE output_type [
```sql
CREATE AGGREGATE FUNCTION l2norm AS "/home/taos/udf_example/libl2norm.so" OUTPUTTYPE DOUBLE bufsize 8;
```
For example, the following SQL statement modifies the buffer size of existing UDF `l2norm` to 64
```sql
CREATE AGGREGATE FUNCTION l2norm AS "/home/taos/udf_example/libl2norm.so" OUTPUTTYPE DOUBLE bufsize 64;
```
For more information about user-defined functions, see [User-Defined Functions](/develop/udf).
## Manage UDF
@ -61,9 +73,9 @@ SHOW FUNCTIONS;
## Call UDF
The function name specified when creating UDF can be used directly in SQL statements, just like builtin functions. For example:
The function name specified when creating UDF can be used directly in SQL statements, just like built-in functions. For example:
```sql
SELECT bit_and(c1,c2) FROM table;
```
The above SQL statement invokes function X for column c1 and c2 on table. You can use query keywords like WHERE with user-defined functions.
The above SQL statement invokes function X for columns c1 and c2 on the table. You can use query keywords like WHERE with user-defined functions.

2
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@ -27,7 +27,7 @@ The following data types can be used in the schema for standard tables.
| - | :------- | :-------- | :------- |
| 1 | ALTER ACCOUNT | Deprecated| This Enterprise Edition-only statement has been removed. It returns the error "This statement is no longer supported."
| 2 | ALTER ALL DNODES | Added | Modifies the configuration of all dnodes.
| 3 | ALTER DATABASE | Modified | Deprecated<ul><li>QUORUM: Specified the required number of confirmations. TDengine 3.0 provides strict consistency by default and doesn't allow to change to weak consitency. </li><li>BLOCKS: Specified the memory blocks used by each vnode. BUFFER is now used to specify the size of the write cache pool for each vnode. </li><li>UPDATE: Specified whether update operations were supported. All databases now support updating data in certain columns. </li><li>CACHELAST: Specified how to cache the newest row of data. CACHEMODEL now replaces CACHELAST. </li><li>COMP: Cannot be modified. <br/>Added</li><li>CACHEMODEL: Specifies whether to cache the latest subtable data. </li><li>CACHESIZE: Specifies the size of the cache for the newest subtable data. </li><li>WAL_FSYNC_PERIOD: Replaces the FSYNC parameter. </li><li>WAL_LEVEL: Replaces the WAL parameter. </li><li>WAL_RETENTION_PERIOD: specifies the time after which WAL files are deleted. This parameter is used for data subscription. </li><li>WAL_RETENTION_SIZE: specifies the size at which WAL files are deleted. This parameter is used for data subscription. <br/>Modified</li><li>REPLICA: Cannot be modified. </li><li>KEEP: Now supports units. </li></ul>
| 3 | ALTER DATABASE | Modified | Deprecated<ul><li>QUORUM: Specified the required number of confirmations. TDengine 3.0 provides strict consistency by default and doesn't allow to change to weak consistency. </li><li>BLOCKS: Specified the memory blocks used by each vnode. BUFFER is now used to specify the size of the write cache pool for each vnode. </li><li>UPDATE: Specified whether update operations were supported. All databases now support updating data in certain columns. </li><li>CACHELAST: Specified how to cache the newest row of data. CACHEMODEL now replaces CACHELAST. </li><li>COMP: Cannot be modified. <br/>Added</li><li>CACHEMODEL: Specifies whether to cache the latest subtable data. </li><li>CACHESIZE: Specifies the size of the cache for the newest subtable data. </li><li>WAL_FSYNC_PERIOD: Replaces the FSYNC parameter. </li><li>WAL_LEVEL: Replaces the WAL parameter. </li><li>WAL_RETENTION_PERIOD: specifies the time after which WAL files are deleted. This parameter is used for data subscription. </li><li>WAL_RETENTION_SIZE: specifies the size at which WAL files are deleted. This parameter is used for data subscription. <br/>Modified</li><li>REPLICA: Cannot be modified. </li><li>KEEP: Now supports units. </li></ul>
| 4 | ALTER STABLE | Modified | Deprecated<ul><li>CHANGE TAG: Modified the name of a tag. Replaced by RENAME TAG. <br/>Added</li><li>RENAME TAG: Replaces CHANGE TAG. </li><li>COMMENT: Specifies comments for a supertable. </li></ul>
| 5 | ALTER TABLE | Modified | Deprecated<ul><li>CHANGE TAG: Modified the name of a tag. Replaced by RENAME TAG. <br/>Added</li><li>RENAME TAG: Replaces CHANGE TAG. </li><li>COMMENT: Specifies comments for a standard table. </li><li>TTL: Specifies the time-to-live for a standard table. </li></ul>
| 6 | ALTER USER | Modified | Deprecated<ul><li>PRIVILEGE: Specified user permissions. Replaced by GRANT and REVOKE. <br/>Added</li><li>ENABLE: Enables or disables a user. </li><li>SYSINFO: Specifies whether a user can query system information. </li></ul>

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@ -42,3 +42,304 @@ An existing Grafana Notification Channel can be specified with parameter `-E`, t
Launch `TDinsight.sh` with the command above and restart Grafana, then open Dashboard `http://localhost:3000/d/tdinsight`.
For more use cases and restrictions please refer to [TDinsight](/reference/tdinsight/).
## log database
The data of tdinsight dashboard is stored in `log` database (default. You can change it in taoskeeper's config file. For more infrmation, please reference to [taoskeeper document](/reference/taosKeeper)). The taoskeeper will create log database on taoskeeper startup.
### cluster\_info table
`cluster_info` table contains cluster information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|first\_ep|VARCHAR||first ep of cluster|
|first\_ep\_dnode\_id|INT||dnode id or first\_ep|
|version|VARCHAR||tdengine version. such as: 3.0.4.0|
|master\_uptime|FLOAT||days of master's uptime|
|monitor\_interval|INT||monitor interval in second|
|dbs\_total|INT||total number of databases in cluster|
|tbs\_total|BIGINT||total number of tables in cluster|
|stbs\_total|INT||total number of stables in cluster|
|dnodes\_total|INT||total number of dnodes in cluster|
|dnodes\_alive|INT||total number of dnodes in ready state|
|mnodes\_total|INT||total number of mnodes in cluster|
|mnodes\_alive|INT||total number of mnodes in ready state|
|vgroups\_total|INT||total number of vgroups in cluster|
|vgroups\_alive|INT||total number of vgroups in ready state|
|vnodes\_total|INT||total number of vnode in cluster|
|vnodes\_alive|INT||total number of vnode in ready state|
|connections\_total|INT||total number of connections to cluster|
|topics\_total|INT||total number of topics in cluster|
|streams\_total|INT||total number of streams in cluster|
|protocol|INT||protocol version|
|cluster\_id|NCHAR|TAG|cluster id|
### d\_info table
`d_info` table contains dnodes information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|status|VARCHAR||dnode status|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### m\_info table
`m_info` table contains mnode information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|role|VARCHAR||the role of mnode. leader or follower|
|mnode\_id|INT|TAG|master node id|
|mnode\_ep|NCHAR|TAG|master node endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### dnodes\_info table
`dnodes_info` table contains dnodes information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|uptime|FLOAT||dnode uptime|
|cpu\_engine|FLOAT||cpu usage of tdengine. read from `/proc/<taosd_pid>/stat`|
|cpu\_system|FLOAT||cpu usage of server. read from `/proc/stat`|
|cpu\_cores|FLOAT||cpu cores of server|
|mem\_engine|INT||memory usage of tdengine. read from `/proc/<taosd_pid>/status`|
|mem\_system|INT||available memory on the server|
|mem\_total|INT||total memory of server in `KB`|
|disk\_engine|INT|||
|disk\_used|BIGINT||usage of data dir in `bytes`|
|disk\_total|BIGINT||the capacity of data dir in `bytes`|
|net\_in|FLOAT||network throughput rate in kb/s. read from `/proc/net/dev`|
|net\_out|FLOAT||network throughput rate in kb/s. read from `/proc/net/dev`|
|io\_read|FLOAT||io throughput rate in kb/s. read from `/proc/<taosd_pid>/io`|
|io\_write|FLOAT||io throughput rate in kb/s. read from `/proc/<taosd_pid>/io`|
|io\_read\_disk|FLOAT||io throughput rate of disk in kb/s. read from `/proc/<taosd_pid>/io`|
|io\_write\_disk|FLOAT||io throughput rate of disk in kb/s. read from `/proc/<taosd_pid>/io`|
|req\_select|INT||number of select queries received per dnode|
|req\_select\_rate|FLOAT||number of select queries received per dnode divided by monitor interval.|
|req\_insert|INT||number of insert queries received per dnode|
|req\_insert\_success|INT||number of successfully insert queries received per dnode|
|req\_insert\_rate|FLOAT||number of insert queries received per dnode divided by monitor interval|
|req\_insert\_batch|INT||number of batch insertions|
|req\_insert\_batch\_success|INT||number of successful batch insertions|
|req\_insert\_batch\_rate|FLOAT||number of batch insertions divided by monitor interval|
|errors|INT||dnode errors|
|vnodes\_num|INT||number of vnodes per dnode|
|masters|INT||number of master vnodes|
|has\_mnode|INT||if the dnode has mnode|
|has\_qnode|INT||if the dnode has qnode|
|has\_snode|INT||if the dnode has snode|
|has\_bnode|INT||if the dnode has bnode|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### data\_dir table
`data_dir` table contains data directory information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|name|NCHAR||data directory. default is `/var/lib/taos`|
|level|INT||level for multi-level storage|
|avail|BIGINT||available space for data directory|
|used|BIGINT||used space for data directory|
|total|BIGINT||total space for data directory|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### log\_dir table
`log_dir` table contains log directory information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|name|NCHAR||log directory. default is `/var/log/taos/`|
|avail|BIGINT||available space for log directory|
|used|BIGINT||used space for data directory|
|total|BIGINT||total space for data directory|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### temp\_dir table
`temp_dir` table contains temp dir information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|name|NCHAR||temp directory. default is `/tmp/`|
|avail|BIGINT||available space for temp directory|
|used|BIGINT||used space for temp directory|
|total|BIGINT||total space for temp directory|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### vgroups\_info table
`vgroups_info` table contains vgroups information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|vgroup\_id|INT||vgroup id|
|database\_name|VARCHAR||database for the vgroup|
|tables\_num|BIGINT||number of tables per vgroup|
|status|VARCHAR||status|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### vnodes\_role table
`vnodes_role` table contains vnode role information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|vnode\_role|VARCHAR||role. leader or follower|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### logs table
`logs` table contains login information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|level|VARCHAR||log level|
|content|NCHAR||log content|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### log\_summary table
`log_summary` table contains log summary information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|error|INT||error count|
|info|INT||info count|
|debug|INT||debug count|
|trace|INT||trace count|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### grants\_info table
`grants_info` table contains grants information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|expire\_time|BIGINT||time until grants expire in seconds|
|timeseries\_used|BIGINT||timeseries used|
|timeseries\_total|BIGINT||total timeseries|
|dnode\_id|INT|TAG|dnode id|
|dnode\_ep|NCHAR|TAG|dnode endpoint|
|cluster\_id|NCHAR|TAG|cluster id|
### keeper\_monitor table
`keeper_monitor` table contains keeper monitor information records.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|ts|TIMESTAMP||timestamp|
|cpu|FLOAT||cpu usage|
|mem|FLOAT||memory usage|
|identify|NCHAR|TAG||
### taosadapter\_restful\_http\_request\_total table
`taosadapter_restful_http_request_total` table contains taosadapter rest request information record. The timestamp column of this table is `_ts`.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|\_ts|TIMESTAMP||timestamp|
|guage|DOUBLE||metric value|
|client\_ip|NCHAR|TAG|client ip|
|endpoint|NCHAR|TAG|taosadpater endpoint|
|request\_method|NCHAR|TAG|request method|
|request\_uri|NCHAR|TAG|request uri|
|status\_code|NCHAR|TAG|status code|
### taosadapter\_restful\_http\_request\_fail table
`taosadapter_restful_http_request_fail` table contains taosadapter failed rest request information record. The timestamp column of this table is `_ts`.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|\_ts|TIMESTAMP||timestamp|
|guage|DOUBLE||metric value|
|client\_ip|NCHAR|TAG|client ip|
|endpoint|NCHAR|TAG|taosadpater endpoint|
|request\_method|NCHAR|TAG|request method|
|request\_uri|NCHAR|TAG|request uri|
|status\_code|NCHAR|TAG|status code|
### taosadapter\_restful\_http\_request\_in\_flight table
`taosadapter_restful_http_request_in_flight` table contains taosadapter rest request information record in real time. The timestamp column of this table is `_ts`.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|\_ts|TIMESTAMP||timestamp|
|guage|DOUBLE||metric value|
|endpoint|NCHAR|TAG|taosadpater endpoint|
### taosadapter\_restful\_http\_request\_summary\_milliseconds table
`taosadapter_restful_http_request_summary_milliseconds` table contains the summary or rest information record. The timestamp column of this table is `_ts`.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|\_ts|TIMESTAMP||timestamp|
|count|DOUBLE|||
|sum|DOUBLE|||
|0.5|DOUBLE|||
|0.9|DOUBLE|||
|0.99|DOUBLE|||
|0.1|DOUBLE|||
|0.2|DOUBLE|||
|endpoint|NCHAR|TAG|taosadpater endpoint|
|request\_method|NCHAR|TAG|request method|
|request\_uri|NCHAR|TAG|request uri|
### taosadapter\_system\_mem\_percent table
`taosadapter_system_mem_percent` table contains taosadapter memory usage information. The timestamp of this table is `_ts`.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|\_ts|TIMESTAMP||timestamp|
|guage|DOUBLE||metric value|
|endpoint|NCHAR|TAG|taosadpater endpoint|
### taosadapter\_system\_cpu\_percent table
`taosadapter_system_cpu_percent` table contains taosadapter cup usage information. The timestamp of this table is `_ts`.
|field|type|is\_tag|comment|
|:----|:---|:-----|:------|
|\_ts|TIMESTAMP||timestamp|
|guage|DOUBLE||mertic value|
|endpoint|NCHAR|TAG|taosadpater endpoint|

6
docs/en/14-reference/03-connector/03-cpp.mdx
View File

@ -423,6 +423,6 @@ In addition to writing data using the SQL method or the parameter binding API, w
**Description**
- The above seven interfaces are extension interfaces, which are mainly used to pass ttl and reqid parameters, and can be used as needed.
- Withing _raw interfaces represent data through the passed parameters lines and len. In order to solve the problem that the original interface data contains '\0' and is truncated. The totalRows pointer returns the number of parsed data rows.
- Withing _ttl interfaces can pass the ttl parameter to control the ttl expiration time of the table.
- Withing _reqid interfaces can track the entire call chain by passing the reqid parameter.
- Within _raw interfaces represent data through the passed parameters lines and len. In order to solve the problem that the original interface data contains '\0' and is truncated. The totalRows pointer returns the number of parsed data rows.
- Within _ttl interfaces can pass the ttl parameter to control the ttl expiration time of the table.
- Within _reqid interfaces can track the entire call chain by passing the reqid parameter.

430
docs/en/14-reference/03-connector/04-java.mdx
View File

@ -36,23 +36,110 @@ REST connection supports all platforms that can run Java.
Please refer to [version support list](/reference/connector#version-support)
## Recent update logs
| taos-jdbcdriver version | major changes |
| :---------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------: |
| 3.2.1 | JDBC REST connection supports schemaless/prepareStatement over WebSocket |
| 3.2.0 | This version has been deprecated |
| 3.1.0 | JDBC REST connection supports subscription over WebSocket |
| 3.0.1 - 3.0.4 | fix the resultSet data is parsed incorrectly sometimes. 3.0.1 is compiled on JDK 11, you are advised to use other version in the JDK 8 environment |
| 3.0.0 | Support for TDengine 3.0 |
| 2.0.42 | fix wasNull interface return value in WebSocket connection |
| 2.0.41 | fix decode method of username and password in REST connection |
| 2.0.39 - 2.0.40 | Add REST connection/request timeout parameters |
| 2.0.38 | JDBC REST connections add bulk pull function |
| 2.0.37 | Support json tags |
| 2.0.36 | Support schemaless writing |
**Note**: adding `batchfetch` to the REST connection and setting it to true will enable the WebSocket connection.
### Handling exceptions
After an error is reported, the error message and error code can be obtained through SQLException.
```java
try (Statement statement = connection.createStatement()) {
// executeQuery
ResultSet resultSet = statement.executeQuery(sql);
// print result
printResult(resultSet);
} catch (SQLException e) {
System.out.println("ERROR Message: " + e.getMessage());
System.out.println("ERROR Code: " + e.getErrorCode());
e.printStackTrace();
}
```
There are four types of error codes that the JDBC connector can report:
- Error code of the JDBC driver itself (error code between 0x2301 and 0x2350),
- Error code of the native connection method (error code between 0x2351 and 0x2360)
- Error code of the consumer method (error code between 0x2371 and 0x2380)
- Error code of other TDengine function modules.
For specific error codes, please refer to.
| Error Code | Description | Suggested Actions |
| ---------- | --------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------- |
| 0x2301 | connection already closed | The connection has been closed, check the connection status, or recreate the connection to execute the relevant instructions. |
| 0x2302 | this operation is NOT supported currently! | The current interface does not support the connection. You can use another connection mode. |
| 0x2303 | invalid variables | The parameter is invalid. Check the interface specification and adjust the parameter type and size. |
| 0x2304 | statement is closed | The statement is closed. Check whether the statement is closed and used again, or whether the connection is normal. |
| 0x2305 | resultSet is closed | result set The result set is released. Check whether the result set is released and used again. |
| 0x2306 | Batch is empty! | prepare statement Add parameters and then execute batch. |
| 0x2307 | Can not issue data manipulation statements with executeQuery() | The update operation should use execute update(), not execute query(). |
| 0x2308 | Can not issue SELECT via executeUpdate() | The query operation should use execute query(), not execute update(). |
| 0x230d | parameter index out of range | The parameter is out of bounds. Check the proper range of the parameter. |
| 0x230e | connection already closed | The connection has been closed. Please check whether the connection is closed and used again, or whether the connection is normal. |
| 0x230f | unknown sql type in tdengine | Check the data type supported by TDengine. |
| 0x2310 | can't register JDBC-JNI driver | The native driver cannot be registered. Please check whether the url is correct. |
| 0x2312 | url is not set | Check whether the REST connection url is correct. |
| 0x2314 | numeric value out of range | Check that the correct interface is used for the numeric types in the obtained result set. |
| 0x2315 | unknown taos type in tdengine | Whether the correct TDengine data type is specified when converting the TDengine data type to the JDBC data type. |
| 0x2317 | | wrong request type was used in the REST connection. |
| 0x2318 | | data transmission exception occurred during the REST connection. Please check the network status and try again. |
| 0x2319 | user is required | The user name information is missing when creating the connection |
| 0x231a | password is required | Password information is missing when creating a connection |
| 0x231c | httpEntity is null, sql: | Execution exception occurred during the REST connection |
| 0x2350 | unknown error | Unknown exception, please return to the developer on github. |
| 0x2352 | Unsupported encoding | An unsupported character encoding set is specified under the native Connection. |
| 0x2353 | internal error of database, please see taoslog for more details | An error occurs when the prepare statement is executed on the native connection. Check the taos log to locate the fault. |
| 0x2354 | JNI connection is NULL | When the command is executed, the native Connection is closed. Check the connection to TDengine. |
| 0x2355 | JNI result set is NULL | The result set is abnormal. Please check the connection status and try again. |
| 0x2356 | invalid num of fields | The meta information of the result set obtained by the native connection does not match. |
| 0x2357 | empty sql string | Fill in the correct SQL for execution. |
| 0x2359 | JNI alloc memory failed, please see taoslog for more details | Memory allocation for the native connection failed. Check the taos log to locate the problem. |
| 0x2371 | consumer properties must not be null! | The parameter is empty when you create a subscription. Please fill in the correct parameter. |
| 0x2372 | configs contain empty key, failed to set consumer property | The parameter key contains a null value. Please enter the correct parameter. |
| 0x2373 | failed to set consumer property, | The parameter value contains a null value. Please enter the correct parameter. |
| 0x2375 | topic reference has been destroyed | The topic reference is released during the creation of the data subscription. Check the connection to TDengine. |
| 0x2376 | failed to set consumer topic, topic name is empty | During data subscription creation, the subscription topic name is empty. Check that the specified topic name is correct. |
| 0x2377 | consumer reference has been destroyed | The subscription data transfer channel has been closed. Please check the connection to TDengine. |
| 0x2378 | consumer create error | Failed to create a data subscription. Check the taos log according to the error message to locate the fault. |
| - | can't create connection with server within | Increase the connection time by adding the httpConnectTimeout parameter, or check the connection to the taos adapter. |
| - | failed to complete the task within the specified time | Increase the execution time by adding the messageWaitTimeout parameter, or check the connection to the taos adapter. |
- [TDengine Java Connector](https://github.com/taosdata/taos-connector-jdbc/blob/main/src/main/java/com/taosdata/jdbc/TSDBErrorNumbers.java)
<!-- - [TDengine_ERROR_CODE](../error-code) -->
## TDengine DataType vs. Java DataType
TDengine currently supports timestamp, number, character, Boolean type, and the corresponding type conversion with Java is as follows:
| TDengine DataType | JDBCType |
| ----------------- | ---------------------------------- |
| TIMESTAMP | java.sql.Timestamp |
| INT | java.lang.Integer |
| BIGINT | java.lang.Long |
| FLOAT | java.lang.Float |
| DOUBLE | java.lang.Double |
| SMALLINT | java.lang.Short |
| TINYINT | java.lang.Byte |
| BOOL | java.lang.Boolean |
| BINARY | byte array |
| NCHAR | java.lang.String |
| JSON | java.lang.String |
| TDengine DataType | JDBCType |
| ----------------- | ------------------ |
| TIMESTAMP | java.sql.Timestamp |
| INT | java.lang.Integer |
| BIGINT | java.lang.Long |
| FLOAT | java.lang.Float |
| DOUBLE | java.lang.Double |
| SMALLINT | java.lang.Short |
| TINYINT | java.lang.Byte |
| BOOL | java.lang.Boolean |
| BINARY | byte array |
| NCHAR | java.lang.String |
| JSON | java.lang.String |
**Note**: Only TAG supports JSON types
@ -82,7 +169,7 @@ Add following dependency in the `pom.xml` file of your Maven project:
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.0.0</version>
<version>3.2.1</version>
</dependency>
```
@ -97,7 +184,7 @@ cd taos-connector-jdbc
mvn clean install -Dmaven.test.skip=true
```
After you have compiled taos-jdbcdriver, the `taos-jdbcdriver-3.0.*-dist.jar` file is created in the target directory. The compiled JAR file is automatically stored in your local Maven repository.
After you have compiled taos-jdbcdriver, the `taos-jdbcdriver-3.2.*-dist.jar` file is created in the target directory. The compiled JAR file is automatically stored in your local Maven repository.
</TabItem>
</Tabs>
@ -227,7 +314,7 @@ In addition to getting the connection from the specified URL, you can use Proper
Note:
- The client parameter set in the application is process-level. If you want to update the parameters of the client, you need to restart the application. This is because the client parameter is a global parameter that takes effect only the first time the application is set.
- The following sample code is based on taos-jdbcdriver-3.0.0.
- The following sample code is based on taos-jdbcdriver-3.1.0.
```java
public Connection getConn() throws Exception{
@ -333,30 +420,6 @@ while(resultSet.next()){
> The query is consistent with operating a relational database. When using subscripts to get the contents of the returned fields, you have to start from 1. However, we recommend using the field names to get the values of the fields in the result set.
### Handling exceptions
After an error is reported, the error message and error code can be obtained through SQLException.
```java
try (Statement statement = connection.createStatement()) {
// executeQuery
ResultSet resultSet = statement.executeQuery(sql);
// print result
printResult(resultSet);
} catch (SQLException e) {
System.out.println("ERROR Message: " + e.getMessage());
System.out.println("ERROR Code: " + e.getErrorCode());
e.printStackTrace();
}
```
There are three types of error codes that the JDBC connector can report: - Error code of the JDBC driver itself (error code between 0x2301 and 0x2350), - Error code of the native connection method (error code between 0x2351 and 0x2400), and - Error code of other TDengine function modules.
For specific error codes, please refer to.
- [TDengine Java Connector](https://github.com/taosdata/taos-connector-jdbc/blob/main/src/main/java/com/taosdata/jdbc/TSDBErrorNumbers.java)
<!-- - [TDengine_ERROR_CODE](../error-code) -->
### Writing data via parameter binding
TDengine has significantly improved the bind APIs to support data writing (INSERT) scenarios. Writing data in this way avoids the resource consumption of SQL syntax parsing, resulting in significant write performance improvements in many cases.
@ -364,9 +427,12 @@ TDengine has significantly improved the bind APIs to support data writing (INSER
**Note:**
- JDBC REST connections do not currently support bind interface
- The following sample code is based on taos-jdbcdriver-3.0.0
- The following sample code is based on taos-jdbcdriver-3.2.1
- The setString method should be called for binary type data, and the setNString method should be called for nchar type data
- both setString and setNString require the user to declare the width of the corresponding column in the size parameter of the table definition
- Do not use `db.?` in prepareStatement when specify the database with the table name, should directly use `?`, then specify the database in setTableName, for example: `prepareStatement.setTableName("db.t1")`.
<Tabs defaultValue="native">
<TabItem value="native" label="native connection">
```java
public class ParameterBindingDemo {
@ -594,21 +660,7 @@ public class ParameterBindingDemo {
}
```
The methods to set TAGS values:
```java
public void setTagNull(int index, int type)
public void setTagBoolean(int index, boolean value)
public void setTagInt(int index, int value)
public void setTagByte(int index, byte value)
public void setTagShort(int index, short value)
public void setTagLong(int index, long value)
public void setTagTimestamp(int index, long value)
public void setTagFloat(int index, float value)
public void setTagDouble(int index, double value)
public void setTagString(int index, String value)
public void setTagNString(int index, String value)
```
**Note**: both setString and setNString require the user to declare the width of the corresponding column in the size parameter of the table definition
The methods to set VALUES columns:
@ -625,17 +677,203 @@ public void setString(int columnIndex, ArrayList<String> list, int size) throws
public void setNString(int columnIndex, ArrayList<String> list, int size) throws SQLException
```
</TabItem>
<TabItem value="ws" label="WebSocket connection">
```java
public class ParameterBindingDemo {
private static final String host = "127.0.0.1";
private static final Random random = new Random(System.currentTimeMillis());
private static final int BINARY_COLUMN_SIZE = 30;
private static final String[] schemaList = {
"create table stable1(ts timestamp, f1 tinyint, f2 smallint, f3 int, f4 bigint) tags(t1 tinyint, t2 smallint, t3 int, t4 bigint)",
"create table stable2(ts timestamp, f1 float, f2 double) tags(t1 float, t2 double)",
"create table stable3(ts timestamp, f1 bool) tags(t1 bool)",
"create table stable4(ts timestamp, f1 binary(" + BINARY_COLUMN_SIZE + ")) tags(t1 binary(" + BINARY_COLUMN_SIZE + "))",
"create table stable5(ts timestamp, f1 nchar(" + BINARY_COLUMN_SIZE + ")) tags(t1 nchar(" + BINARY_COLUMN_SIZE + "))"
};
private static final int numOfSubTable = 10, numOfRow = 10;
public static void main(String[] args) throws SQLException {
String jdbcUrl = "jdbc:TAOS-RS://" + host + ":6041/?batchfetch=true";
Connection conn = DriverManager.getConnection(jdbcUrl, "root", "taosdata");
init(conn);
bindInteger(conn);
bindFloat(conn);
bindBoolean(conn);
bindBytes(conn);
bindString(conn);
conn.close();
}
private static void init(Connection conn) throws SQLException {
try (Statement stmt = conn.createStatement()) {
stmt.execute("drop database if exists test_ws_parabind");
stmt.execute("create database if not exists test_ws_parabind");
stmt.execute("use test_ws_parabind");
for (int i = 0; i < schemaList.length; i++) {
stmt.execute(schemaList[i]);
}
}
}
private static void bindInteger(Connection conn) throws SQLException {
String sql = "insert into ? using stable1 tags(?,?,?,?) values(?,?,?,?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t1_" + i);
// set tags
pstmt.setTagByte(1, Byte.parseByte(Integer.toString(random.nextInt(Byte.MAX_VALUE))));
pstmt.setTagShort(2, Short.parseShort(Integer.toString(random.nextInt(Short.MAX_VALUE))));
pstmt.setTagInt(3, random.nextInt(Integer.MAX_VALUE));
pstmt.setTagLong(4, random.nextLong());
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setByte(2, Byte.parseByte(Integer.toString(random.nextInt(Byte.MAX_VALUE))));
pstmt.setShort(3, Short.parseShort(Integer.toString(random.nextInt(Short.MAX_VALUE))));
pstmt.setInt(4, random.nextInt(Integer.MAX_VALUE));
pstmt.setLong(5, random.nextLong());
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindFloat(Connection conn) throws SQLException {
String sql = "insert into ? using stable2 tags(?,?) values(?,?,?)";
try(TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t2_" + i);
// set tags
pstmt.setTagFloat(1, random.nextFloat());
pstmt.setTagDouble(2, random.nextDouble());
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setFloat(2, random.nextFloat());
pstmt.setDouble(3, random.nextDouble());
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindBoolean(Connection conn) throws SQLException {
String sql = "insert into ? using stable3 tags(?) values(?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t3_" + i);
// set tags
pstmt.setTagBoolean(1, random.nextBoolean());
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setBoolean(2, random.nextBoolean());
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindBytes(Connection conn) throws SQLException {
String sql = "insert into ? using stable4 tags(?) values(?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t4_" + i);
// set tags
pstmt.setTagString(1, new String("abc"));
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setString(2, "abc");
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindString(Connection conn) throws SQLException {
String sql = "insert into ? using stable5 tags(?) values(?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t5_" + i);
// set tags
pstmt.setTagNString(1, "California.SanFrancisco");
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(0, new Timestamp(current + j));
pstmt.setNString(1, "California.SanFrancisco");
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
}
```
</TabItem>
</Tabs>
The methods to set TAGS values:
```java
public void setTagNull(int index, int type)
public void setTagBoolean(int index, boolean value)
public void setTagInt(int index, int value)
public void setTagByte(int index, byte value)
public void setTagShort(int index, short value)
public void setTagLong(int index, long value)
public void setTagTimestamp(int index, long value)
public void setTagFloat(int index, float value)
public void setTagDouble(int index, double value)
public void setTagString(int index, String value)
public void setTagNString(int index, String value)
```
### Schemaless Writing
TDengine supports schemaless writing. It is compatible with InfluxDB's Line Protocol, OpenTSDB's telnet line protocol, and OpenTSDB's JSON format protocol. For more information, see [Schemaless Writing](../../schemaless).
Note:
- JDBC REST connections do not currently support schemaless writes
- The following sample code is based on taos-jdbcdriver-3.0.0
<Tabs defaultValue="native">
<TabItem value="native" label="native connection">
```java
public class SchemalessInsertTest {
public class SchemalessJniTest {
private static final String host = "127.0.0.1";
private static final String lineDemo = "st,t1=3i64,t2=4f64,t3=\"t3\" c1=3i64,c3=L\"passit\",c2=false,c4=4f64 1626006833639000000";
private static final String telnetDemo = "stb0_0 1626006833 4 host=host0 interface=eth0";
@ -663,6 +901,41 @@ public class SchemalessInsertTest {
}
```
</TabItem>
<TabItem value="ws" label="WebSocket connection">
```java
public class SchemalessWsTest {
private static final String host = "127.0.0.1";
private static final String lineDemo = "st,t1=3i64,t2=4f64,t3=\"t3\" c1=3i64,c3=L\"passit\",c2=false,c4=4f64 1626006833639000000";
private static final String telnetDemo = "stb0_0 1626006833 4 host=host0 interface=eth0";
private static final String jsonDemo = "{\"metric\": \"meter_current\",\"timestamp\": 1626846400,\"value\": 10.3, \"tags\": {\"groupid\": 2, \"location\": \"California.SanFrancisco\", \"id\": \"d1001\"}}";
public static void main(String[] args) throws SQLException {
final String url = "jdbc:TAOS-RS://" + host + ":6041/?user=root&password=taosdata&batchfetch=true";
Connection connection = DriverManager.getConnection(url);
init(connection);
SchemalessWriter writer = new SchemalessWriter(connection, "test_ws_schemaless");
writer.write(lineDemo, SchemalessProtocolType.LINE, SchemalessTimestampType.NANO_SECONDS);
writer.write(telnetDemo, SchemalessProtocolType.TELNET, SchemalessTimestampType.MILLI_SECONDS);
writer.write(jsonDemo, SchemalessProtocolType.JSON, SchemalessTimestampType.SECONDS);
System.exit(0);
}
private static void init(Connection connection) throws SQLException {
try (Statement stmt = connection.createStatement()) {
stmt.executeUpdate("drop database if exists test_ws_schemaless");
stmt.executeUpdate("create database if not exists test_ws_schemaless keep 36500");
stmt.executeUpdate("use test_ws_schemaless");
}
}
}
```
</TabItem>
</Tabs>
### Data Subscription
The TDengine Java Connector supports subscription functionality with the following application API.
@ -706,8 +979,9 @@ TaosConsumer consumer = new TaosConsumer<>(config);
```java
while(true) {
ConsumerRecords<ResultBean> records = consumer.poll(Duration.ofMillis(100));
for (ResultBean record : records) {
process(record);
for (ConsumerRecord<ResultBean> record : records) {
ResultBean bean = record.value();
process(bean);
}
}
```
@ -760,8 +1034,9 @@ public abstract class ConsumerLoop {
while (!shutdown.get()) {
ConsumerRecords<ResultBean> records = consumer.poll(Duration.ofMillis(100));
for (ResultBean record : records) {
process(record);
for (ConsumerRecord<ResultBean> record : records) {
ResultBean bean = record.value();
process(bean);
}
}
consumer.unsubscribe();
@ -836,8 +1111,9 @@ public abstract class ConsumerLoop {
while (!shutdown.get()) {
ConsumerRecords<ResultBean> records = consumer.poll(Duration.ofMillis(100));
for (ResultBean record : records) {
process(record);
for (ConsumerRecord<ResultBean> record : records) {
ResultBean bean = record.value();
process(bean);
}
}
consumer.unsubscribe();
@ -963,20 +1239,6 @@ The source code of the sample application is under `TDengine/examples/JDBC`:
[JDBC example](https://github.com/taosdata/TDengine/tree/3.0/examples/JDBC)
## Recent update logs
| taos-jdbcdriver version | major changes |
| :---------------------: | :--------------------------------------------: |
| 3.1.0 | JDBC REST connection supports subscription over WebSocket |
| 3.0.1 - 3.0.4 | fix the resultSet data is parsed incorrectly sometimes. 3.0.1 is compiled on JDK 11, you are advised to use other version in the JDK 8 environment |
| 3.0.0 | Support for TDengine 3.0 |
| 2.0.42 | fix wasNull interface return value in WebSocket connection |
| 2.0.41 | fix decode method of username and password in REST connection |
| 2.0.39 - 2.0.40 | Add REST connection/request timeout parameters |
| 2.0.38 | JDBC REST connections add bulk pull function |
| 2.0.37 | Support json tags |
| 2.0.36 | Support schemaless writing |
## Frequently Asked Questions
1. Why is there no performance improvement when using Statement's `addBatch()` and `executeBatch()` to perform `batch data writing/update`?
@ -999,9 +1261,9 @@ The source code of the sample application is under `TDengine/examples/JDBC`:
4. java.lang.NoSuchMethodError: setByteArray
**Cause**: taos-jbdcdriver 3.* only supports TDengine 3.0 and later.
**Cause**: taos-jbdcdriver 3.\* only supports TDengine 3.0 and later.
**Solution**: Use taos-jdbcdriver 2.* with your TDengine 2.* deployment.
**Solution**: Use taos-jdbcdriver 2.\* with your TDengine 2.\* deployment.
5. java.lang.NoSuchMethodError: java.nio.ByteBuffer.position(I)Ljava/nio/ByteBuffer; ... taos-jdbcdriver-3.0.1.jar

5
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@ -11,6 +11,7 @@ import TabItem from '@theme/TabItem';
import Preparition from "./_preparation.mdx"
import RustInsert from "../../07-develop/03-insert-data/_rust_sql.mdx"
import RustBind from "../../07-develop/03-insert-data/_rust_stmt.mdx"
import RustSml from "../../07-develop/03-insert-data/_rust_schemaless.mdx"
import RustQuery from "../../07-develop/04-query-data/_rust.mdx"
[![Crates.io](https://img.shields.io/crates/v/taos)](https://crates.io/crates/taos) ![Crates.io](https://img.shields.io/crates/d/taos) [![docs.rs](https://img.shields.io/docsrs/taos)](https://docs.rs/taos)
@ -232,6 +233,10 @@ There are two ways to query data: Using built-in types or the [serde](https://se
<RustBind />
#### Schemaless Write
<RustSml />
### Query data
<RustQuery />

2
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View File

@ -62,7 +62,7 @@ The different database framework specifications for various programming language
| **Regular Query** | Support | Support | Support | Support | Support | Support |
| **Parameter Binding** | Not Supported | Not Supported | Support | Support | Not Supported | Support |
| **Subscription (TMQ) ** | Supported | Support | Support | Not Supported | Not Supported | Support |
| **Schemaless** | Not Supported | Not Supported | Not Supported | Not Supported | Not Supported | Not Supported |
| **Schemaless** | Supported | Not Supported | Not Supported | Not Supported | Not Supported | Not Supported |
| **Bulk Pulling (based on WebSocket) ** | Support | Support | Support | Support | Support | Support |
| **DataFrame** | Not Supported | Support | Not Supported | Not Supported | Not Supported | Not Supported |

1
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@ -76,6 +76,7 @@ Usage: taosdump [OPTION...] dbname [tbname ...]
-A, --all-databases Dump all databases.
-D, --databases=DATABASES Dump listed databases. Use comma to separate
database names.
-e, --escape-character Use escaped character for database name
-N, --without-property Dump database without its properties.
-s, --schemaonly Only dump table schemas.
-y, --answer-yes Input yes for prompt. It will skip data file

4
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View File

@ -12,8 +12,8 @@ After TDengine starts, it automatically writes many metrics in specific interval
To deploy TDinsight, we need
- a single-node TDengine server or a multi-node TDengine cluster and a [Grafana] server are required. This dashboard requires TDengine 3.0.1.0 and above, with the monitoring feature enabled. For detailed configuration, please refer to [TDengine monitoring configuration](../config/#monitoring-parameters).
- taosAdapter has been instaleld and running, please refer to [taosAdapter](../taosadapter).
- taosKeeper has been installed and running, please refer to [taosKeeper](../taoskeeper).
- taosAdapter has been installed and running, please refer to [taosAdapter](../taosadapter).
- taosKeeper has been installed and running, please refer to [taosKeeper](../taosKeeper).
Please record
- The endpoint of taosAdapter REST service, for example `http://tdengine.local:6041`

11
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View File

@ -358,6 +358,17 @@ The charset that takes effect is UTF-8.
| Value Range | 0-4096 |
| Default Value | 2x the CPU cores |
## Performance Tuning
### numOfCommitThreads
| Attribute | Description |
| ------------- | ----------------------------------- |
| Applicable | Server Only |
| Meaning | Maximum number of threads to commit |
| Value Range | 0-1024 |
| Default Value | |
## Log Parameters
### logDir

34
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@ -108,7 +108,7 @@ The following `launchctl` commands can help you manage taoskeeper service:
#### Launch With Configuration File
You can quickly launch taosKeeper with the following commands. If you do not specify a configuration file, `/etc/taos/keeper.toml` is used by default. If this file does not specify configurations, the default values are used.
You can quickly launch taosKeeper with the following commands. If you do not specify a configuration file, `/etc/taos/taoskeeper.toml` is used by default. If this file does not specify configurations, the default values are used.
```shell
$ taoskeeper -c <keeper config file>
@ -153,6 +153,10 @@ database = "log"
# standard tables to monitor
tables = ["normal_table"]
# database options for db storing metrics data
[metrics.databaseoptions]
cachemodel = "none"
```
### Obtain Monitoring Metrics
@ -203,7 +207,7 @@ taos_cluster_info_dnodes_total{cluster_id="5981392874047724755"} 1
taos_cluster_info_first_ep{cluster_id="5981392874047724755",value="hlb:6030"} 1
```
### check_health
### check\_health
```
$ curl -i http://127.0.0.1:6043/check_health
@ -219,3 +223,29 @@ Content-Length: 19
{"version":"1.0.0"}
```
### taoskeeper with Prometheus
There is `/metrics` api in taoskeeper provide TDengine metric data for Prometheus.
#### scrape config
Scrape config in Prometheus specifies a set of targets and parameters describing how to scrape metric data from endpoint. For more information, please reference to [Prometheus documents](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config).
```
# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
- job_name: "taoskeeper"
# metrics_path defaults to '/metrics'
# scheme defaults to 'http'.
static_configs:
- targets: ["localhost:6043"]
```
#### Dashboard
There is a dashboard named `TaosKeeper Prometheus Dashboard for 3.x`, which provides a monitoring dashboard similar to TInsight.
In Grafana, click the Dashboard menu and click `import`, enter the dashboard ID `18587` and click the `Load` button. Then finished importing `TaosKeeper Prometheus Dashboard for 3.x` dashboard.

17
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View File

@ -46,15 +46,14 @@ Execute in any directory:
````
curl -O http://packages.confluent.io/archive/7.1/confluent-7.1.1.tar.gz
tar xzf confluent-7.1.1.tar.gz -C /opt/test
tar xzf confluent-7.1.1.tar.gz -C /opt/
````
Then you need to add the `$CONFLUENT_HOME/bin` directory to the PATH.
```title=".profile"
export CONFLUENT_HOME=/opt/confluent-7.1.1
PATH=$CONFLUENT_HOME/bin
export PATH
export PATH=$CONFLUENT_HOME/bin:$PATH
```
Users can append the above script to the current user's profile file (~/.profile or ~/.bash_profile)
@ -329,7 +328,15 @@ DROP DATABASE IF EXISTS test;
CREATE DATABASE test;
USE test;
CREATE STABLE meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (location BINARY(64), groupId INT);
INSERT INTO d1001 USING meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:05.000',10.30000,219,0.31000) d1001 USING meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:15.000',12.60000,218,0.33000) d1001 USING meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:16.800',12.30000,221,0.31000) d1002 USING meters TAGS(California.SanFrancisco, 3) VALUES('2018-10-03 14:38:16.650',10.30000,218,0.25000) d1003 USING meters TAGS(California.LoSangeles, 2) VALUES('2018-10-03 14:38:05.500',11.80000,221,0.28000) d1003 USING meters TAGS(California.LoSangeles, 2) VALUES('2018-10-03 14:38:16.600',13.40000,223,0.29000) d1004 USING meters TAGS(California.LoSangeles, 3) VALUES('2018-10-03 14:38:05.000',10.80000,223,0.29000) d1004 USING meters TAGS(California.LoSangeles, 3) VALUES('2018-10-03 14:38:06.500',11.50000,221,0.35000);
INSERT INTO d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:05.000',10.30000,219,0.31000) \
d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:15.000',12.60000,218,0.33000) \
d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:16.800',12.30000,221,0.31000) \
d1002 USING meters TAGS('California.SanFrancisco', 3) VALUES('2018-10-03 14:38:16.650',10.30000,218,0.25000) \
d1003 USING meters TAGS('California.LosAngeles', 2) VALUES('2018-10-03 14:38:05.500',11.80000,221,0.28000) \
d1003 USING meters TAGS('California.LosAngeles', 2) VALUES('2018-10-03 14:38:16.600',13.40000,223,0.29000) \
d1004 USING meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 14:38:05.000',10.80000,223,0.29000) \
d1004 USING meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 14:38:06.500',11.50000,221,0.35000);
```
Use TDengine CLI to execute SQL script
@ -384,7 +391,7 @@ confluent local services connect connector status
You should now have two active connectors if you followed the previous steps. Use the following command to unload:
````
confluent local services connect connector unload TDengineSourceConnector
confluent local services connect connector unload TDengineSinkConnector
confluent local services connect connector unload TDengineSourceConnector
````

2
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@ -35,7 +35,7 @@ Please refer to the [official documentation](https://grafana.com/grafana/downloa
### TDengine
Download the latest TDengine-server from the [Downloads](http://tdengine.com/en/all-downloads/) page on the TAOSData website and install it.
Download and install the [latest version of TDengine](https://docs.tdengine.com/releases/tdengine/).
## Data Connection Setup

2
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@ -38,7 +38,7 @@ Please refer to the [official documentation](https://grafana.com/grafana/downloa
### Install TDengine
Download the latest TDengine-server from the [Downloads](http://tdengine.com/en/all-downloads/) page on the TAOSData website and install it.
Download and install the [latest version of TDengine](https://docs.tdengine.com/releases/tdengine/).
## Data Connection Setup

2
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@ -32,7 +32,7 @@ TDengine 3.0 is not compatible with the configuration and data files from previo
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).
5. For assistance in migrating data to TDengine 3.0, contact [TDengine Support](https://tdengine.com/support/).
### 2. How can I resolve the "Unable to establish connection" error?

4
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@ -10,6 +10,10 @@ For TDengine 2.x installation packages by version, please visit [here](https://w
import Release from "/components/ReleaseV3";
## 3.0.4.1
<Release type="tdengine" version="3.0.4.1" />
## 3.0.4.0
<Release type="tdengine" version="3.0.4.0" />

4
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@ -10,6 +10,10 @@ For other historical version installers, please visit [here](https://www.taosdat
import Release from "/components/ReleaseV3";
## 2.5.0
<Release type="tools" version="2.5.0" />
## 2.4.12
<Release type="tools" version="2.4.12" />

2
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@ -8,7 +8,7 @@
#include <sys/time.h>
#include <taos.h>
typedef int16_t VarDataLenT;
typedef uint16_t VarDataLenT;
#define TSDB_NCHAR_SIZE sizeof(int32_t)
#define VARSTR_HEADER_SIZE sizeof(VarDataLenT)

2
docs/examples/c/query_example.c
View File

@ -6,7 +6,7 @@
#include <string.h>
#include <taos.h>
typedef int16_t VarDataLenT;
typedef uint16_t VarDataLenT;
#define TSDB_NCHAR_SIZE sizeof(int32_t)
#define VARSTR_HEADER_SIZE sizeof(VarDataLenT)

2
docs/examples/java/pom.xml
View File

@ -22,7 +22,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.1.0</version>
<version>3.2.1</version>
</dependency>
<!-- ANCHOR_END: dep-->
<dependency>

4
docs/examples/java/src/main/java/com/taos/example/SubscribeDemo.java
View File

@ -1,5 +1,6 @@
package com.taos.example;
import com.taosdata.jdbc.tmq.ConsumerRecord;
import com.taosdata.jdbc.tmq.ConsumerRecords;
import com.taosdata.jdbc.tmq.TMQConstants;
import com.taosdata.jdbc.tmq.TaosConsumer;
@ -64,7 +65,8 @@ public class SubscribeDemo {
consumer.subscribe(Collections.singletonList(TOPIC));
while (!shutdown.get()) {
ConsumerRecords<Meters> meters = consumer.poll(Duration.ofMillis(100));
for (Meters meter : meters) {
for (ConsumerRecord<Meters> recode : meters) {
Meters meter = recode.value();
System.out.println(meter);
}
}

74
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@ -0,0 +1,74 @@
use taos_query::common::SchemalessPrecision;
use taos_query::common::SchemalessProtocol;
use taos_query::common::SmlDataBuilder;
use crate::AsyncQueryable;
use crate::AsyncTBuilder;
use crate::TaosBuilder;
async fn put_json() -> anyhow::Result<()> {
// std::env::set_var("RUST_LOG", "taos=trace");
std::env::set_var("RUST_LOG", "taos=debug");
pretty_env_logger::init();
let dsn =
std::env::var("TDENGINE_ClOUD_DSN").unwrap_or("http://localhost:6041".to_string());
log::debug!("dsn: {:?}", &dsn);
let client = TaosBuilder::from_dsn(dsn)?.build().await?;
let db = "demo_schemaless_ws";
client.exec(format!("drop database if exists {db}")).await?;
client
.exec(format!("create database if not exists {db}"))
.await?;
// should specify database before insert
client.exec(format!("use {db}")).await?;
// SchemalessProtocol::Json
let data = [
r#"[{"metric": "meters.current", "timestamp": 1681345954000, "value": 10.3, "tags": {"location": "California.SanFrancisco", "groupid": 2}}, {"metric": "meters.voltage", "timestamp": 1648432611249, "value": 219, "tags": {"location": "California.LosAngeles", "groupid": 1}}, {"metric": "meters.current", "timestamp": 1648432611250, "value": 12.6, "tags": {"location": "California.SanFrancisco", "groupid": 2}}, {"metric": "meters.voltage", "timestamp": 1648432611250, "value": 221, "tags": {"location": "California.LosAngeles", "groupid": 1}}]"#
]
.map(String::from)
.to_vec();
// demo with all fields
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Json)
.precision(SchemalessPrecision::Millisecond)
.data(data.clone())
.ttl(1000)
.req_id(300u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default precision
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Json)
.data(data.clone())
.ttl(1000)
.req_id(301u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default ttl
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Json)
.data(data.clone())
.req_id(302u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default req_id
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Json)
.data(data.clone())
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
client.exec(format!("drop database if exists {db}")).await?;
Ok(())
}

78
docs/examples/rust/nativeexample/examples/schemaless_insert_line.rs Normal file
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@ -0,0 +1,78 @@
use taos_query::common::SchemalessPrecision;
use taos_query::common::SchemalessProtocol;
use taos_query::common::SmlDataBuilder;
use crate::AsyncQueryable;
use crate::AsyncTBuilder;
use crate::TaosBuilder;
async fn put_line() -> anyhow::Result<()> {
// std::env::set_var("RUST_LOG", "taos=trace");
std::env::set_var("RUST_LOG", "taos=debug");
pretty_env_logger::init();
let dsn =
std::env::var("TDENGINE_ClOUD_DSN").unwrap_or("http://localhost:6041".to_string());
log::debug!("dsn: {:?}", &dsn);
let client = TaosBuilder::from_dsn(dsn)?.build().await?;
let db = "demo_schemaless_ws";
client.exec(format!("drop database if exists {db}")).await?;
client
.exec(format!("create database if not exists {db}"))
.await?;
// should specify database before insert
client.exec(format!("use {db}")).await?;
let data = [
"measurement,host=host1 field1=2i,field2=2.0 1577837300000",
"measurement,host=host1 field1=2i,field2=2.0 1577837400000",
"measurement,host=host1 field1=2i,field2=2.0 1577837500000",
"measurement,host=host1 field1=2i,field2=2.0 1577837600000",
]
.map(String::from)
.to_vec();
// demo with all fields
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Line)
.precision(SchemalessPrecision::Millisecond)
.data(data.clone())
.ttl(1000)
.req_id(100u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default ttl
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Line)
.precision(SchemalessPrecision::Millisecond)
.data(data.clone())
.req_id(101u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default ttl and req_id
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Line)
.precision(SchemalessPrecision::Millisecond)
.data(data.clone())
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default precision
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Line)
.data(data)
.req_id(103u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
client.exec(format!("drop database if exists {db}")).await?;
Ok(())
}

80
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@ -0,0 +1,80 @@
use taos_query::common::SchemalessPrecision;
use taos_query::common::SchemalessProtocol;
use taos_query::common::SmlDataBuilder;
use crate::AsyncQueryable;
use crate::AsyncTBuilder;
use crate::TaosBuilder;
async fn put_telnet() -> anyhow::Result<()> {
// std::env::set_var("RUST_LOG", "taos=trace");
std::env::set_var("RUST_LOG", "taos=debug");
pretty_env_logger::init();
let dsn =
std::env::var("TDENGINE_ClOUD_DSN").unwrap_or("http://localhost:6041".to_string());
log::debug!("dsn: {:?}", &dsn);
let client = TaosBuilder::from_dsn(dsn)?.build().await?;
let db = "demo_schemaless_ws";
client.exec(format!("drop database if exists {db}")).await?;
client
.exec(format!("create database if not exists {db}"))
.await?;
// should specify database before insert
client.exec(format!("use {db}")).await?;
let data = [
"meters.current 1648432611249 10.3 location=California.SanFrancisco group=2",
"meters.current 1648432611250 12.6 location=California.SanFrancisco group=2",
"meters.current 1648432611249 10.8 location=California.LosAngeles group=3",
"meters.current 1648432611250 11.3 location=California.LosAngeles group=3",
"meters.voltage 1648432611249 219 location=California.SanFrancisco group=2",
"meters.voltage 1648432611250 218 location=California.SanFrancisco group=2",
"meters.voltage 1648432611249 221 location=California.LosAngeles group=3",
"meters.voltage 1648432611250 217 location=California.LosAngeles group=3",
]
.map(String::from)
.to_vec();
// demo with all fields
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Telnet)
.precision(SchemalessPrecision::Millisecond)
.data(data.clone())
.ttl(1000)
.req_id(200u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default precision
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Telnet)
.data(data.clone())
.ttl(1000)
.req_id(201u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default ttl
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Telnet)
.data(data.clone())
.req_id(202u64)
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
// demo with default req_id
let sml_data = SmlDataBuilder::default()
.protocol(SchemalessProtocol::Telnet)
.data(data.clone())
.build()?;
assert_eq!(client.put(&sml_data).await?, ());
client.exec(format!("drop database if exists {db}")).await?;
Ok(())
}

5
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@ -100,7 +100,8 @@ sudo apt-get install tdengine
:::tip
apt-get 方式只适用于 Debian 或 Ubuntu 系统。
::::
:::
</TabItem>
<TabItem label="Windows 安装" value="windows">
@ -206,6 +207,8 @@ Active: inactive (dead)
- 查看服务状态：`sudo launchctl list | grep taosd`
- 查看服务详细信息：`launchctl print system/com.tdengine.taosd`
:::info
- `launchctl` 命令管理`com.tdengine.taosd`需要管理员权限，务必在前面加 `sudo` 来增强安全性。

2
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View File

@ -38,7 +38,7 @@ meters,location=California.LosAngeles,groupid=2 current=13.4,voltage=223,phase=0
- field_set 中的每个数据项都需要对自身的数据类型进行描述, 比如 1.2f32 代表 FLOAT 类型的数值 1.2, 如果不带类型后缀会被当作 DOUBLE 处理;
- timestamp 支持多种时间精度。写入数据的时候需要用参数指定时间精度，支持从小时到纳秒的 6 种时间精度。
- 为了提高写入的效率，默认假设同一个超级表中 field_set 的顺序是一样的（第一条数据包含所有的 field，后面的数据按照这个顺序），如果顺序不一样，需要配置参数 smlDataFormat 为 false，否则，数据写入按照相同顺序写入，库中数据会异常。（3.0.1.3 之后的版本 smlDataFormat 默认为 false，从3.0.3.0开始，该配置废弃） [TDengine 无模式写入参考指南](/reference/schemaless/#无模式写入行协议)
- 默认产生的子表名是根据规则生成的唯一 ID 值。用户也可以通过在 taos.cfg 里配置 smlChildTableName 参数来指定某个标签值作为子表名。该标签值应该具有全局唯一性。举例如下：假设有个标签名为tname, 配置 smlChildTableName=tname, 插入数据为 st,tname=cpu1,t1=4 c1=3 1626006833639000000 则创建的子表名为 cpu1。注意如果多行数据 tname 相同，但是后面的 tag_set 不同，则使用第一行自动建表时指定的 tag_set，其他的行会忽略）。[TDengine 无模式写入参考指南](/reference/schemaless/#无模式写入行协议)
- 默认产生的子表名是根据规则生成的唯一 ID 值。用户也可以通过在client端的 taos.cfg 里配置 smlChildTableName 参数来指定某个标签值作为子表名。该标签值应该具有全局唯一性。举例如下：假设有个标签名为tname, 配置 smlChildTableName=tname, 插入数据为 st,tname=cpu1,t1=4 c1=3 1626006833639000000 则创建的子表名为 cpu1。注意如果多行数据 tname 相同，但是后面的 tag_set 不同，则使用第一行自动建表时指定的 tag_set，其他的行会忽略）。[TDengine 无模式写入参考指南](/reference/schemaless/#无模式写入行协议)
:::
要了解更多可参考：[InfluxDB Line 协议官方文档](https://docs.influxdata.com/influxdb/v2.0/reference/syntax/line-protocol/) 和 [TDengine 无模式写入参考指南](/reference/schemaless/#无模式写入行协议)

2
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@ -32,7 +32,7 @@ OpenTSDB 行协议同样采用一行字符串来表示一行数据。OpenTSDB
meters.current 1648432611250 11.3 location=California.LosAngeles groupid=3
```
- 默认生产的子表名是根据规则生成的唯一 ID 值。用户也可以通过在 taos.cfg 里配置 smlChildTableName 参数来指定某个标签值作为子表名。该标签值应该具有全局唯一性。举例如下：假设有个标签名为tname, 配置 smlChildTableName=tname, 插入数据为 meters.current 1648432611250 11.3 tname=cpu1 location=California.LosAngeles groupid=3 则创建的表名为 cpu1，注意如果多行数据 tname 相同，但是后面的 tag_set 不同，则使用第一行自动建表时指定的 tag_set，其他的行会忽略）。
- 默认生产的子表名是根据规则生成的唯一 ID 值。用户也可以通过在client端的 taos.cfg 里配置 smlChildTableName 参数来指定某个标签值作为子表名。该标签值应该具有全局唯一性。举例如下：假设有个标签名为tname, 配置 smlChildTableName=tname, 插入数据为 meters.current 1648432611250 11.3 tname=cpu1 location=California.LosAngeles groupid=3 则创建的表名为 cpu1，注意如果多行数据 tname 相同，但是后面的 tag_set 不同，则使用第一行自动建表时指定的 tag_set，其他的行会忽略）。
参考 [OpenTSDB Telnet API 文档](http://opentsdb.net/docs/build/html/api_telnet/put.html)。
## 示例代码

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@ -47,7 +47,7 @@ OpenTSDB JSON 格式协议采用一个 JSON 字符串表示一行或多行数据
:::note
- 对于 JSON 格式协议，TDengine 并不会自动把所有标签转成 NCHAR 类型， 字符串将将转为 NCHAR 类型， 数值将同样转换为 DOUBLE 类型。
- 默认生成的子表名是根据规则生成的唯一 ID 值。用户也可以通过在 taos.cfg 里配置 smlChildTableName 参数来指定某个标签值作为子表名。该标签值应该具有全局唯一性。举例如下：假设有个标签名为tname, 配置 smlChildTableName=tname, 插入数据为 `"tags": { "host": "web02","dc": "lga","tname":"cpu1"}` 则创建的子表名为 cpu1。注意如果多行数据 tname 相同，但是后面的 tag_set 不同，则使用第一行自动建表时指定的 tag_set，其他的行会忽略）。
- 默认生成的子表名是根据规则生成的唯一 ID 值。用户也可以通过在client端的 taos.cfg 里配置 smlChildTableName 参数来指定某个标签值作为子表名。该标签值应该具有全局唯一性。举例如下：假设有个标签名为tname, 配置 smlChildTableName=tname, 插入数据为 `"tags": { "host": "web02","dc": "lga","tname":"cpu1"}` 则创建的子表名为 cpu1。注意如果多行数据 tname 相同，但是后面的 tag_set 不同，则使用第一行自动建表时指定的 tag_set，其他的行会忽略）。
:::
## 示例代码

3
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@ -0,0 +1,3 @@
```rust
{{#include docs/examples/rust/nativeexample/examples/schemaless_insert_line.rs}}
```

9
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@ -25,7 +25,8 @@ import CDemo from "./_sub_c.mdx";
本文档不对消息队列本身的基础知识做介绍，如果需要了解，请自行搜索。
注意：默认是从wal消费数据，如果wal被删除，消费到的数据会不全，此时可以将参数 experimental.snapshot.enable 设置为true，从tsdb获取全部数据，但是这样的话就不能保证数据的消费顺序。所以建议根据自己的消费情况合理的设置wal的保留策略，保证可以从wal里订阅到全部数据。
注意：数据订阅是从 WAL 消费数据，如果一些 WAL 文件被基于 WAL 保留策略删除，则已经删除的 WAL 文件中的数据就无法再消费到。需要根据业务需要在创建数据库时合理设置 `WAL_RETENTION_PERIOD` 或 `WAL_RETENTION_SIZE` ，并确保应用及时消费数据，这样才不会产生数据丢失的现象。数据订阅的行为与 Kafka 等广泛使用的消息队列类产品的行为相似。
## 主要数据结构和 API
不同语言下， TMQ 订阅相关的 API 及数据结构如下：
@ -221,7 +222,7 @@ void Close()
```sql
DROP DATABASE IF EXISTS tmqdb;
CREATE DATABASE tmqdb;
CREATE DATABASE tmqdb WAL_RETENTION_PERIOD 3600;
CREATE TABLE tmqdb.stb (ts TIMESTAMP, c1 INT, c2 FLOAT, c3 VARCHAR(16)) TAGS(t1 INT, t3 VARCHAR(16));
CREATE TABLE tmqdb.ctb0 USING tmqdb.stb TAGS(0, "subtable0");
CREATE TABLE tmqdb.ctb1 USING tmqdb.stb TAGS(1, "subtable1");
@ -293,7 +294,6 @@ CREATE TOPIC topic_name AS DATABASE db_name;
| `auto.offset.reset` | enum | 消费组订阅的初始位置 | <br />`earliest`: default;从头开始订阅; <br/>`latest`: 仅从最新数据开始订阅; <br/>`none`: 没有提交的 offset 无法订阅 |
| `enable.auto.commit` | boolean | 是否启用消费位点自动提交，true: 自动提交，客户端应用无需commit；false：客户端应用需要自行commit | 默认值为 true |
| `auto.commit.interval.ms` | integer | 消费记录自动提交消费位点时间间隔，单位为毫秒 | 默认值为 5000 |
| `experimental.snapshot.enable` | boolean | 是否允许从 TSDB 消费数据。当其关闭时，只能消费依据 WAL 保留策略仍然在WAL中的数据；当其打开时，除WAL中的数据以外，也能够消费已经从WAL中删除但落盘到TSDB中的数据 | 实验功能，默认关闭 |
| `msg.with.table.name` | boolean | 是否允许从消息中解析表名, 不适用于列订阅（列订阅时可将 tbname 作为列写入 subquery 语句） |默认关闭 |
对于不同编程语言，其设置方式如下：
@ -311,7 +311,6 @@ tmq_conf_set(conf, "group.id", "cgrpName");
tmq_conf_set(conf, "td.connect.user", "root");
tmq_conf_set(conf, "td.connect.pass", "taosdata");
tmq_conf_set(conf, "auto.offset.reset", "earliest");
tmq_conf_set(conf, "experimental.snapshot.enable", "true");
tmq_conf_set(conf, "msg.with.table.name", "true");
tmq_conf_set_auto_commit_cb(conf, tmq_commit_cb_print, NULL);
@ -367,7 +366,6 @@ conf := &tmq.ConfigMap{
"td.connect.port": "6030",
"client.id": "test_tmq_c",
"enable.auto.commit": "false",
"experimental.snapshot.enable": "true",
"msg.with.table.name": "true",
}
consumer, err := NewConsumer(conf)
@ -417,7 +415,6 @@ consumer = Consumer({"group.id": "local", "td.connect.ip": "127.0.0.1"})
| `enable.auto.commit` | string | 启用自动提交 | 合法值：`true`, `false` |
| `auto.commit.interval.ms` | string | 以毫秒为单位的自动提交时间间隔 | 默认值：5000 ms |
| `auto.offset.reset` | string | 消费组订阅的初始位置 | 可选：`earliest`(default), `latest`, `none` |
| `experimental.snapshot.enable` | string | 是否允许从 TSDB 消费数据 | 合法值：`true`, `false` |
</TabItem>

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@ -6,18 +6,20 @@ description: "支持用户编码的聚合函数和标量函数，在查询中嵌
在有些应用场景中，应用逻辑需要的查询无法直接使用系统内置的函数来表示。利用 UDF(User Defined Function) 功能，TDengine 可以插入用户编写的处理代码并在查询中使用它们，就能够很方便地解决特殊应用场景中的使用需求。 UDF 通常以数据表中的一列数据做为输入，同时支持以嵌套子查询的结果作为输入。
TDengine 支持通过 C/C++ 语言进行 UDF 定义。接下来结合示例讲解 UDF 的使用方法。
用户可以通过 UDF 实现两类函数：标量函数和聚合函数。标量函数对每行数据输出一个值，如求绝对值 abs，正弦函数 sin，字符串拼接函数 concat 等。聚合函数对多行数据进行输出一个值，如求平均数 avg，最大值 max 等。
实现 UDF 时，需要实现规定的接口函数
TDengine 支持通过 C/Python 语言进行 UDF 定义。接下来结合示例讲解 UDF 的使用方法。
## 用 C 语言实现 UDF
使用 C 语言实现 UDF 时，需要实现规定的接口函数
- 标量函数需要实现标量接口函数 scalarfn 。
- 聚合函数需要实现聚合接口函数 aggfn_start ， aggfn ， aggfn_finish。
- 如果需要初始化，实现 udf_init；如果需要清理工作，实现udf_destroy。
接口函数的名称是 UDF 名称，或者是 UDF 名称和特定后缀（_start, _finish, _init, _destroy)的连接。列表中的scalarfn，aggfn, udf需要替换成udf函数名。
## 实现标量函数
### 用 C 语言实现标量函数
标量函数实现模板如下
```c
#include "taos.h"
@ -49,7 +51,7 @@ int32_t scalarfn_destroy() {
```
scalarfn 为函数名的占位符，需要替换成函数名，如bit_and。
## 实现聚合函数
### 用 C 语言实现聚合函数
聚合函数的实现模板如下
```c
@ -100,7 +102,7 @@ int32_t aggfn_destroy() {
```
aggfn为函数名的占位符，需要修改为自己的函数名，如l2norm。
## 接口函数定义
### C 语言 UDF 接口函数定义
接口函数的名称是 udf 名称，或者是 udf 名称和特定后缀（_start, _finish, _init, _destroy)的连接。以下描述中函数名称中的 scalarfn，aggfn, udf 需要替换成udf函数名。
@ -108,7 +110,7 @@ aggfn为函数名的占位符，需要修改为自己的函数名，如l2norm。
接口函数参数类型见数据结构定义。
### 标量接口函数
#### 标量函数接口
`int32_t scalarfn(SUdfDataBlock* inputDataBlock, SUdfColumn *resultColumn)`
@ -118,7 +120,7 @@ aggfn为函数名的占位符，需要修改为自己的函数名，如l2norm。
- inputDataBlock: 输入的数据块
- resultColumn: 输出列
### 聚合接口函数
#### 聚合函数接口
`int32_t aggfn_start(SUdfInterBuf *interBuf)`
@ -135,7 +137,7 @@ aggfn为函数名的占位符，需要修改为自己的函数名，如l2norm。
- result：最终结果。
### UDF 初始化和销毁
#### 初始化和销毁接口
`int32_t udf_init()`
`int32_t udf_destroy()`
@ -143,7 +145,7 @@ aggfn为函数名的占位符，需要修改为自己的函数名，如l2norm。
其中 udf 是函数名的占位符。udf_init 完成初始化工作。 udf_destroy 完成清理工作。如果没有初始化工作，无需定义udf_init函数。如果没有清理工作，无需定义udf_destroy函数。
## UDF 数据结构
### C 语言 UDF 数据结构
```c
typedef struct SUdfColumnMeta {
int16_t type;
@ -201,7 +203,7 @@ typedef struct SUdfInterBuf {
为了更好的操作以上数据结构，提供了一些便利函数，定义在 taosudf.h。
## 编译 UDF
### 编译 C UDF
用户定义函数的 C 语言源代码无法直接被 TDengine 系统使用，而是需要先编译为 动态链接库，之后才能载入 TDengine 系统。
@ -213,12 +215,9 @@ gcc -g -O0 -fPIC -shared bit_and.c -o libbitand.so
这样就准备好了动态链接库 libbitand.so 文件，可以供后文创建 UDF 时使用了。为了保证可靠的系统运行，编译器 GCC 推荐使用 7.5 及以上版本。
## 管理和使用UDF
编译好的UDF，还需要将其加入到系统才能被正常的SQL调用。关于如何管理和使用UDF，参见[UDF使用说明](../12-taos-sql/26-udf.md)
### C UDF 示例代码
## 示例代码
### 标量函数示例 [bit_and](https://github.com/taosdata/TDengine/blob/develop/tests/script/sh/bit_and.c)
#### 标量函数示例 [bit_and](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/bit_and.c)
bit_add 实现多列的按位与功能。如果只有一列，返回这一列。bit_add 忽略空值。
@ -231,7 +230,7 @@ bit_add 实现多列的按位与功能。如果只有一列，返回这一列。
</details>
### 聚合函数示例1 返回值为数值类型 [l2norm](https://github.com/taosdata/TDengine/blob/develop/tests/script/sh/l2norm.c)
#### 聚合函数示例1 返回值为数值类型 [l2norm](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/l2norm.c)
l2norm 实现了输入列的所有数据的二阶范数，即对每个数据先平方，再累加求和，最后开方。
@ -244,7 +243,7 @@ l2norm 实现了输入列的所有数据的二阶范数，即对每个数据先
</details>
### 聚合函数示例2 返回值为字符串类型 [max_vol](https://github.com/taosdata/TDengine/blob/develop/tests/script/sh/max_vol.c)
#### 聚合函数示例2 返回值为字符串类型 [max_vol](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/max_vol.c)
max_vol 实现了从多个输入的电压列中找到最大电压，返回由设备ID + 最大电压所在（行，列）+ 最大电压值 组成的组合字符串值
@ -268,4 +267,125 @@ select max_vol(vol1,vol2,vol3,deviceid) from battery;
{{#include tests/script/sh/max_vol.c}}
```
</details>
</details>
## 用 Python 语言实现 UDF
使用 Python 语言实现 UDF 时，需要实现规定的接口函数
- 标量函数需要实现标量接口函数 process 。
- 聚合函数需要实现聚合接口函数 start ，reduce ，finish。
- 如果需要初始化，实现 init；如果需要清理工作，实现 destroy。
### 用 Python 实现标量函数
标量函数实现模版如下
```Python
def init():
# initialization
def destroy():
# destroy
def process(input: datablock) -> tuple[output_type]:
# process input datablock,
# datablock.data(row, col) is to access the python object in location(row,col)
# return tuple object consisted of object of type outputtype
```
### 用 Python 实现聚合函数
聚合函数实现模版如下
```Python
def init():
#initialization
def destroy():
#destroy
def start() -> bytes:
#return serialize(init_state)
def reduce(inputs: datablock, buf: bytes) -> bytes
# deserialize buf to state
# reduce the inputs and state into new_state.
# use inputs.data(i,j) to access python ojbect of location(i,j)
# serialize new_state into new_state_bytes
return new_state_bytes
def finish(buf: bytes) -> output_type:
#return obj of type outputtype
```
### Python UDF 接口函数定义
#### 标量函数接口
```Python
def process(input: datablock) -> tuple[output_type]:
```
- input:datablock 类似二维矩阵，通过成员方法 data(row,col)返回位于 row 行，col 列的 python 对象
- 返回值是一个 Python 对象元组，每个元素类型为输出类型。
#### 聚合函数接口
```Python
def start() -> bytes:
def reduce(inputs: datablock, buf: bytes) -> bytes
def finish(buf: bytes) -> output_type:
```
首先调用 start 生成最初结果 buffer，然后输入数据会被分为多个行数据块，对每个数据块 inputs 和当前中间结果 buf 调用 reduce，得到新的中间结果，最后再调用 finish 从中间结果 buf 产生最终输出，最终输出只能含 0 或 1 条数据。
#### 初始化和销毁接口
```Python
def init()
def destroy()
```
其中 init 完成初始化工作。 destroy 完成清理工作。如果没有初始化工作，无需定义 init 函数。如果没有清理工作，无需定义 destroy 函数。
### Python 和 TDengine之间的数据类型映射
下表描述了TDengine SQL数据类型和Python数据类型的映射。任何类型的NULL值都映射成Python的None值。
| **TDengine SQL数据类型** | **Python数据类型** |
| :-----------------------: | ------------ |
|TINYINT / SMALLINT / INT / BIGINT | int |
|TINYINT UNSIGNED / SMALLINT UNSIGNED / INT UNSIGNED / BIGINT UNSIGNED | int |
|FLOAT / DOUBLE | float |
|BOOL | bool |
|BINARY / VARCHAR / NCHAR | bytes|
|TIMESTAMP | int |
|JSON and other types | 不支持 |
### Python UDF 环境的安装
1. 安装 taospyudf 包。此包执行Python UDF程序。
```bash
sudo pip install taospyudf
ldconfig
```
2. 如果 Python UDF 程序执行时，通过 PYTHONPATH 引用其它的包，可以设置 taos.cfg 的 UdfdLdLibPath 变量为PYTHONPATH的内容
### Python UDF 示例代码
#### 标量函数示例 [pybitand](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/pybitand.py)
pybitand 实现多列的按位与功能。如果只有一列，返回这一列。pybitand 忽略空值。
<details>
<summary>pybitand.py</summary>
```Python
{{#include tests/script/sh/pybitand.py}}
```
</details>
#### 聚合函数示例 [pyl2norm](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/pyl2norm.py)
pyl2norm 实现了输入列的所有数据的二阶范数，即对每个数据先平方，再累加求和，最后开方。
<details>
<summary>pyl2norm.py</summary>
```c
{{#include tests/script/sh/pyl2norm.py}}
```
</details>
## 管理和使用 UDF
在使用 UDF 之前需要先将其加入到 TDengine 系统中。关于如何管理和使用 UDF，请参考[管理和使用 UDF](../12-taos-sql/26-udf.md)

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@ -36,23 +36,110 @@ REST 连接支持所有能运行 Java 的平台。
请参考[版本支持列表](../#版本支持)
## 最近更新记录
| taos-jdbcdriver 版本 | 主要变化 |
| :------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------: |
| 3.2.1 | 新增功能：WebSocket 连接支持 schemaless 与 prepareStatement 写入。变更：consumer poll 返回结果集为 ConsumerRecord，可通过 value() 获取指定结果集数据。 |
| 3.2.0 | 存在连接问题，不推荐使用 |
| 3.1.0 | WebSocket 连接支持订阅功能 |
| 3.0.1 - 3.0.4 | 修复一些情况下结果集数据解析错误的问题。3.0.1 在 JDK 11 环境编译，JDK 8 环境下建议使用其他版本 |
| 3.0.0 | 支持 TDengine 3.0 |
| 2.0.42 | 修在 WebSocket 连接中 wasNull 接口返回值 |
| 2.0.41 | 修正 REST 连接中用户名和密码转码方式 |
| 2.0.39 - 2.0.40 | 增加 REST 连接/请求 超时设置 |
| 2.0.38 | JDBC REST 连接增加批量拉取功能 |
| 2.0.37 | 增加对 json tag 支持 |
| 2.0.36 | 增加对 schemaless 写入支持 |
**注**：REST 连接中增加 `batchfetch` 参数并设置为 true，将开启 WebSocket 连接。
## 处理异常
在报错后，通过 SQLException 可以获取到错误的信息和错误码：
```java
try (Statement statement = connection.createStatement()) {
// executeQuery
ResultSet resultSet = statement.executeQuery(sql);
// print result
printResult(resultSet);
} catch (SQLException e) {
System.out.println("ERROR Message: " + e.getMessage());
System.out.println("ERROR Code: " + e.getErrorCode());
e.printStackTrace();
}
```
JDBC 连接器可能报错的错误码包括 4 种：
- JDBC driver 本身的报错（错误码在 0x2301 到 0x2350 之间）
- 原生连接方法的报错（错误码在 0x2351 到 0x2360 之间）
- 数据订阅的报错（错误码在 0x2371 到 0x2380 之间）
- TDengine 其他功能模块的报错。
具体的错误码请参考：
| Error Code | Description | Suggested Actions |
| ---------- | --------------------------------------------------------------- | --------------------------------------------------------------------------------------- |
| 0x2301 | connection already closed | 连接已经关闭，检查连接情况，或重新创建连接去执行相关指令。 |
| 0x2302 | this operation is NOT supported currently! | 当前使用接口不支持，可以更换其他连接方式。 |
| 0x2303 | invalid variables | 参数不合法，请检查相应接口规范，调整参数类型及大小。 |
| 0x2304 | statement is closed | statement 已经关闭，请检查 statement 是否关闭后再次使用，或是连接是否正常。 |
| 0x2305 | resultSet is closed | resultSet 结果集已经释放，请检查 resultSet 是否释放后再次使用。 |
| 0x2306 | Batch is empty! | prepareStatement 添加参数后再执行 executeBatch。 |
| 0x2307 | Can not issue data manipulation statements with executeQuery() | 更新操作应该使用 executeUpdate()，而不是 executeQuery()。 |
| 0x2308 | Can not issue SELECT via executeUpdate() | 查询操作应该使用 executeQuery()，而不是 executeUpdate()。 |
| 0x230d | parameter index out of range | 参数越界，请检查参数的合理范围。 |
| 0x230e | connection already closed | 连接已经关闭，请检查 Connection 是否关闭后再次使用，或是连接是否正常。 |
| 0x230f | unknown sql type in tdengine | 请检查 TDengine 支持的 Data Type 类型。 |
| 0x2310 | can't register JDBC-JNI driver | 不能注册 JNI 驱动，请检查 url 是否填写正确。 |
| 0x2312 | url is not set | 请检查 REST 连接 url 是否填写正确。 |
| 0x2314 | numeric value out of range | 请检查获取结果集中数值类型是否使用了正确的接口。 |
| 0x2315 | unknown taos type in tdengine | 在 TDengine 数据类型与 JDBC 数据类型转换时，是否指定了正确的 TDengine 数据类型。 |
| 0x2317 | | REST 连接中使用了错误的请求类型。 |
| 0x2318 | | REST 连接中出现了数据传输异常，请检查网络情况并重试。 |
| 0x2319 | user is required | 创建连接时缺少用户名信息 |
| 0x231a | password is required | 创建连接时缺少密码信息 |
| 0x231c | httpEntity is null, sql: | REST 连接中执行出现异常 |
| 0x2350 | unknown error | 未知异常，请在 github 反馈给开发人员。 |
| 0x2352 | Unsupported encoding | 本地连接下指定了不支持的字符编码集 |
| 0x2353 | internal error of database, please see taoslog for more details | 本地连接执行 prepareStatement 时出现错误，请检查 taos log 进行问题定位。 |
| 0x2354 | JNI connection is NULL | 本地连接执行命令时，Connection 已经关闭。请检查与 TDengine 的连接情况。 |
| 0x2355 | JNI result set is NULL | 本地连接获取结果集，结果集异常，请检查连接情况，并重试。 |
| 0x2356 | invalid num of fields | 本地连接获取结果集的 meta 信息不匹配。 |
| 0x2357 | empty sql string | 填写正确的 SQL 进行执行。 |
| 0x2359 | JNI alloc memory failed, please see taoslog for more details | 本地连接分配内存错误，请检查 taos log 进行问题定位。 |
| 0x2371 | consumer properties must not be null! | 创建订阅时参数为空，请填写正确的参数。 |
| 0x2372 | configs contain empty key, failed to set consumer property | 参数 key 中包含空值，请填写正确的参数。 |
| 0x2373 | failed to set consumer property, | 参数 value 中包含空值，请填写正确的参数。 |
| 0x2375 | topic reference has been destroyed | 创建数据订阅过程中，topic 引用被释放。请检查与 TDengine 的连接情况。 |
| 0x2376 | failed to set consumer topic, topic name is empty | 创建数据订阅过程中，订阅 topic 名称为空。请检查指定的 topic 名称是否填写正确。 |
| 0x2377 | consumer reference has been destroyed | 订阅数据传输通道已经关闭，请检查与 TDengine 的连接情况。 |
| 0x2378 | consumer create error | 创建数据订阅失败，请根据错误信息检查 taos log 进行问题定位。 |
| - | can't create connection with server within | 通过增加参数 httpConnectTimeout 增加连接耗时，或是请检查与 taosAdapter 之间的连接情况。 |
| - | failed to complete the task within the specified time | 通过增加参数 messageWaitTimeout 增加执行耗时，或是请检查与 taosAdapter 之间的连接情况。 |
- [TDengine Java Connector](https://github.com/taosdata/taos-connector-jdbc/blob/main/src/main/java/com/taosdata/jdbc/TSDBErrorNumbers.java)
<!-- - [TDengine_ERROR_CODE](../error-code) -->
## TDengine DataType 和 Java DataType
TDengine 目前支持时间戳、数字、字符、布尔类型，与 Java 对应类型转换如下：
| TDengine DataType | JDBCType |
| ----------------- | ---------------------------------- |
| TIMESTAMP | java.sql.Timestamp |
| INT | java.lang.Integer |
| BIGINT | java.lang.Long |
| FLOAT | java.lang.Float |
| DOUBLE | java.lang.Double |
| SMALLINT | java.lang.Short |
| TINYINT | java.lang.Byte |
| BOOL | java.lang.Boolean |
| BINARY | byte array |
| NCHAR | java.lang.String |
| JSON | java.lang.String |
| TDengine DataType | JDBCType |
| ----------------- | ------------------ |
| TIMESTAMP | java.sql.Timestamp |
| INT | java.lang.Integer |
| BIGINT | java.lang.Long |
| FLOAT | java.lang.Float |
| DOUBLE | java.lang.Double |
| SMALLINT | java.lang.Short |
| TINYINT | java.lang.Byte |
| BOOL | java.lang.Boolean |
| BINARY | byte array |
| NCHAR | java.lang.String |
| JSON | java.lang.String |
**注意**：JSON 类型仅在 tag 中支持。
@ -82,7 +169,7 @@ Maven 项目中，在 pom.xml 中添加以下依赖：
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.0.0</version>
<version>3.2.1</version>
</dependency>
```
@ -97,7 +184,7 @@ cd taos-connector-jdbc
mvn clean install -Dmaven.test.skip=true
```
编译后，在 target 目录下会产生 taos-jdbcdriver-3.0.*-dist.jar 的 jar 包，并自动将编译的 jar 文件放在本地的 Maven 仓库中。
编译后，在 target 目录下会产生 taos-jdbcdriver-3.2.\*-dist.jar 的 jar 包，并自动将编译的 jar 文件放在本地的 Maven 仓库中。
</TabItem>
</Tabs>
@ -230,7 +317,7 @@ INSERT INTO test.t1 USING test.weather (ts, temperature) TAGS('California.SanFra
**注意**：
- 应用中设置的 client parameter 为进程级别的，即如果要更新 client 的参数，需要重启应用。这是因为 client parameter 是全局参数，仅在应用程序的第一次设置生效。
- 以下示例代码基于 taos-jdbcdriver-3.0.0。
- 以下示例代码基于 taos-jdbcdriver-3.1.0。
```java
public Connection getConn() throws Exception{
@ -272,7 +359,7 @@ properties 中的配置参数如下：
- TSDBDriver.HTTP_SOCKET_TIMEOUT: socket 超时时间，单位 ms，默认值为 5000。仅在 REST 连接且 batchfetch 设置为 false 时生效。
- TSDBDriver.PROPERTY_KEY_MESSAGE_WAIT_TIMEOUT: 消息超时时间, 单位 ms， 默认值为 3000。 仅在 REST 连接且 batchfetch 设置为 true 时生效。
- TSDBDriver.PROPERTY_KEY_USE_SSL: 连接中是否使用 SSL。仅在 REST 连接时生效。
此外对 JDBC 原生连接，通过指定 URL 和 Properties 还可以指定其他参数，比如日志级别、SQL 长度等。更多详细配置请参考[客户端配置](/reference/config/#仅客户端适用)。
此外对 JDBC 原生连接，通过指定 URL 和 Properties 还可以指定其他参数，比如日志级别、SQL 长度等。更多详细配置请参考[客户端配置](/reference/config/#仅客户端适用)。
### 配置参数的优先级
@ -336,30 +423,6 @@ while(resultSet.next()){
> 查询和操作关系型数据库一致，使用下标获取返回字段内容时从 1 开始，建议使用字段名称获取。
### 处理异常
在报错后，通过 SQLException 可以获取到错误的信息和错误码：
```java
try (Statement statement = connection.createStatement()) {
// executeQuery
ResultSet resultSet = statement.executeQuery(sql);
// print result
printResult(resultSet);
} catch (SQLException e) {
System.out.println("ERROR Message: " + e.getMessage());
System.out.println("ERROR Code: " + e.getErrorCode());
e.printStackTrace();
}
```
JDBC 连接器可能报错的错误码包括 3 种：JDBC driver 本身的报错（错误码在 0x2301 到 0x2350 之间），原生连接方法的报错（错误码在 0x2351 到 0x2400 之间），TDengine 其他功能模块的报错。
具体的错误码请参考：
- [TDengine Java Connector](https://github.com/taosdata/taos-connector-jdbc/blob/main/src/main/java/com/taosdata/jdbc/TSDBErrorNumbers.java)
<!-- - [TDengine_ERROR_CODE](../error-code) -->
### 通过参数绑定写入数据
TDengine 的 JDBC 原生连接实现大幅改进了参数绑定方式对数据写入（INSERT）场景的支持。采用这种方式写入数据时，能避免 SQL 语法解析的资源消耗，从而在很多情况下显著提升写入性能。
@ -367,9 +430,12 @@ TDengine 的 JDBC 原生连接实现大幅改进了参数绑定方式对数据
**注意**：
- JDBC REST 连接目前不支持参数绑定
- 以下示例代码基于 taos-jdbcdriver-3.0.0
- 以下示例代码基于 taos-jdbcdriver-3.2.1
- binary 类型数据需要调用 setString 方法，nchar 类型数据需要调用 setNString 方法
- setString 和 setNString 都要求用户在 size 参数里声明表定义中对应列的列宽
- 预处理语句中指定数据库与子表名称不要使用 `db.?`，应直接使用 `?`，然后在 setTableName 中指定数据库，如：`prepareStatement.setTableName("db.t1")`。
<Tabs defaultValue="native">
<TabItem value="native" label="原生连接">
```java
public class ParameterBindingDemo {
@ -597,21 +663,7 @@ public class ParameterBindingDemo {
}
```
用于设定 TAGS 取值的方法总共有：
```java
public void setTagNull(int index, int type)
public void setTagBoolean(int index, boolean value)
public void setTagInt(int index, int value)
public void setTagByte(int index, byte value)
public void setTagShort(int index, short value)
public void setTagLong(int index, long value)
public void setTagTimestamp(int index, long value)
public void setTagFloat(int index, float value)
public void setTagDouble(int index, double value)
public void setTagString(int index, String value)
public void setTagNString(int index, String value)
```
**注**：setString 和 setNString 都要求用户在 size 参数里声明表定义中对应列的列宽
用于设定 VALUES 数据列的取值的方法总共有：
@ -628,17 +680,203 @@ public void setString(int columnIndex, ArrayList<String> list, int size) throws
public void setNString(int columnIndex, ArrayList<String> list, int size) throws SQLException
```
</TabItem>
<TabItem value="rest" label="WebSocket 连接">
```java
public class ParameterBindingDemo {
private static final String host = "127.0.0.1";
private static final Random random = new Random(System.currentTimeMillis());
private static final int BINARY_COLUMN_SIZE = 30;
private static final String[] schemaList = {
"create table stable1(ts timestamp, f1 tinyint, f2 smallint, f3 int, f4 bigint) tags(t1 tinyint, t2 smallint, t3 int, t4 bigint)",
"create table stable2(ts timestamp, f1 float, f2 double) tags(t1 float, t2 double)",
"create table stable3(ts timestamp, f1 bool) tags(t1 bool)",
"create table stable4(ts timestamp, f1 binary(" + BINARY_COLUMN_SIZE + ")) tags(t1 binary(" + BINARY_COLUMN_SIZE + "))",
"create table stable5(ts timestamp, f1 nchar(" + BINARY_COLUMN_SIZE + ")) tags(t1 nchar(" + BINARY_COLUMN_SIZE + "))"
};
private static final int numOfSubTable = 10, numOfRow = 10;
public static void main(String[] args) throws SQLException {
String jdbcUrl = "jdbc:TAOS-RS://" + host + ":6041/?batchfetch=true";
Connection conn = DriverManager.getConnection(jdbcUrl, "root", "taosdata");
init(conn);
bindInteger(conn);
bindFloat(conn);
bindBoolean(conn);
bindBytes(conn);
bindString(conn);
conn.close();
}
private static void init(Connection conn) throws SQLException {
try (Statement stmt = conn.createStatement()) {
stmt.execute("drop database if exists test_ws_parabind");
stmt.execute("create database if not exists test_ws_parabind");
stmt.execute("use test_ws_parabind");
for (int i = 0; i < schemaList.length; i++) {
stmt.execute(schemaList[i]);
}
}
}
private static void bindInteger(Connection conn) throws SQLException {
String sql = "insert into ? using stable1 tags(?,?,?,?) values(?,?,?,?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t1_" + i);
// set tags
pstmt.setTagByte(1, Byte.parseByte(Integer.toString(random.nextInt(Byte.MAX_VALUE))));
pstmt.setTagShort(2, Short.parseShort(Integer.toString(random.nextInt(Short.MAX_VALUE))));
pstmt.setTagInt(3, random.nextInt(Integer.MAX_VALUE));
pstmt.setTagLong(4, random.nextLong());
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setByte(2, Byte.parseByte(Integer.toString(random.nextInt(Byte.MAX_VALUE))));
pstmt.setShort(3, Short.parseShort(Integer.toString(random.nextInt(Short.MAX_VALUE))));
pstmt.setInt(4, random.nextInt(Integer.MAX_VALUE));
pstmt.setLong(5, random.nextLong());
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindFloat(Connection conn) throws SQLException {
String sql = "insert into ? using stable2 tags(?,?) values(?,?,?)";
try(TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t2_" + i);
// set tags
pstmt.setTagFloat(1, random.nextFloat());
pstmt.setTagDouble(2, random.nextDouble());
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setFloat(2, random.nextFloat());
pstmt.setDouble(3, random.nextDouble());
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindBoolean(Connection conn) throws SQLException {
String sql = "insert into ? using stable3 tags(?) values(?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t3_" + i);
// set tags
pstmt.setTagBoolean(1, random.nextBoolean());
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setBoolean(2, random.nextBoolean());
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindBytes(Connection conn) throws SQLException {
String sql = "insert into ? using stable4 tags(?) values(?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t4_" + i);
// set tags
pstmt.setTagString(1, new String("abc"));
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(1, new Timestamp(current + j));
pstmt.setString(2, "abc");
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
private static void bindString(Connection conn) throws SQLException {
String sql = "insert into ? using stable5 tags(?) values(?,?)";
try (TSWSPreparedStatement pstmt = conn.prepareStatement(sql).unwrap(TSWSPreparedStatement.class)) {
for (int i = 1; i <= numOfSubTable; i++) {
// set table name
pstmt.setTableName("t5_" + i);
// set tags
pstmt.setTagNString(1, "California.SanFrancisco");
// set columns
long current = System.currentTimeMillis();
for (int j = 0; j < numOfRow; j++) {
pstmt.setTimestamp(0, new Timestamp(current + j));
pstmt.setNString(1, "California.SanFrancisco");
pstmt.addBatch();
}
pstmt.executeBatch();
}
}
}
}
```
</TabItem>
</Tabs>
用于设定 TAGS 取值的方法总共有：
```java
public void setTagNull(int index, int type)
public void setTagBoolean(int index, boolean value)
public void setTagInt(int index, int value)
public void setTagByte(int index, byte value)
public void setTagShort(int index, short value)
public void setTagLong(int index, long value)
public void setTagTimestamp(int index, long value)
public void setTagFloat(int index, float value)
public void setTagDouble(int index, double value)
public void setTagString(int index, String value)
public void setTagNString(int index, String value)
```
### 无模式写入
TDengine 支持无模式写入功能。无模式写入兼容 InfluxDB 的 行协议（Line Protocol）、OpenTSDB 的 telnet 行协议和 OpenTSDB 的 JSON 格式协议。详情请参见[无模式写入](../../reference/schemaless/)。
**注意**：
- JDBC REST 连接目前不支持无模式写入
- 以下示例代码基于 taos-jdbcdriver-3.0.0
<Tabs defaultValue="native">
<TabItem value="native" label="原生连接">
```java
public class SchemalessInsertTest {
public class SchemalessJniTest {
private static final String host = "127.0.0.1";
private static final String lineDemo = "st,t1=3i64,t2=4f64,t3=\"t3\" c1=3i64,c3=L\"passit\",c2=false,c4=4f64 1626006833639000000";
private static final String telnetDemo = "stb0_0 1626006833 4 host=host0 interface=eth0";
@ -666,6 +904,41 @@ public class SchemalessInsertTest {
}
```
</TabItem>
<TabItem value="ws" label="WebSocket 连接">
```java
public class SchemalessWsTest {
private static final String host = "127.0.0.1";
private static final String lineDemo = "st,t1=3i64,t2=4f64,t3=\"t3\" c1=3i64,c3=L\"passit\",c2=false,c4=4f64 1626006833639000000";
private static final String telnetDemo = "stb0_0 1626006833 4 host=host0 interface=eth0";
private static final String jsonDemo = "{\"metric\": \"meter_current\",\"timestamp\": 1626846400,\"value\": 10.3, \"tags\": {\"groupid\": 2, \"location\": \"California.SanFrancisco\", \"id\": \"d1001\"}}";
public static void main(String[] args) throws SQLException {
final String url = "jdbc:TAOS-RS://" + host + ":6041/?user=root&password=taosdata&batchfetch=true";
Connection connection = DriverManager.getConnection(url);
init(connection);
SchemalessWriter writer = new SchemalessWriter(connection, "test_ws_schemaless");
writer.write(lineDemo, SchemalessProtocolType.LINE, SchemalessTimestampType.NANO_SECONDS);
writer.write(telnetDemo, SchemalessProtocolType.TELNET, SchemalessTimestampType.MILLI_SECONDS);
writer.write(jsonDemo, SchemalessProtocolType.JSON, SchemalessTimestampType.SECONDS);
System.exit(0);
}
private static void init(Connection connection) throws SQLException {
try (Statement stmt = connection.createStatement()) {
stmt.executeUpdate("drop database if exists test_ws_schemaless");
stmt.executeUpdate("create database if not exists test_ws_schemaless keep 36500");
stmt.executeUpdate("use test_ws_schemaless");
}
}
}
```
</TabItem>
</Tabs>
### 数据订阅
TDengine Java 连接器支持订阅功能，应用 API 如下：
@ -702,15 +975,16 @@ TaosConsumer consumer = new TaosConsumer<>(config);
- td.connect.type: 连接方式。jni：表示使用动态库连接的方式，ws/WebSocket：表示使用 WebSocket 进行数据通信。默认为 jni 方式。
- httpConnectTimeout：创建连接超时参数，单位 ms，默认为 5000 ms。仅在 WebSocket 连接下有效。
- messageWaitTimeout：数据传输超时参数，单位 ms，默认为 10000 ms。仅在 WebSocket 连接下有效。
其他参数请参考：[Consumer 参数列表](../../../develop/tmq#创建-consumer-以及consumer-group)
其他参数请参考：[Consumer 参数列表](../../../develop/tmq#创建-consumer-以及consumer-group)
#### 订阅消费数据
```java
while(true) {
ConsumerRecords<ResultBean> records = consumer.poll(Duration.ofMillis(100));
for (ResultBean record : records) {
process(record);
for (ConsumerRecord<ResultBean> record : records) {
ResultBean bean = record.value();
process(bean);
}
}
```
@ -761,8 +1035,9 @@ public abstract class ConsumerLoop {
while (!shutdown.get()) {
ConsumerRecords<ResultBean> records = consumer.poll(Duration.ofMillis(100));
for (ResultBean record : records) {
process(record);
for (ConsumerRecord<ResultBean> record : records) {
ResultBean bean = record.value();
process(bean);
}
}
consumer.unsubscribe();
@ -839,8 +1114,9 @@ public abstract class ConsumerLoop {
while (!shutdown.get()) {
ConsumerRecords<ResultBean> records = consumer.poll(Duration.ofMillis(100));
for (ResultBean record : records) {
process(record);
for (ConsumerRecord<ResultBean> record : records) {
ResultBean bean = record.value();
process(bean);
}
}
consumer.unsubscribe();
@ -966,20 +1242,6 @@ public static void main(String[] args) throws Exception {
请参考：[JDBC example](https://github.com/taosdata/TDengine/tree/3.0/examples/JDBC)
## 最近更新记录
| taos-jdbcdriver 版本 | 主要变化 |
| :------------------: | :----------------------------: |
| 3.1.0 | WebSocket 连接支持订阅功能 |
| 3.0.1 - 3.0.4 | 修复一些情况下结果集数据解析错误的问题。3.0.1 在 JDK 11 环境编译，JDK 8 环境下建议使用其他版本 |
| 3.0.0 | 支持 TDengine 3.0 |
| 2.0.42 | 修在 WebSocket 连接中 wasNull 接口返回值 |
| 2.0.41 | 修正 REST 连接中用户名和密码转码方式 |
| 2.0.39 - 2.0.40 | 增加 REST 连接/请求 超时设置 |
| 2.0.38 | JDBC REST 连接增加批量拉取功能 |
| 2.0.37 | 增加对 json tag 支持 |
| 2.0.36 | 增加对 schemaless 写入支持 |
## 常见问题
1. 使用 Statement 的 `addBatch()` 和 `executeBatch()` 来执行“批量写入/更新”，为什么没有带来性能上的提升？
@ -1002,9 +1264,9 @@ public static void main(String[] args) throws Exception {
4. java.lang.NoSuchMethodError: setByteArray
**原因**：taos-jdbcdriver 3.* 版本仅支持 TDengine 3.0 及以上版本。
**原因**：taos-jdbcdriver 3.\* 版本仅支持 TDengine 3.0 及以上版本。
**解决方法**： 使用 taos-jdbcdriver 2.* 版本连接 TDengine 2.* 版本。
**解决方法**： 使用 taos-jdbcdriver 2.\* 版本连接 TDengine 2.\* 版本。
5. java.lang.NoSuchMethodError: java.nio.ByteBuffer.position(I)Ljava/nio/ByteBuffer; ... taos-jdbcdriver-3.0.1.jar

5
docs/zh/08-connector/26-rust.mdx
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@ -10,6 +10,7 @@ import TabItem from '@theme/TabItem';
import Preparation from "./_preparation.mdx"
import RustInsert from "../07-develop/03-insert-data/_rust_sql.mdx"
import RustBind from "../07-develop/03-insert-data/_rust_stmt.mdx"
import RustSml from "../07-develop/03-insert-data/_rust_schemaless.mdx"
import RustQuery from "../07-develop/04-query-data/_rust.mdx"
[![Crates.io](https://img.shields.io/crates/v/taos)](https://crates.io/crates/taos) ![Crates.io](https://img.shields.io/crates/d/taos) [![docs.rs](https://img.shields.io/docsrs/taos)](https://docs.rs/taos)
@ -230,6 +231,10 @@ async fn demo(taos: &Taos, db: &str) -> Result<(), Error> {
<RustBind />
#### Schemaless 写入
<RustSml />
### 查询数据
<RustQuery />

2
docs/zh/08-connector/index.md
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@ -61,7 +61,7 @@ TDengine 版本更新往往会增加新的功能特性，列表中的连接器
| **普通查询** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **参数绑定** | 暂不支持 | 暂不支持 | 支持 | 支持 | 暂不支持 | 支持 |
| **数据订阅（TMQ）** | 支持 | 支持 | 支持 | 暂不支持 | 暂不支持 | 支持 |
| **Schemaless** | 暂不支持 | 暂不支持 | 暂不支持 | 暂不支持 | 暂不支持 | 暂不支持 |
| **Schemaless** | 支持 | 暂不支持 | 暂不支持 | 暂不支持 | 暂不支持 | 暂不支持 |
| **批量拉取（基于 WebSocket）** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **DataFrame** | 不支持 | 支持 | 不支持 | 不支持 | 不支持 | 不支持 |

4
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@ -71,8 +71,8 @@ database_option: {
- 0：表示可以创建多张超级表。
- 1：表示只可以创建一张超级表。
- STT_TRIGGER：表示落盘文件触发文件合并的个数。默认为 1，范围 1 到 16。对于少表高频场景，此参数建议使用默认配置，或较小的值；而对于多表低频场景，此参数建议配置较大的值。
- TABLE_PREFIX：内部存储引擎根据表名分配存储该表数据的 VNODE 时要忽略的前缀的长度。
- TABLE_SUFFIX：内部存储引擎根据表名分配存储该表数据的 VNODE 时要忽略的后缀的长度。
- TABLE_PREFIX：当其为正值时，在决定把一个表分配到哪个 vgroup 时要忽略表名中指定长度的前缀；当其为负值时，在决定把一个表分配到哪个 vgroup 时只使用表名中指定长度的前缀；例如，假定表名为 "v30001"，当 TSDB_PREFIX = 2 时 使用 "0001" 来决定分配到哪个 vgroup ，当 TSDB_PREFIX = -2 时使用 "v3" 来决定分配到哪个 vgroup
- TABLE_SUFFIX：当其为正值时，在决定把一个表分配到哪个 vgroup 时要忽略表名中指定长度的后缀；当其为负值时，在决定把一个表分配到哪个 vgroup 时只使用表名中指定长度的后缀；例如，假定表名为 "v30001"，当 TSDB_SUFFIX = 2 时 使用 "v300" 来决定分配到哪个 vgroup ，当 TSDB_SUFFIX = -2 时使用 "01" 来决定分配到哪个 vgroup。
- TSDB_PAGESIZE：一个 VNODE 中时序数据存储引擎的页大小，单位为 KB，默认为 4 KB。范围为 1 到 16384，即 1 KB到 16 MB。
- WAL_RETENTION_PERIOD: 为了数据订阅消费，需要WAL日志文件额外保留的最大时长策略。WAL日志清理，不受订阅客户端消费状态影响。单位为 s。默认为 0，表示无需为订阅保留。新建订阅，应先设置恰当的时长策略。
- WAL_RETENTION_SIZE：为了数据订阅消费，需要WAL日志文件额外保留的最大累计大小策略。单位为 KB。默认为 0，表示累计大小无上限。

2
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@ -33,7 +33,7 @@ column_definition:
SHOW STABLES [LIKE tb_name_wildcard];
```
查看数据库内全部 STable，及其相关信息，包括 STable 的名称、创建时间、列数量、标签（TAG）数量、通过该 STable 建表的数量。
查看数据库内全部超级表。
### 显示一个超级表的创建语句

2
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@ -55,7 +55,7 @@ window_clause: {
| INTERVAL(interval_val [, interval_offset]) [SLIDING (sliding_val)] [WATERMARK(watermark_val)] [FILL(fill_mod_and_val)]
interp_clause:
RANGE(ts_val, ts_val), EVERY(every_val), FILL(fill_mod_and_val)
RANGE(ts_val, ts_val) EVERY(every_val) FILL(fill_mod_and_val)
partition_by_clause:
PARTITION BY expr [, expr] ...

2
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@ -888,7 +888,7 @@ INTERP(expr)
- INTERP 的输出时间范围根据 RANGE(timestamp1,timestamp2)字段来指定，需满足 timestamp1 <= timestamp2。其中 timestamp1（必选值）为输出时间范围的起始值，即如果 timestamp1 时刻符合插值条件则 timestamp1 为输出的第一条记录，timestamp2（必选值）为输出时间范围的结束值，即输出的最后一条记录的 timestamp 不能大于 timestamp2。
- INTERP 根据 EVERY(time_unit) 字段来确定输出时间范围内的结果条数，即从 timestamp1 开始每隔固定长度的时间（time_unit 值）进行插值，time_unit 可取值时间单位：1a(毫秒)，1s(秒)，1m(分)，1h(小时)，1d(天)，1w(周)。例如 EVERY(500a) 将对于指定数据每500毫秒间隔进行一次插值.
- INTERP 根据 FILL 字段来决定在每个符合输出条件的时刻如何进行插值。关于 FILL 子句如何使用请参考 [FILL 子句](../distinguished/#fill-子句)
- INTERP 只能在一个时间序列内进行插值，因此当作用于超级表时必须跟 partition by tbname 一起使用。
- INTERP 作用于超级表时, 会将该超级表下的所有子表数据按照主键列排序后进行插值计算，也可以搭配 PARTITION BY tbname 使用，将结果强制规约到单个时间线。
- INTERP 可以与伪列 _irowts 一起使用，返回插值点所对应的时间戳(3.0.2.0版本以后支持)。
- INTERP 可以与伪列 _isfilled 一起使用，显示返回结果是否为原始记录或插值算法产生的数据(3.0.3.0版本以后支持)。

40
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@ -15,6 +15,7 @@ stream_options: {
IGNORE EXPIRED [0|1]
DELETE_MARK time
FILL_HISTORY [0|1]
IGNORE UPDATE [0|1]
}
```
@ -169,7 +170,7 @@ T3 时刻，最新事件到达，T 向后推移超过了第二个窗口关闭的
在 window_close 或 max_delay 模式下，窗口关闭直接影响推送结果。在 at_once 模式下，窗口关闭只与内存占用有关。
## 流式计算的过期数据处理策略
## 流式计算对于过期数据的处理策略
对于已关闭的窗口，再次落入该窗口中的数据被标记为过期数据.
@ -177,11 +178,20 @@ TDengine 对于过期数据提供两种处理方式，由 IGNORE EXPIRED 选项
1. 重新计算，即 IGNORE EXPIRED 0：从 TSDB 中重新查找对应窗口的所有数据并重新计算得到最新结果
2. 直接丢弃, 即 IGNORE EXPIRED 1：默认配置，忽略过期数据
2. 直接丢弃，即 IGNORE EXPIRED 1：默认配置，忽略过期数据
无论在哪种模式下，watermark 都应该被妥善设置，来得到正确结果（直接丢弃模式）或避免频繁触发重算带来的性能开销（重新计算模式）。
## 流式计算对于修改数据的处理策略
TDengine 对于修改数据提供两种处理方式，由 IGNORE UPDATE 选项指定：
1. 检查数据是否被修改，即 IGNORE UPDATE 0：默认配置，如果被修改，则重新计算对应窗口。
2. 不检查数据是否被修改，全部按增量数据计算，即 IGNORE UPDATE 1。
## 写入已存在的超级表
```sql
[field1_name,...]
@ -213,3 +223,29 @@ DELETE_MARK time
```
DELETE_MARK用于删除缓存的窗口状态，也就是删除流计算的中间结果。如果不设置，默认值是10年
T = 最新事件时间 - DELETE_MARK
## 流式计算支持的函数
1. 所有的 [单行函数](../function/#单行函数) 均可用于流计算。
2. 以下 19 个聚合/选择函数 <b>不能</b> 应用在创建流计算的 SQL 语句。此外的其他类型的函数均可用于流计算。
- [leastsquares](../function/#leastsquares)
- [percentile](../function/#percentile)
- [top](../function/#top)
- [bottom](../function/#bottom)
- [elapsed](../function/#elapsed)
- [interp](../function/#interp)
- [derivative](../function/#derivative)
- [irate](../function/#irate)
- [twa](../function/#twa)
- [histogram](../function/#histogram)
- [diff](../function/#diff)
- [statecount](../function/#statecount)
- [stateduration](../function/#stateduration)
- [csum](../function/#csum)
- [mavg](../function/#mavg)
- [sample](../function/#sample)
- [tail](../function/#tail)
- [unique](../function/#unique)
- [mode](../function/#mode)

4
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@ -120,6 +120,10 @@ TDengine 内置了一个名为 `INFORMATION_SCHEMA` 的数据库，提供对数
| 5 | create_time | TIMESTAMP | 创建时间 |
| 6 | code_len | INT | 代码长度 |
| 7 | bufsize | INT | buffer 大小 |
| 8 | func_language | BINARY(31) | 自定义函数编程语言 |
| 9 | func_body | BINARY(16384) | 函数体定义 |
| 10 | func_version | INT | 函数版本号。初始版本为0，每次替换更新，版本号加1。|
## INS_INDEXES

8
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@ -129,6 +129,14 @@ SHOW QNODES;
显示当前系统中 QNODE （查询节点）的信息。
## SHOW QUERIES
```sql
SHOW QUERIES;
```
显示当前系统中正在进行的查询。
## SHOW SCORES
```sql

30
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@ -13,27 +13,34 @@ description: 使用 UDF 的详细指南
- 创建标量函数
```sql
CREATE FUNCTION function_name AS library_path OUTPUTTYPE output_type;
CREATE [OR REPLACE] FUNCTION function_name AS library_path OUTPUTTYPE output_type [LANGUAGE 'C|Python'];
```
- function_name：标量函数未来在 SQL 中被调用时的函数名，必须与函数实现中 udf 的实际名称一致；
- library_path：包含 UDF 函数实现的动态链接库的库文件绝对路径（指的是库文件在当前客户端所在主机上的保存路径，通常是指向一个 .so 文件），这个路径需要用英文单引号或英文双引号括起来；
- OR REPLACE: 如果函数已经存在，会修改已有的函数属性。
- function_name：标量函数未来在 SQL 中被调用时的函数名；
- LANGUAGE 'C|Python'：函数编程语言，目前支持C语言和Python语言。 如果这个从句忽略，编程语言是C语言
- library_path：如果编程语言是C，路径是包含 UDF 函数实现的动态链接库的库文件绝对路径（指的是库文件在当前客户端所在主机上的保存路径，通常是指向一个 .so 文件）。如果编程语言是Python，路径是包含 UDF 函数实现的Python文件路径。这个路径需要用英文单引号或英文双引号括起来；
- output_type：此函数计算结果的数据类型名称；
例如，如下语句可以把 libbitand.so 创建为系统中可用的 UDF：
例如，如下语句可以把 libbitand.so 创建为系统中可用的 UDF：
```sql
CREATE FUNCTION bit_and AS "/home/taos/udf_example/libbitand.so" OUTPUTTYPE INT;
```
例如，使用以下语句可以修改已经定义的 bit_and 函数，输出类型是 BIGINT，使用Python语言实现。
```sql
CREATE OR REPLACE FUNCTION bit_and AS "/home/taos/udf_example/bit_and.py" OUTPUTTYPE BIGINT LANGUAGE 'Python';
```
- 创建聚合函数：
```sql
CREATE AGGREGATE FUNCTION function_name AS library_path OUTPUTTYPE output_type [ BUFSIZE buffer_size ];
CREATE [OR REPLACE] AGGREGATE FUNCTION function_name AS library_path OUTPUTTYPE output_type [ BUFSIZE buffer_size ] [LANGUAGE 'C|Python'];
```
- OR REPLACE: 如果函数已经存在，会修改已有的函数属性。
- function_name：聚合函数未来在 SQL 中被调用时的函数名，必须与函数实现中 udfNormalFunc 的实际名称一致；
- library_path：包含 UDF 函数实现的动态链接库的库文件绝对路径（指的是库文件在当前客户端所在主机上的保存路径，通常是指向一个 .so 文件），这个路径需要用英文单引号或英文双引号括起来；
- output_type：此函数计算结果的数据类型，与上文中 udfNormalFunc 的 itype 参数不同，这里不是使用数字表示法，而是直接写类型名称即可；
- LANGUAGE 'C|Python'：函数编程语言，目前支持C语言和Python语言。
- library_path：如果编程语言是C，路径是包含 UDF 函数实现的动态链接库的库文件绝对路径（指的是库文件在当前客户端所在主机上的保存路径，通常是指向一个 .so 文件）。如果编程语言是Python，路径是包含 UDF 函数实现的Python文件路径。这个路径需要用英文单引号或英文双引号括起来；；
- output_type：此函数计算结果的数据类型名称；
- buffer_size：中间计算结果的缓冲区大小，单位是字节。如果不使用可以不设置。
例如，如下语句可以把 libl2norm.so 创建为系统中可用的 UDF：
@ -41,6 +48,11 @@ CREATE AGGREGATE FUNCTION function_name AS library_path OUTPUTTYPE output_type [
```sql
CREATE AGGREGATE FUNCTION l2norm AS "/home/taos/udf_example/libl2norm.so" OUTPUTTYPE DOUBLE bufsize 8;
```
例如，使用以下语句可以修改已经定义的 l2norm 函数的缓冲区大小为64。
```sql
CREATE AGGREGATE FUNCTION l2norm AS "/home/taos/udf_example/libl2norm.so" OUTPUTTYPE DOUBLE bufsize 64;
```
关于如何开发自定义函数，请参考 [UDF使用说明](/develop/udf)。
## 管理 UDF

4
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@ -27,13 +27,13 @@ description: "TDengine 3.0 版本的语法变更说明"
| - | :------- | :-------- | :------- |
| 1 | ALTER ACCOUNT | 废除 | 2.x中为企业版功能，3.0不再支持。语法暂时保留了，执行报“This statement is no longer supported”错误。
| 2 | ALTER ALL DNODES | 新增 | 修改所有DNODE的参数。
| 3 | ALTER DATABASE | 调整 | 废除<ul><li>QUORUM：写入需要的副本确认数。3.0 版本默认行为是强一致性，且不支持修改为弱一致性。</li><li>BLOCKS：VNODE使用的内存块数。3.0版本使用BUFFER来表示VNODE写入内存池的大小。</li><li>UPDATE：更新操作的支持模式。3.0版本所有数据库都支持部分列更新。</li><li>CACHELAST：缓存最新一行数据的模式。3.0版本用CACHEMODEL代替。</li><li>COMP：3.0版本暂不支持修改。</li><br/>新增<li>CACHEMODEL：表示是否在内存中缓存子表的最近数据。</li><li>CACHESIZE：表示缓存子表最近数据的内存大小。</li><li>WAL_FSYNC_PERIOD：代替原FSYNC参数。</li><li>WAL_LEVEL：代替原WAL参数。</li><li>WAL_RETENTION_PERIOD：3.0.4.0版本新增，wal文件的额外保留策略，用于数据订阅。</li><li>WAL_RETENTION_SIZE：3.0.4.0版本新增，wal文件的额外保留策略，用于数据订阅。<br/>调整</li><li>REPLICA：3.0.0版本暂不支持修改。</li><li>KEEP：3.0版本新增支持带单位的设置方式。</li></ul>
| 3 | ALTER DATABASE | 调整 | <p>废除</p><ul><li>QUORUM：写入需要的副本确认数。3.0 版本默认行为是强一致性，且不支持修改为弱一致性。</li><li>BLOCKS：VNODE使用的内存块数。3.0版本使用BUFFER来表示VNODE写入内存池的大小。</li><li>UPDATE：更新操作的支持模式。3.0版本所有数据库都支持部分列更新。</li><li>CACHELAST：缓存最新一行数据的模式。3.0版本用CACHEMODEL代替。</li><li>COMP：3.0版本暂不支持修改。</li></ul><p>新增</p><ul><li>CACHEMODEL：表示是否在内存中缓存子表的最近数据。</li><li>CACHESIZE：表示缓存子表最近数据的内存大小。</li><li>WAL_FSYNC_PERIOD：代替原FSYNC参数。</li><li>WAL_LEVEL：代替原WAL参数。</li><li>WAL_RETENTION_PERIOD：3.0.4.0版本新增，wal文件的额外保留策略，用于数据订阅。</li><li>WAL_RETENTION_SIZE：3.0.4.0版本新增，wal文件的额外保留策略，用于数据订阅。</li></ul><p>调整</p><ul><li>KEEP：3.0版本新增支持带单位的设置方式。</li></ul>
| 4 | ALTER STABLE | 调整 | 废除<ul><li>CHANGE TAG：修改标签列的名称。3.0版本使用RENAME TAG代替。<br/>新增</li><li>RENAME TAG：代替原CHANGE TAG子句。</li><li>COMMENT：修改超级表的注释。</li></ul>
| 5 | ALTER TABLE | 调整 | 废除<ul><li>CHANGE TAG：修改标签列的名称。3.0版本使用RENAME TAG代替。<br/>新增</li><li>RENAME TAG：代替原CHANGE TAG子句。</li><li>COMMENT：修改表的注释。</li><li>TTL：修改表的生命周期。</li></ul>
| 6 | ALTER USER | 调整 | 废除<ul><li>PRIVILEGE：修改用户权限。3.0版本使用GRANT和REVOKE来授予和回收权限。<br/>新增</li><li>ENABLE：启用或停用此用户。</li><li>SYSINFO：修改用户是否可查看系统信息。</li></ul>
| 7 | COMPACT VNODES | 暂不支持 | 整理指定VNODE的数据。3.0.0版本暂不支持。
| 8 | CREATE ACCOUNT | 废除 | 2.x中为企业版功能，3.0不再支持。语法暂时保留了，执行报“This statement is no longer supported”错误。
| 9 | CREATE DATABASE | 调整 | 废除<ul><li>BLOCKS：VNODE使用的内存块数。3.0版本使用BUFFER来表示VNODE写入内存池的大小。</li><li>CACHE：VNODE使用的内存块的大小。3.0版本使用BUFFER来表示VNODE写入内存池的大小。</li><li>CACHELAST：缓存最新一行数据的模式。3.0版本用CACHEMODEL代替。</li><li>DAYS：数据文件存储数据的时间跨度。3.0版本使用DURATION代替。</li><li>FSYNC：当 WAL 设置为 2 时，执行 fsync 的周期。3.0版本使用WAL_FSYNC_PERIOD代替。</li><li>QUORUM：写入需要的副本确认数。3.0版本使用STRICT来指定强一致还是弱一致。</li><li>UPDATE：更新操作的支持模式。3.0版本所有数据库都支持部分列更新。</li><li>WAL：WAL 级别。3.0版本使用WAL_LEVEL代替。<br/>新增</li><li>BUFFER：一个 VNODE 写入内存池大小。</li><li>CACHEMODEL：表示是否在内存中缓存子表的最近数据。</li><li>CACHESIZE：表示缓存子表最近数据的内存大小。</li><li>DURATION：代替原DAYS参数。新增支持带单位的设置方式。</li><li>PAGES：一个 VNODE 中元数据存储引擎的缓存页个数。</li><li>PAGESIZE：一个 VNODE 中元数据存储引擎的页大小。</li><li>RETENTIONS：表示数据的聚合周期和保存时长。</li><li>STRICT：表示数据同步的一致性要求。</li><li>SINGLE_STABLE：表示此数据库中是否只可以创建一个超级表。</li><li>VGROUPS：数据库中初始VGROUP的数目。</li><li>WAL_FSYNC_PERIOD：代替原FSYNC参数。</li><li>WAL_LEVEL：代替原WAL参数。</li><li>WAL_RETENTION_PERIOD：wal文件的额外保留策略，用于数据订阅。</li><li>WAL_RETENTION_SIZE：wal文件的额外保留策略，用于数据订阅。</li><li>WAL_ROLL_PERIOD：wal文件切换时长。</li><li>WAL_SEGMENT_SIZE：wal单个文件大小。<br/>调整</li><li>KEEP：3.0版本新增支持带单位的设置方式。</li></ul>
| 9 | CREATE DATABASE | 调整 | <p>废除</p><ul><li>BLOCKS：VNODE使用的内存块数。3.0版本使用BUFFER来表示VNODE写入内存池的大小。</li><li>CACHE：VNODE使用的内存块的大小。3.0版本使用BUFFER来表示VNODE写入内存池的大小。</li><li>CACHELAST：缓存最新一行数据的模式。3.0版本用CACHEMODEL代替。</li><li>DAYS：数据文件存储数据的时间跨度。3.0版本使用DURATION代替。</li><li>FSYNC：当 WAL 设置为 2 时，执行 fsync 的周期。3.0版本使用WAL_FSYNC_PERIOD代替。</li><li>QUORUM：写入需要的副本确认数。3.0版本使用STRICT来指定强一致还是弱一致。</li><li>UPDATE：更新操作的支持模式。3.0版本所有数据库都支持部分列更新。</li><li>WAL：WAL 级别。3.0版本使用WAL_LEVEL代替。</li></ul><p>新增</p><ul><li>BUFFER：一个 VNODE 写入内存池大小。</li><li>CACHEMODEL：表示是否在内存中缓存子表的最近数据。</li><li>CACHESIZE：表示缓存子表最近数据的内存大小。</li><li>DURATION：代替原DAYS参数。新增支持带单位的设置方式。</li><li>PAGES：一个 VNODE 中元数据存储引擎的缓存页个数。</li><li>PAGESIZE：一个 VNODE 中元数据存储引擎的页大小。</li><li>RETENTIONS：表示数据的聚合周期和保存时长。</li><li>STRICT：表示数据同步的一致性要求。</li><li>SINGLE_STABLE：表示此数据库中是否只可以创建一个超级表。</li><li>VGROUPS：数据库中初始VGROUP的数目。</li><li>WAL_FSYNC_PERIOD：代替原FSYNC参数。</li><li>WAL_LEVEL：代替原WAL参数。</li><li>WAL_RETENTION_PERIOD：wal文件的额外保留策略，用于数据订阅。</li><li>WAL_RETENTION_SIZE：wal文件的额外保留策略，用于数据订阅。</li><li>WAL_ROLL_PERIOD：wal文件切换时长。</li><li>WAL_SEGMENT_SIZE：wal单个文件大小。</li></ul><p>调整</p><ul><li>KEEP：3.0版本新增支持带单位的设置方式。</li></ul>
| 10 | CREATE DNODE | 调整 | 新增主机名和端口号分开指定语法<ul><li>CREATE DNODE dnode_host_name PORT port_val</li></ul>
| 11 | CREATE INDEX | 新增 | 创建SMA索引。
| 12 | CREATE MNODE | 新增 | 创建管理节点。

1
docs/zh/14-reference/06-taosdump.md
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@ -79,6 +79,7 @@ Usage: taosdump [OPTION...] dbname [tbname ...]
-A, --all-databases Dump all databases.
-D, --databases=DATABASES Dump inputted databases. Use comma to separate
databases' name.
-e, --escape-character Use escaped character for database name
-N, --without-property Dump database without its properties.
-s, --schemaonly Only dump tables' schema.
-y, --answer-yes Input yes for prompt. It will skip data file

4
docs/zh/14-reference/12-config/index.md
View File

@ -356,7 +356,7 @@ charset 的有效值是 UTF-8。
| 适用范围 | 仅服务端适用 |
| 含义 | dnode 支持的最大 vnode 数目 |
| 取值范围 | 0-4096 |
| 缺省值 | CPU 核数的 2 倍 |
| 缺省值 | CPU 核数的 2 倍 |
## 性能调优
@ -366,6 +366,7 @@ charset 的有效值是 UTF-8。
| -------- | ---------------------- |
| 适用范围 | 仅服务端适用 |
| 含义 | 设置写入线程的最大数量 |
| 取值范围 | 0-1024 |
| 缺省值 | |
## 日志相关
@ -734,7 +735,6 @@ charset 的有效值是 UTF-8。
| 16 | maxTmrCtrl | 是 | 否 | 3.0 行为未知 |
| 17 | monitorReplica | 是 | 否 | 由 RAFT 协议管理多副本 |
| 18 | smlTagNullName | 是 | 否 | 3.0 行为未知 |
| 19 | keepColumnName | 是 | 否 | 3.0 行为未知 |
| 20 | ratioOfQueryCores | 是 | 否 | 由 线程池 相关配置参数决定 |
| 21 | maxStreamCompDelay | 是 | 否 | 3.0 行为未知 |
| 22 | maxFirstStreamCompDelay | 是 | 否 | 3.0 行为未知 |

34
docs/zh/14-reference/14-taosKeeper.md
View File

@ -111,7 +111,7 @@ Active: inactive (dead)
#### 配置文件启动
执行以下命令即可快速体验 taosKeeper。当不指定 taosKeeper 配置文件时，优先使用 `/etc/taos/keeper.toml` 配置，否则将使用默认配置。
执行以下命令即可快速体验 taosKeeper。当不指定 taosKeeper 配置文件时，优先使用 `/etc/taos/taoskeeper.toml` 配置，否则将使用默认配置。
```shell
$ taoskeeper -c <keeper config file>
@ -156,6 +156,10 @@ database = "log"
# 指定需要监控的普通表
tables = []
# database options for db storing metrics data
[metrics.databaseoptions]
cachemodel = "none"
```
### 获取监控指标
@ -206,7 +210,7 @@ taos_cluster_info_dnodes_total{cluster_id="5981392874047724755"} 1
taos_cluster_info_first_ep{cluster_id="5981392874047724755",value="hlb:6030"} 1
```
### check_health
### check\_health
```
$ curl -i http://127.0.0.1:6043/check_health
@ -222,3 +226,29 @@ Content-Length: 19
{"version":"1.0.0"}
```
### 集成 Prometheus
taoskeeper 提供了 `/metrics` 接口，返回了 Prometheus 格式的监控数据，Prometheus 可以从 taoskeeper 抽取监控数据，实现通过 Prometheus 监控 TDengine 的目的。
#### 抽取配置
Prometheus 提供了 `scrape_configs` 配置如何从 endpoint 抽取监控数据，通常只需要修改 `static_configs` 中的 targets 配置为 taoskeeper 的 endpoint 地址，更多配置信息请参考 [Prometheus 配置文档](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config)。
```
# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
- job_name: "taoskeeper"
# metrics_path defaults to '/metrics'
# scheme defaults to 'http'.
static_configs:
- targets: ["localhost:6043"]
```
#### Dashboard
我们提供了 `TaosKeeper Prometheus Dashboard for 3.x` dashboard，提供了和 TDinsight 类似的监控 dashboard。
在 Grafana Dashboard 菜单点击 `import`，dashboard ID 填写 `18587`，点击 `Load` 按钮即可导入 `TaosKeeper Prometheus Dashboard for 3.x` dashboard。

16
docs/zh/17-operation/10-monitor.md
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@ -54,7 +54,7 @@ TDinsight dashboard 数据来源于 log 库（存放监控数据的默认db，
|first\_ep\_dnode\_id|INT||集群 first ep 的 dnode id|
|version|VARCHAR||tdengine version。例如：3.0.4.0|
|master\_uptime|FLOAT||当前 master 节点的uptime。单位：天|
|monitor_interval|INT||monitor interval。单位：秒|
|monitor\_interval|INT||monitor interval。单位：秒|
|dbs\_total|INT||database 总数|
|tbs\_total|BIGINT||当前集群 table 总数|
|stbs\_total|INT||当前集群 stable 总数|
@ -107,17 +107,17 @@ TDinsight dashboard 数据来源于 log 库（存放监控数据的默认db，
|cpu\_system|FLOAT||服务器 cpu 使用率，从 `/proc/stat` 读取|
|cpu\_cores|FLOAT||服务器 cpu 核数|
|mem\_engine|INT||taosd 内存使用率，从 `/proc/<taosd_pid>/status` 读取|
|mem\_system|INT||服务器内存使用率|
|mem\_system|INT||服务器可用内存|
|mem\_total|INT||服务器内存总量，单位 KB|
|disk\_engine|INT|||
|disk\_used|BIGINT||data dir 挂载的磁盘使用量，单位 bytes|
|disk\_total|BIGINT||data dir 挂载的磁盘总容量，单位 bytes|
|net\_in|FLOAT||网络吞吐率，从 `/proc/net/dev` 中读取的 received bytes。单位 bytes per second|
|net\_out|FLOAT||网络吞吐率，从 `/proc/net/dev` 中读取的 transmit bytes。单位 bytes per second|
|io\_read|FLOAT||io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 rchar 与上次数值计算之后，计算得到速度。单位 bytes per second|
|io\_write|FLOAT||io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 wchar 与上次数值计算之后，计算得到速度。单位 bytes per second|
|io\_read\_disk|FLOAT||磁盘 io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 read_bytes。单位 bytes per second|
|io\_write\_disk|FLOAT||磁盘 io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 write_bytes。单位 bytes per second|
|net\_in|FLOAT||网络吞吐率，从 `/proc/net/dev` 中读取的 received bytes。单位 kb/s|
|net\_out|FLOAT||网络吞吐率，从 `/proc/net/dev` 中读取的 transmit bytes。单位 kb/s|
|io\_read|FLOAT||io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 rchar 与上次数值计算之后，计算得到速度。单位 kb/s|
|io\_write|FLOAT||io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 wchar 与上次数值计算之后，计算得到速度。单位 kb/s|
|io\_read\_disk|FLOAT||磁盘 io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 read_bytes。单位 kb/s|
|io\_write\_disk|FLOAT||磁盘 io 吞吐率，从 `/proc/<taosd_pid>/io` 中读取的 write_bytes。单位 kb/s|
|req\_select|INT||两个间隔内发生的查询请求数目|
|req\_select\_rate|FLOAT||两个间隔内的查询请求速度 = `req_select / monitorInterval`|
|req\_insert|INT||两个间隔内发生的写入请求，包含的单条数据数目|

17
docs/zh/20-third-party/11-kafka.md vendored
View File

@ -48,15 +48,14 @@ Confluent 提供了 Docker 和二进制包两种安装方式。本文仅介绍
```
curl -O http://packages.confluent.io/archive/7.1/confluent-7.1.1.tar.gz
tar xzf confluent-7.1.1.tar.gz -C /opt/test
tar xzf confluent-7.1.1.tar.gz -C /opt/
```
然后需要把 `$CONFLUENT_HOME/bin` 目录加入 PATH。
```title=".profile"
export CONFLUENT_HOME=/opt/confluent-7.1.1
PATH=$CONFLUENT_HOME/bin
export PATH
export PATH=$CONFLUENT_HOME/bin:$PATH
```
以上脚本可以追加到当前用户的 profile 文件（~/.profile 或 ~/.bash_profile）
@ -333,7 +332,15 @@ DROP DATABASE IF EXISTS test;
CREATE DATABASE test;
USE test;
CREATE STABLE meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (location BINARY(64), groupId INT);
INSERT INTO d1001 USING meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:05.000',10.30000,219,0.31000) d1001 USING meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:15.000',12.60000,218,0.33000) d1001 USING meters TAGS(California.SanFrancisco, 2) VALUES('2018-10-03 14:38:16.800',12.30000,221,0.31000) d1002 USING meters TAGS(California.SanFrancisco, 3) VALUES('2018-10-03 14:38:16.650',10.30000,218,0.25000) d1003 USING meters TAGS(California.LosAngeles, 2) VALUES('2018-10-03 14:38:05.500',11.80000,221,0.28000) d1003 USING meters TAGS(California.LosAngeles, 2) VALUES('2018-10-03 14:38:16.600',13.40000,223,0.29000) d1004 USING meters TAGS(California.LosAngeles, 3) VALUES('2018-10-03 14:38:05.000',10.80000,223,0.29000) d1004 USING meters TAGS(California.LosAngeles, 3) VALUES('2018-10-03 14:38:06.500',11.50000,221,0.35000);
INSERT INTO d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:05.000',10.30000,219,0.31000) \
d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:15.000',12.60000,218,0.33000) \
d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-10-03 14:38:16.800',12.30000,221,0.31000) \
d1002 USING meters TAGS('California.SanFrancisco', 3) VALUES('2018-10-03 14:38:16.650',10.30000,218,0.25000) \
d1003 USING meters TAGS('California.LosAngeles', 2) VALUES('2018-10-03 14:38:05.500',11.80000,221,0.28000) \
d1003 USING meters TAGS('California.LosAngeles', 2) VALUES('2018-10-03 14:38:16.600',13.40000,223,0.29000) \
d1004 USING meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 14:38:05.000',10.80000,223,0.29000) \
d1004 USING meters TAGS('California.LosAngeles', 3) VALUES('2018-10-03 14:38:06.500',11.50000,221,0.35000);
```
使用 TDengine CLI, 执行 SQL 文件。
@ -388,7 +395,7 @@ confluent local services connect connector status
如果按照前述操作，此时应有两个活跃的 connector。使用下面的命令 unload：
```
confluent local services connect connector unload TDengineSourceConnector
confluent local services connect connector unload TDengineSinkConnector
confluent local services connect connector unload TDengineSourceConnector
```

2
docs/zh/27-train-faq/01-faq.md
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@ -77,7 +77,7 @@ description: 一些常见问题的解决方法汇总
- Windows 系统请使用 PowerShell 命令 Test-NetConnection -ComputerName {fqdn} -Port {port} 检测服务段端口是否访问
11. 也可以使用 taos 程序内嵌的网络连通检测功能，来验证服务器和客户端之间指定的端口连接是否通畅：[诊断及其他](https://docs.taosdata.com/3.0-preview/operation/diagnose/)。
11. 也可以使用 taos 程序内嵌的网络连通检测功能，来验证服务器和客户端之间指定的端口连接是否通畅：[诊断及其他](../../operation/diagnose/)。
### 5. 遇到错误 Unable to resolve FQDN” 怎么办？

4
docs/zh/28-releases/01-tdengine.md
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@ -10,6 +10,10 @@ TDengine 2.x 各版本安装包请访问[这里](https://www.taosdata.com/all-do
import Release from "/components/ReleaseV3";
## 3.0.4.1
<Release type="tdengine" version="3.0.4.1" />
## 3.0.4.0
<Release type="tdengine" version="3.0.4.0" />

8
docs/zh/28-releases/02-tools.md
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@ -10,6 +10,14 @@ taosTools 各版本安装包下载链接如下：
import Release from "/components/ReleaseV3";
## 2.5.0
<Release type="tools" version="2.5.0" />
## 2.5.0
<Release type="tools" version="2.5.0" />
## 2.4.12
<Release type="tools" version="2.4.12" />

33
examples/c/tmq.c
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@ -20,7 +20,8 @@
#include <time.h>
#include "taos.h"
static int running = 1;
static int running = 1;
const char* topic_name = "topicname";
static int32_t msg_process(TAOS_RES* msg) {
char buf[1024];
@ -243,7 +244,7 @@ _end:
tmq_list_t* build_topic_list() {
tmq_list_t* topicList = tmq_list_new();
int32_t code = tmq_list_append(topicList, "topicname");
int32_t code = tmq_list_append(topicList, topic_name);
if (code) {
tmq_list_destroy(topicList);
return NULL;
@ -269,6 +270,31 @@ void basic_consume_loop(tmq_t* tmq) {
fprintf(stderr, "%d msg consumed, include %d rows\n", msgCnt, totalRows);
}
void consume_repeatly(tmq_t* tmq) {
int32_t numOfAssignment = 0;
tmq_topic_assignment* pAssign = NULL;
int32_t code = tmq_get_topic_assignment(tmq, topic_name, &pAssign, &numOfAssignment);
if (code != 0) {
fprintf(stderr, "failed to get assignment, reason:%s", tmq_err2str(code));
}
// seek to the earliest offset
for(int32_t i = 0; i < numOfAssignment; ++i) {
tmq_topic_assignment* p = &pAssign[i];
code = tmq_offset_seek(tmq, topic_name, p->vgId, p->begin);
if (code != 0) {
fprintf(stderr, "failed to seek to %ld, reason:%s", p->begin, tmq_err2str(code));
}
}
free(pAssign);
// let's do it again
basic_consume_loop(tmq);
}
int main(int argc, char* argv[]) {
int32_t code;
@ -294,10 +320,13 @@ int main(int argc, char* argv[]) {
if ((code = tmq_subscribe(tmq, topic_list))) {
fprintf(stderr, "Failed to tmq_subscribe(): %s\n", tmq_err2str(code));
}
tmq_list_destroy(topic_list);
basic_consume_loop(tmq);
consume_repeatly(tmq);
code = tmq_consumer_close(tmq);
if (code) {
fprintf(stderr, "Failed to close consumer: %s\n", tmq_err2str(code));

18
include/client/taos.h
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@ -101,6 +101,7 @@ typedef struct TAOS_FIELD_E {
#endif
typedef void (*__taos_async_fn_t)(void *param, TAOS_RES *res, int code);
typedef void (*__taos_notify_fn_t)(void *param, void *ext, int type);
typedef struct TAOS_MULTI_BIND {
int buffer_type;
@ -121,6 +122,10 @@ typedef enum {
SET_CONF_RET_ERR_TOO_LONG = -6
} SET_CONF_RET_CODE;
typedef enum {
TAOS_NOTIFY_PASSVER = 0,
} TAOS_NOTIFY_TYPE;
#define RET_MSG_LENGTH 1024
typedef struct setConfRet {
SET_CONF_RET_CODE retCode;
@ -162,7 +167,7 @@ DLL_EXPORT int taos_stmt_set_sub_tbname(TAOS_STMT *stmt, const char *name
DLL_EXPORT int taos_stmt_get_tag_fields(TAOS_STMT *stmt, int *fieldNum, TAOS_FIELD_E **fields);
DLL_EXPORT int taos_stmt_get_col_fields(TAOS_STMT *stmt, int *fieldNum, TAOS_FIELD_E **fields);
// let stmt to reclaim TAOS_FIELD_E that was allocated by `taos_stmt_get_tag_fields`/`taos_stmt_get_col_fields`
DLL_EXPORT void taos_stmt_reclaim_fields(TAOS_STMT *stmt, TAOS_FIELD_E *fields);
DLL_EXPORT void taos_stmt_reclaim_fields(TAOS_STMT *stmt, TAOS_FIELD_E *fields);
DLL_EXPORT int taos_stmt_is_insert(TAOS_STMT *stmt, int *insert);
DLL_EXPORT int taos_stmt_num_params(TAOS_STMT *stmt, int *nums);
@ -228,6 +233,8 @@ DLL_EXPORT int taos_load_table_info(TAOS *taos, const char *tableNameList);
// set heart beat thread quit mode , if quicByKill 1 then kill thread else quit from inner
DLL_EXPORT void taos_set_hb_quit(int8_t quitByKill);
DLL_EXPORT int taos_set_notify_cb(TAOS *taos, __taos_notify_fn_t fp, void *param, int type);
/* --------------------------schemaless INTERFACE------------------------------- */
DLL_EXPORT TAOS_RES *taos_schemaless_insert(TAOS *taos, char *lines[], int numLines, int protocol, int precision);
@ -265,6 +272,12 @@ DLL_EXPORT tmq_t *tmq_consumer_new(tmq_conf_t *conf, char *errstr, int32_t errst
DLL_EXPORT const char *tmq_err2str(int32_t code);
/* ------------------------TMQ CONSUMER INTERFACE------------------------ */
typedef struct tmq_topic_assignment {
int32_t vgId;
int64_t currentOffset;
int64_t begin;
int64_t end;
} tmq_topic_assignment;
DLL_EXPORT int32_t tmq_subscribe(tmq_t *tmq, const tmq_list_t *topic_list);
DLL_EXPORT int32_t tmq_unsubscribe(tmq_t *tmq);
@ -273,6 +286,9 @@ DLL_EXPORT TAOS_RES *tmq_consumer_poll(tmq_t *tmq, int64_t timeout);
DLL_EXPORT int32_t tmq_consumer_close(tmq_t *tmq);
DLL_EXPORT int32_t tmq_commit_sync(tmq_t *tmq, const TAOS_RES *msg);
DLL_EXPORT void tmq_commit_async(tmq_t *tmq, const TAOS_RES *msg, tmq_commit_cb *cb, void *param);
DLL_EXPORT int32_t tmq_get_topic_assignment(tmq_t *tmq, const char *pTopicName, tmq_topic_assignment **assignment,
int32_t *numOfAssignment);
DLL_EXPORT int32_t tmq_offset_seek(tmq_t *tmq, const char *pTopicName, int32_t vgId, int64_t offset);
/* ----------------------TMQ CONFIGURATION INTERFACE---------------------- */

1
include/common/tcommon.h
View File

@ -128,6 +128,7 @@ enum {
TMQ_MSG_TYPE__POLL_META_RSP,
TMQ_MSG_TYPE__EP_RSP,
TMQ_MSG_TYPE__TAOSX_RSP,
TMQ_MSG_TYPE__WALINFO_RSP,
TMQ_MSG_TYPE__END_RSP,
};

8
include/common/tglobal.h
View File

@ -24,6 +24,12 @@
extern "C" {
#endif
#define SLOW_LOG_TYPE_QUERY 0x1
#define SLOW_LOG_TYPE_INSERT 0x2
#define SLOW_LOG_TYPE_OTHERS 0x4
#define SLOW_LOG_TYPE_ALL 0xFFFFFFFF
// cluster
extern char tsFirst[];
extern char tsSecond[];
@ -118,6 +124,8 @@ extern int32_t tsRedirectFactor;
extern int32_t tsRedirectMaxPeriod;
extern int32_t tsMaxRetryWaitTime;
extern bool tsUseAdapter;
extern int32_t tsSlowLogThreshold;
extern int32_t tsSlowLogScope;
// client
extern int32_t tsMinSlidingTime;

62
include/common/tgrant.h
View File

@ -26,6 +26,10 @@ extern "C" {
#include "tgrantCfg.h"
#endif
#ifndef GRANTS_COL_MAX_LEN
#define GRANTS_COL_MAX_LEN 196
#endif
typedef enum {
TSDB_GRANT_ALL,
TSDB_GRANT_TIME,
@ -47,23 +51,49 @@ typedef enum {
int32_t grantCheck(EGrantType grant);
#ifndef GRANTS_CFG
#define GRANTS_SCHEMA \
static const SSysDbTableSchema grantsSchema[] = { \
{.name = "version", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "expire_time", .bytes = 19 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "expired", .bytes = 5 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "storage", .bytes = 21 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "timeseries", .bytes = 21 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "databases", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "users", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "accounts", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "dnodes", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "connections", .bytes = 11 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "streams", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "cpu_cores", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "speed", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "querytime", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
#ifdef TD_ENTERPRISE
#define GRANTS_SCHEMA \
static const SSysDbTableSchema grantsSchema[] = { \
{.name = "version", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "expire_time", .bytes = 19 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "expired", .bytes = 5 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "storage", .bytes = 21 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "timeseries", .bytes = 21 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "databases", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "users", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "accounts", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "dnodes", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "connections", .bytes = 11 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "streams", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "cpu_cores", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "speed", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "querytime", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "opc_da", .bytes = GRANTS_COL_MAX_LEN + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "opc_ua", .bytes = GRANTS_COL_MAX_LEN + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "pi", .bytes = GRANTS_COL_MAX_LEN + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "kafka", .bytes = GRANTS_COL_MAX_LEN + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "influxdb", .bytes = GRANTS_COL_MAX_LEN + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "mqtt", .bytes = GRANTS_COL_MAX_LEN + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
}
#else
#define GRANTS_SCHEMA \
static const SSysDbTableSchema grantsSchema[] = { \
{.name = "version", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "expire_time", .bytes = 19 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "expired", .bytes = 5 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "storage", .bytes = 21 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "timeseries", .bytes = 21 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "databases", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "users", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "accounts", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "dnodes", .bytes = 10 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "connections", .bytes = 11 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "streams", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "cpu_cores", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "speed", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
{.name = "querytime", .bytes = 9 + VARSTR_HEADER_SIZE, .type = TSDB_DATA_TYPE_VARCHAR}, \
}
#endif
#define GRANT_CFG_ADD
#define GRANT_CFG_SET
#define GRANT_CFG_GET

138
include/common/tmsg.h
View File

@ -106,6 +106,7 @@ enum {
HEARTBEAT_KEY_DBINFO,
HEARTBEAT_KEY_STBINFO,
HEARTBEAT_KEY_TMQ,
HEARTBEAT_KEY_USER_PASSINFO,
};
typedef enum _mgmt_table {
@ -634,6 +635,7 @@ typedef struct {
int8_t connType;
SEpSet epSet;
int32_t svrTimestamp;
int32_t passVer;
char sVer[TSDB_VERSION_LEN];
char sDetailVer[128];
} SConnectRsp;
@ -717,6 +719,14 @@ int32_t tSerializeSGetUserAuthRsp(void* buf, int32_t bufLen, SGetUserAuthRsp* pR
int32_t tDeserializeSGetUserAuthRsp(void* buf, int32_t bufLen, SGetUserAuthRsp* pRsp);
void tFreeSGetUserAuthRsp(SGetUserAuthRsp* pRsp);
typedef struct SUserPassVersion {
char user[TSDB_USER_LEN];
int32_t version;
} SUserPassVersion;
typedef SGetUserAuthReq SGetUserPassReq;
typedef SUserPassVersion SGetUserPassRsp;
/*
* for client side struct, only column id, type, bytes are necessary
* But for data in vnode side, we need all the following information.
@ -1047,6 +1057,14 @@ int32_t tSerializeSUserAuthBatchRsp(void* buf, int32_t bufLen, SUserAuthBatchRsp
int32_t tDeserializeSUserAuthBatchRsp(void* buf, int32_t bufLen, SUserAuthBatchRsp* pRsp);
void tFreeSUserAuthBatchRsp(SUserAuthBatchRsp* pRsp);
typedef struct {
SArray* pArray; // Array of SGetUserPassRsp
} SUserPassBatchRsp;
int32_t tSerializeSUserPassBatchRsp(void* buf, int32_t bufLen, SUserPassBatchRsp* pRsp);
int32_t tDeserializeSUserPassBatchRsp(void* buf, int32_t bufLen, SUserPassBatchRsp* pRsp);
void tFreeSUserPassBatchRsp(SUserPassBatchRsp* pRsp);
typedef struct {
char db[TSDB_DB_FNAME_LEN];
STimeWindow timeRange;
@ -1215,6 +1233,14 @@ typedef struct {
SEp ep;
} SDnodeEp;
typedef struct {
int32_t id;
int8_t isMnode;
SEp ep;
char active[TSDB_ACTIVE_KEY_LEN];
char connActive[TSDB_CONN_ACTIVE_KEY_LEN];
} SDnodeInfo;
typedef struct {
int64_t dnodeVer;
SDnodeCfg dnodeCfg;
@ -1287,6 +1313,9 @@ typedef struct {
int16_t hashSuffix;
int32_t tsdbPageSize;
int64_t reserved[8];
int8_t learnerReplica;
int8_t learnerSelfIndex;
SReplica learnerReplicas[TSDB_MAX_LEARNER_REPLICA];
} SCreateVnodeReq;
int32_t tSerializeSCreateVnodeReq(void* buf, int32_t bufLen, SCreateVnodeReq* pReq);
@ -1358,7 +1387,10 @@ typedef struct {
int8_t replica;
SReplica replicas[TSDB_MAX_REPLICA];
int64_t reserved[8];
} SAlterVnodeReplicaReq;
int8_t learnerSelfIndex;
int8_t learnerReplica;
SReplica learnerReplicas[TSDB_MAX_LEARNER_REPLICA];
} SAlterVnodeReplicaReq, SAlterVnodeTypeReq;
int32_t tSerializeSAlterVnodeReplicaReq(void* buf, int32_t bufLen, SAlterVnodeReplicaReq* pReq);
int32_t tDeserializeSAlterVnodeReplicaReq(void* buf, int32_t bufLen, SAlterVnodeReplicaReq* pReq);
@ -1602,6 +1634,21 @@ typedef struct {
int32_t tSerializeSDropDnodeReq(void* buf, int32_t bufLen, SDropDnodeReq* pReq);
int32_t tDeserializeSDropDnodeReq(void* buf, int32_t bufLen, SDropDnodeReq* pReq);
enum {
RESTORE_TYPE__ALL = 1,
RESTORE_TYPE__MNODE,
RESTORE_TYPE__VNODE,
RESTORE_TYPE__QNODE,
};
typedef struct {
int32_t dnodeId;
int8_t restoreType;
} SRestoreDnodeReq;
int32_t tSerializeSRestoreDnodeReq(void* buf, int32_t bufLen, SRestoreDnodeReq* pReq);
int32_t tDeserializeSRestoreDnodeReq(void* buf, int32_t bufLen, SRestoreDnodeReq* pReq);
typedef struct {
int32_t dnodeId;
char config[TSDB_DNODE_CONFIG_LEN];
@ -1630,7 +1677,10 @@ int32_t tDeserializeSCreateDropMQSNodeReq(void* buf, int32_t bufLen, SMCreateQno
typedef struct {
int8_t replica;
SReplica replicas[TSDB_MAX_REPLICA];
} SDCreateMnodeReq, SDAlterMnodeReq;
int8_t learnerReplica;
SReplica learnerReplicas[TSDB_MAX_LEARNER_REPLICA];
int64_t lastIndex;
} SDCreateMnodeReq, SDAlterMnodeReq, SDAlterMnodeTypeReq;
int32_t tSerializeSDCreateMnodeReq(void* buf, int32_t bufLen, SDCreateMnodeReq* pReq);
int32_t tDeserializeSDCreateMnodeReq(void* buf, int32_t bufLen, SDCreateMnodeReq* pReq);
@ -2800,6 +2850,7 @@ typedef struct {
} SMqOffset;
typedef struct {
int64_t consumerId;
int32_t num;
SMqOffset* offsets;
} SMqCMCommitOffsetReq;
@ -2867,6 +2918,14 @@ typedef struct {
int32_t tEncodeSTqOffset(SEncoder* pEncoder, const STqOffset* pOffset);
int32_t tDecodeSTqOffset(SDecoder* pDecoder, STqOffset* pOffset);
typedef struct SMqVgOffset {
int64_t consumerId;
STqOffset offset;
} SMqVgOffset;
int32_t tEncodeMqVgOffset(SEncoder* pEncoder, const SMqVgOffset* pOffset);
int32_t tDecodeMqVgOffset(SDecoder* pDecoder, SMqVgOffset* pOffset);
typedef struct {
SMsgHead head;
int32_t taskId;
@ -3132,18 +3191,19 @@ typedef struct {
int32_t code;
int32_t epoch;
int64_t consumerId;
int64_t walsver;
int64_t walever;
} SMqRspHead;
typedef struct {
SMsgHead head;
char subKey[TSDB_SUBSCRIBE_KEY_LEN];
int8_t withTbName;
int8_t useSnapshot;
int32_t epoch;
uint64_t reqId;
int64_t consumerId;
int64_t timeout;
// int64_t currentOffset;
SMsgHead head;
char subKey[TSDB_SUBSCRIBE_KEY_LEN];
int8_t withTbName;
int8_t useSnapshot;
int32_t epoch;
uint64_t reqId;
int64_t consumerId;
int64_t timeout;
STqOffsetVal reqOffset;
} SMqPollReq;
@ -3178,43 +3238,9 @@ typedef struct {
SSchemaWrapper schema;
} SMqSubTopicEp;
static FORCE_INLINE int32_t tEncodeSMqSubTopicEp(void** buf, const SMqSubTopicEp* pTopicEp) {
int32_t tlen = 0;
tlen += taosEncodeString(buf, pTopicEp->topic);
tlen += taosEncodeString(buf, pTopicEp->db);
int32_t sz = taosArrayGetSize(pTopicEp->vgs);
tlen += taosEncodeFixedI32(buf, sz);
for (int32_t i = 0; i < sz; i++) {
SMqSubVgEp* pVgEp = (SMqSubVgEp*)taosArrayGet(pTopicEp->vgs, i);
tlen += tEncodeSMqSubVgEp(buf, pVgEp);
}
tlen += taosEncodeSSchemaWrapper(buf, &pTopicEp->schema);
return tlen;
}
static FORCE_INLINE void* tDecodeSMqSubTopicEp(void* buf, SMqSubTopicEp* pTopicEp) {
buf = taosDecodeStringTo(buf, pTopicEp->topic);
buf = taosDecodeStringTo(buf, pTopicEp->db);
int32_t sz;
buf = taosDecodeFixedI32(buf, &sz);
pTopicEp->vgs = taosArrayInit(sz, sizeof(SMqSubVgEp));
if (pTopicEp->vgs == NULL) {
return NULL;
}
for (int32_t i = 0; i < sz; i++) {
SMqSubVgEp vgEp;
buf = tDecodeSMqSubVgEp(buf, &vgEp);
taosArrayPush(pTopicEp->vgs, &vgEp);
}
buf = taosDecodeSSchemaWrapper(buf, &pTopicEp->schema);
return buf;
}
static FORCE_INLINE void tDeleteSMqSubTopicEp(SMqSubTopicEp* pSubTopicEp) {
taosMemoryFreeClear(pSubTopicEp->schema.pSchema);
pSubTopicEp->schema.nCols = 0;
taosArrayDestroy(pSubTopicEp->vgs);
}
int32_t tEncodeMqSubTopicEp(void** buf, const SMqSubTopicEp* pTopicEp);
void* tDecodeMqSubTopicEp(void* buf, SMqSubTopicEp* pTopicEp);
void tDeleteMqSubTopicEp(SMqSubTopicEp* pSubTopicEp);
typedef struct {
SMqRspHead head;
@ -3224,8 +3250,8 @@ typedef struct {
void* metaRsp;
} SMqMetaRsp;
int32_t tEncodeSMqMetaRsp(SEncoder* pEncoder, const SMqMetaRsp* pRsp);
int32_t tDecodeSMqMetaRsp(SDecoder* pDecoder, SMqMetaRsp* pRsp);
int32_t tEncodeMqMetaRsp(SEncoder* pEncoder, const SMqMetaRsp* pRsp);
int32_t tDecodeMqMetaRsp(SDecoder* pDecoder, SMqMetaRsp* pRsp);
typedef struct {
SMqRspHead head;
@ -3240,9 +3266,9 @@ typedef struct {
SArray* blockSchema;
} SMqDataRsp;
int32_t tEncodeSMqDataRsp(SEncoder* pEncoder, const SMqDataRsp* pRsp);
int32_t tDecodeSMqDataRsp(SDecoder* pDecoder, SMqDataRsp* pRsp);
void tDeleteSMqDataRsp(SMqDataRsp* pRsp);
int32_t tEncodeMqDataRsp(SEncoder* pEncoder, const SMqDataRsp* pRsp);
int32_t tDecodeMqDataRsp(SDecoder* pDecoder, SMqDataRsp* pRsp);
void tDeleteMqDataRsp(SMqDataRsp* pRsp);
typedef struct {
SMqRspHead head;
@ -3278,7 +3304,7 @@ static FORCE_INLINE int32_t tEncodeSMqAskEpRsp(void** buf, const SMqAskEpRsp* pR
tlen += taosEncodeFixedI32(buf, sz);
for (int32_t i = 0; i < sz; i++) {
SMqSubTopicEp* pVgEp = (SMqSubTopicEp*)taosArrayGet(pRsp->topics, i);
tlen += tEncodeSMqSubTopicEp(buf, pVgEp);
tlen += tEncodeMqSubTopicEp(buf, pVgEp);
}
return tlen;
}
@ -3293,14 +3319,14 @@ static FORCE_INLINE void* tDecodeSMqAskEpRsp(void* buf, SMqAskEpRsp* pRsp) {
}
for (int32_t i = 0; i < sz; i++) {
SMqSubTopicEp topicEp;
buf = tDecodeSMqSubTopicEp(buf, &topicEp);
buf = tDecodeMqSubTopicEp(buf, &topicEp);
taosArrayPush(pRsp->topics, &topicEp);
}
return buf;
}
static FORCE_INLINE void tDeleteSMqAskEpRsp(SMqAskEpRsp* pRsp) {
taosArrayDestroyEx(pRsp->topics, (FDelete)tDeleteSMqSubTopicEp);
taosArrayDestroyEx(pRsp->topics, (FDelete)tDeleteMqSubTopicEp);
}
#define TD_AUTO_CREATE_TABLE 0x1

6
include/common/tmsgdef.h
View File

@ -83,6 +83,8 @@ enum {
TD_DEF_MSG_TYPE(TDMT_DND_CONFIG_DNODE, "config-dnode", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_DND_SYSTABLE_RETRIEVE, "dnode-retrieve", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_DND_MAX_MSG, "dnd-max", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_DND_ALTER_MNODE_TYPE, "dnode-alter-mnode-type", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_DND_ALTER_VNODE_TYPE, "dnode-alter-vnode-type", NULL, NULL)
TD_NEW_MSG_SEG(TDMT_MND_MSG)
TD_DEF_MSG_TYPE(TDMT_MND_CONNECT, "connect", NULL, NULL)
@ -176,6 +178,7 @@ enum {
// TD_DEF_MSG_TYPE(TDMT_MND_STREAM_BEGIN_CHECKPOINT, "stream-begin-checkpoint", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_MND_MAX_MSG, "mnd-max", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_MND_BALANCE_VGROUP_LEADER, "balance-vgroup-leader", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_MND_RESTORE_DNODE, "restore-dnode", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_MND_PAUSE_STREAM, "pause-stream", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_MND_RESUME_STREAM, "resume-stream", NULL, NULL)
@ -225,7 +228,6 @@ enum {
TD_DEF_MSG_TYPE(TDMT_VND_COMMIT, "vnode-commit", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_CREATE_INDEX, "vnode-create-index", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_DROP_INDEX, "vnode-drop-index", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_DISABLE_WRITE, "vnode-disable-write", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_MAX_MSG, "vnd-max", NULL, NULL)
@ -304,9 +306,11 @@ enum {
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_SUBSCRIBE, "vnode-tmq-subscribe", SMqRebVgReq, SMqRebVgRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_DELETE_SUB, "vnode-tmq-delete-sub", SMqVDeleteReq, SMqVDeleteRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_COMMIT_OFFSET, "vnode-tmq-commit-offset", STqOffset, STqOffset)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_SEEK_TO_OFFSET, "vnode-tmq-seekto-offset", STqOffset, STqOffset)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_ADD_CHECKINFO, "vnode-tmq-add-checkinfo", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_DEL_CHECKINFO, "vnode-del-checkinfo", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_CONSUME, "vnode-tmq-consume", SMqPollReq, SMqDataBlkRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_VG_WALINFO, "vnode-tmq-vg-walinfo", SMqPollReq, SMqDataBlkRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TMQ_MAX_MSG, "vnd-tmq-max", NULL, NULL)

667
include/common/ttokendef.h
View File

@ -16,338 +16,341 @@
#ifndef _TD_COMMON_TOKEN_H_
#define _TD_COMMON_TOKEN_H_
#define TK_OR 1
#define TK_AND 2
#define TK_UNION 3
#define TK_ALL 4
#define TK_MINUS 5
#define TK_EXCEPT 6
#define TK_INTERSECT 7
#define TK_NK_BITAND 8
#define TK_NK_BITOR 9
#define TK_NK_LSHIFT 10
#define TK_NK_RSHIFT 11
#define TK_NK_PLUS 12
#define TK_NK_MINUS 13
#define TK_NK_STAR 14
#define TK_NK_SLASH 15
#define TK_NK_REM 16
#define TK_NK_CONCAT 17
#define TK_CREATE 18
#define TK_ACCOUNT 19
#define TK_NK_ID 20
#define TK_PASS 21
#define TK_NK_STRING 22
#define TK_ALTER 23
#define TK_PPS 24
#define TK_TSERIES 25
#define TK_STORAGE 26
#define TK_STREAMS 27
#define TK_QTIME 28
#define TK_DBS 29
#define TK_USERS 30
#define TK_CONNS 31
#define TK_STATE 32
#define TK_USER 33
#define TK_ENABLE 34
#define TK_NK_INTEGER 35
#define TK_SYSINFO 36
#define TK_DROP 37
#define TK_GRANT 38
#define TK_ON 39
#define TK_TO 40
#define TK_REVOKE 41
#define TK_FROM 42
#define TK_SUBSCRIBE 43
#define TK_NK_COMMA 44
#define TK_READ 45
#define TK_WRITE 46
#define TK_NK_DOT 47
#define TK_WITH 48
#define TK_DNODE 49
#define TK_PORT 50
#define TK_DNODES 51
#define TK_NK_IPTOKEN 52
#define TK_FORCE 53
#define TK_LOCAL 54
#define TK_QNODE 55
#define TK_BNODE 56
#define TK_SNODE 57
#define TK_MNODE 58
#define TK_DATABASE 59
#define TK_USE 60
#define TK_FLUSH 61
#define TK_TRIM 62
#define TK_COMPACT 63
#define TK_IF 64
#define TK_NOT 65
#define TK_EXISTS 66
#define TK_BUFFER 67
#define TK_CACHEMODEL 68
#define TK_CACHESIZE 69
#define TK_COMP 70
#define TK_DURATION 71
#define TK_NK_VARIABLE 72
#define TK_MAXROWS 73
#define TK_MINROWS 74
#define TK_KEEP 75
#define TK_PAGES 76
#define TK_PAGESIZE 77
#define TK_TSDB_PAGESIZE 78
#define TK_PRECISION 79
#define TK_REPLICA 80
#define TK_VGROUPS 81
#define TK_SINGLE_STABLE 82
#define TK_RETENTIONS 83
#define TK_SCHEMALESS 84
#define TK_WAL_LEVEL 85
#define TK_WAL_FSYNC_PERIOD 86
#define TK_WAL_RETENTION_PERIOD 87
#define TK_WAL_RETENTION_SIZE 88
#define TK_WAL_ROLL_PERIOD 89
#define TK_WAL_SEGMENT_SIZE 90
#define TK_STT_TRIGGER 91
#define TK_TABLE_PREFIX 92
#define TK_TABLE_SUFFIX 93
#define TK_NK_COLON 94
#define TK_MAX_SPEED 95
#define TK_START 96
#define TK_TIMESTAMP 97
#define TK_END 98
#define TK_TABLE 99
#define TK_NK_LP 100
#define TK_NK_RP 101
#define TK_STABLE 102
#define TK_ADD 103
#define TK_COLUMN 104
#define TK_MODIFY 105
#define TK_RENAME 106
#define TK_TAG 107
#define TK_SET 108
#define TK_NK_EQ 109
#define TK_USING 110
#define TK_TAGS 111
#define TK_BOOL 112
#define TK_TINYINT 113
#define TK_SMALLINT 114
#define TK_INT 115
#define TK_INTEGER 116
#define TK_BIGINT 117
#define TK_FLOAT 118
#define TK_DOUBLE 119
#define TK_BINARY 120
#define TK_NCHAR 121
#define TK_UNSIGNED 122
#define TK_JSON 123
#define TK_VARCHAR 124
#define TK_MEDIUMBLOB 125
#define TK_BLOB 126
#define TK_VARBINARY 127
#define TK_DECIMAL 128
#define TK_COMMENT 129
#define TK_MAX_DELAY 130
#define TK_WATERMARK 131
#define TK_ROLLUP 132
#define TK_TTL 133
#define TK_SMA 134
#define TK_DELETE_MARK 135
#define TK_FIRST 136
#define TK_LAST 137
#define TK_SHOW 138
#define TK_PRIVILEGES 139
#define TK_DATABASES 140
#define TK_TABLES 141
#define TK_STABLES 142
#define TK_MNODES 143
#define TK_QNODES 144
#define TK_FUNCTIONS 145
#define TK_INDEXES 146
#define TK_ACCOUNTS 147
#define TK_APPS 148
#define TK_CONNECTIONS 149
#define TK_LICENCES 150
#define TK_GRANTS 151
#define TK_QUERIES 152
#define TK_SCORES 153
#define TK_TOPICS 154
#define TK_VARIABLES 155
#define TK_CLUSTER 156
#define TK_BNODES 157
#define TK_SNODES 158
#define TK_TRANSACTIONS 159
#define TK_DISTRIBUTED 160
#define TK_CONSUMERS 161
#define TK_SUBSCRIPTIONS 162
#define TK_VNODES 163
#define TK_ALIVE 164
#define TK_LIKE 165
#define TK_TBNAME 166
#define TK_QTAGS 167
#define TK_AS 168
#define TK_INDEX 169
#define TK_FUNCTION 170
#define TK_INTERVAL 171
#define TK_COUNT 172
#define TK_LAST_ROW 173
#define TK_TOPIC 174
#define TK_META 175
#define TK_CONSUMER 176
#define TK_GROUP 177
#define TK_DESC 178
#define TK_DESCRIBE 179
#define TK_RESET 180
#define TK_QUERY 181
#define TK_CACHE 182
#define TK_EXPLAIN 183
#define TK_ANALYZE 184
#define TK_VERBOSE 185
#define TK_NK_BOOL 186
#define TK_RATIO 187
#define TK_NK_FLOAT 188
#define TK_OUTPUTTYPE 189
#define TK_AGGREGATE 190
#define TK_BUFSIZE 191
#define TK_LANGUAGE 192
#define TK_REPLACE 193
#define TK_STREAM 194
#define TK_INTO 195
#define TK_PAUSE 196
#define TK_RESUME 197
#define TK_TRIGGER 198
#define TK_AT_ONCE 199
#define TK_WINDOW_CLOSE 200
#define TK_IGNORE 201
#define TK_EXPIRED 202
#define TK_FILL_HISTORY 203
#define TK_UPDATE 204
#define TK_SUBTABLE 205
#define TK_UNTREATED 206
#define TK_KILL 207
#define TK_CONNECTION 208
#define TK_TRANSACTION 209
#define TK_BALANCE 210
#define TK_VGROUP 211
#define TK_LEADER 212
#define TK_MERGE 213
#define TK_REDISTRIBUTE 214
#define TK_SPLIT 215
#define TK_DELETE 216
#define TK_INSERT 217
#define TK_NULL 218
#define TK_NK_QUESTION 219
#define TK_NK_ARROW 220
#define TK_ROWTS 221
#define TK_QSTART 222
#define TK_QEND 223
#define TK_QDURATION 224
#define TK_WSTART 225
#define TK_WEND 226
#define TK_WDURATION 227
#define TK_IROWTS 228
#define TK_ISFILLED 229
#define TK_CAST 230
#define TK_NOW 231
#define TK_TODAY 232
#define TK_TIMEZONE 233
#define TK_CLIENT_VERSION 234
#define TK_SERVER_VERSION 235
#define TK_SERVER_STATUS 236
#define TK_CURRENT_USER 237
#define TK_CASE 238
#define TK_WHEN 239
#define TK_THEN 240
#define TK_ELSE 241
#define TK_BETWEEN 242
#define TK_IS 243
#define TK_NK_LT 244
#define TK_NK_GT 245
#define TK_NK_LE 246
#define TK_NK_GE 247
#define TK_NK_NE 248
#define TK_MATCH 249
#define TK_NMATCH 250
#define TK_CONTAINS 251
#define TK_IN 252
#define TK_JOIN 253
#define TK_INNER 254
#define TK_SELECT 255
#define TK_DISTINCT 256
#define TK_WHERE 257
#define TK_PARTITION 258
#define TK_BY 259
#define TK_SESSION 260
#define TK_STATE_WINDOW 261
#define TK_EVENT_WINDOW 262
#define TK_SLIDING 263
#define TK_FILL 264
#define TK_VALUE 265
#define TK_VALUE_F 266
#define TK_NONE 267
#define TK_PREV 268
#define TK_NULL_F 269
#define TK_LINEAR 270
#define TK_NEXT 271
#define TK_HAVING 272
#define TK_RANGE 273
#define TK_EVERY 274
#define TK_ORDER 275
#define TK_SLIMIT 276
#define TK_SOFFSET 277
#define TK_LIMIT 278
#define TK_OFFSET 279
#define TK_ASC 280
#define TK_NULLS 281
#define TK_ABORT 282
#define TK_AFTER 283
#define TK_ATTACH 284
#define TK_BEFORE 285
#define TK_BEGIN 286
#define TK_BITAND 287
#define TK_BITNOT 288
#define TK_BITOR 289
#define TK_BLOCKS 290
#define TK_CHANGE 291
#define TK_COMMA 292
#define TK_CONCAT 293
#define TK_CONFLICT 294
#define TK_COPY 295
#define TK_DEFERRED 296
#define TK_DELIMITERS 297
#define TK_DETACH 298
#define TK_DIVIDE 299
#define TK_DOT 300
#define TK_EACH 301
#define TK_FAIL 302
#define TK_FILE 303
#define TK_FOR 304
#define TK_GLOB 305
#define TK_ID 306
#define TK_IMMEDIATE 307
#define TK_IMPORT 308
#define TK_INITIALLY 309
#define TK_INSTEAD 310
#define TK_ISNULL 311
#define TK_KEY 312
#define TK_MODULES 313
#define TK_NK_BITNOT 314
#define TK_NK_SEMI 315
#define TK_NOTNULL 316
#define TK_OF 317
#define TK_PLUS 318
#define TK_PRIVILEGE 319
#define TK_RAISE 320
#define TK_RESTRICT 321
#define TK_ROW 322
#define TK_SEMI 323
#define TK_STAR 324
#define TK_STATEMENT 325
#define TK_STRICT 326
#define TK_STRING 327
#define TK_TIMES 328
#define TK_VALUES 329
#define TK_VARIABLE 330
#define TK_VIEW 331
#define TK_WAL 332
#define TK_OR 1
#define TK_AND 2
#define TK_UNION 3
#define TK_ALL 4
#define TK_MINUS 5
#define TK_EXCEPT 6
#define TK_INTERSECT 7
#define TK_NK_BITAND 8
#define TK_NK_BITOR 9
#define TK_NK_LSHIFT 10
#define TK_NK_RSHIFT 11
#define TK_NK_PLUS 12
#define TK_NK_MINUS 13
#define TK_NK_STAR 14
#define TK_NK_SLASH 15
#define TK_NK_REM 16
#define TK_NK_CONCAT 17
#define TK_CREATE 18
#define TK_ACCOUNT 19
#define TK_NK_ID 20
#define TK_PASS 21
#define TK_NK_STRING 22
#define TK_ALTER 23
#define TK_PPS 24
#define TK_TSERIES 25
#define TK_STORAGE 26
#define TK_STREAMS 27
#define TK_QTIME 28
#define TK_DBS 29
#define TK_USERS 30
#define TK_CONNS 31
#define TK_STATE 32
#define TK_USER 33
#define TK_ENABLE 34
#define TK_NK_INTEGER 35
#define TK_SYSINFO 36
#define TK_DROP 37
#define TK_GRANT 38
#define TK_ON 39
#define TK_TO 40
#define TK_REVOKE 41
#define TK_FROM 42
#define TK_SUBSCRIBE 43
#define TK_NK_COMMA 44
#define TK_READ 45
#define TK_WRITE 46
#define TK_NK_DOT 47
#define TK_WITH 48
#define TK_DNODE 49
#define TK_PORT 50
#define TK_DNODES 51
#define TK_RESTORE 52
#define TK_NK_IPTOKEN 53
#define TK_FORCE 54
#define TK_LOCAL 55
#define TK_QNODE 56
#define TK_BNODE 57
#define TK_SNODE 58
#define TK_MNODE 59
#define TK_VNODE 60
#define TK_DATABASE 61
#define TK_USE 62
#define TK_FLUSH 63
#define TK_TRIM 64
#define TK_COMPACT 65
#define TK_IF 66
#define TK_NOT 67
#define TK_EXISTS 68
#define TK_BUFFER 69
#define TK_CACHEMODEL 70
#define TK_CACHESIZE 71
#define TK_COMP 72
#define TK_DURATION 73
#define TK_NK_VARIABLE 74
#define TK_MAXROWS 75
#define TK_MINROWS 76
#define TK_KEEP 77
#define TK_PAGES 78
#define TK_PAGESIZE 79
#define TK_TSDB_PAGESIZE 80
#define TK_PRECISION 81
#define TK_REPLICA 82
#define TK_VGROUPS 83
#define TK_SINGLE_STABLE 84
#define TK_RETENTIONS 85
#define TK_SCHEMALESS 86
#define TK_WAL_LEVEL 87
#define TK_WAL_FSYNC_PERIOD 88
#define TK_WAL_RETENTION_PERIOD 89
#define TK_WAL_RETENTION_SIZE 90
#define TK_WAL_ROLL_PERIOD 91
#define TK_WAL_SEGMENT_SIZE 92
#define TK_STT_TRIGGER 93
#define TK_TABLE_PREFIX 94
#define TK_TABLE_SUFFIX 95
#define TK_NK_COLON 96
#define TK_MAX_SPEED 97
#define TK_START 98
#define TK_TIMESTAMP 99
#define TK_END 100
#define TK_TABLE 101
#define TK_NK_LP 102
#define TK_NK_RP 103
#define TK_STABLE 104
#define TK_ADD 105
#define TK_COLUMN 106
#define TK_MODIFY 107
#define TK_RENAME 108
#define TK_TAG 109
#define TK_SET 110
#define TK_NK_EQ 111
#define TK_USING 112
#define TK_TAGS 113
#define TK_BOOL 114
#define TK_TINYINT 115
#define TK_SMALLINT 116
#define TK_INT 117
#define TK_INTEGER 118
#define TK_BIGINT 119
#define TK_FLOAT 120
#define TK_DOUBLE 121
#define TK_BINARY 122
#define TK_NCHAR 123
#define TK_UNSIGNED 124
#define TK_JSON 125
#define TK_VARCHAR 126
#define TK_MEDIUMBLOB 127
#define TK_BLOB 128
#define TK_VARBINARY 129
#define TK_DECIMAL 130
#define TK_COMMENT 131
#define TK_MAX_DELAY 132
#define TK_WATERMARK 133
#define TK_ROLLUP 134
#define TK_TTL 135
#define TK_SMA 136
#define TK_DELETE_MARK 137
#define TK_FIRST 138
#define TK_LAST 139
#define TK_SHOW 140
#define TK_PRIVILEGES 141
#define TK_DATABASES 142
#define TK_TABLES 143
#define TK_STABLES 144
#define TK_MNODES 145
#define TK_QNODES 146
#define TK_FUNCTIONS 147
#define TK_INDEXES 148
#define TK_ACCOUNTS 149
#define TK_APPS 150
#define TK_CONNECTIONS 151
#define TK_LICENCES 152
#define TK_GRANTS 153
#define TK_QUERIES 154
#define TK_SCORES 155
#define TK_TOPICS 156
#define TK_VARIABLES 157
#define TK_CLUSTER 158
#define TK_BNODES 159
#define TK_SNODES 160
#define TK_TRANSACTIONS 161
#define TK_DISTRIBUTED 162
#define TK_CONSUMERS 163
#define TK_SUBSCRIPTIONS 164
#define TK_VNODES 165
#define TK_ALIVE 166
#define TK_LIKE 167
#define TK_TBNAME 168
#define TK_QTAGS 169
#define TK_AS 170
#define TK_INDEX 171
#define TK_FUNCTION 172
#define TK_INTERVAL 173
#define TK_COUNT 174
#define TK_LAST_ROW 175
#define TK_TOPIC 176
#define TK_META 177
#define TK_CONSUMER 178
#define TK_GROUP 179
#define TK_DESC 180
#define TK_DESCRIBE 181
#define TK_RESET 182
#define TK_QUERY 183
#define TK_CACHE 184
#define TK_EXPLAIN 185
#define TK_ANALYZE 186
#define TK_VERBOSE 187
#define TK_NK_BOOL 188
#define TK_RATIO 189
#define TK_NK_FLOAT 190
#define TK_OUTPUTTYPE 191
#define TK_AGGREGATE 192
#define TK_BUFSIZE 193
#define TK_LANGUAGE 194
#define TK_REPLACE 195
#define TK_STREAM 196
#define TK_INTO 197
#define TK_PAUSE 198
#define TK_RESUME 199
#define TK_TRIGGER 200
#define TK_AT_ONCE 201
#define TK_WINDOW_CLOSE 202
#define TK_IGNORE 203
#define TK_EXPIRED 204
#define TK_FILL_HISTORY 205
#define TK_UPDATE 206
#define TK_SUBTABLE 207
#define TK_UNTREATED 208
#define TK_KILL 209
#define TK_CONNECTION 210
#define TK_TRANSACTION 211
#define TK_BALANCE 212
#define TK_VGROUP 213
#define TK_LEADER 214
#define TK_MERGE 215
#define TK_REDISTRIBUTE 216
#define TK_SPLIT 217
#define TK_DELETE 218
#define TK_INSERT 219
#define TK_NULL 220
#define TK_NK_QUESTION 221
#define TK_NK_ARROW 222
#define TK_ROWTS 223
#define TK_QSTART 224
#define TK_QEND 225
#define TK_QDURATION 226
#define TK_WSTART 227
#define TK_WEND 228
#define TK_WDURATION 229
#define TK_IROWTS 230
#define TK_ISFILLED 231
#define TK_CAST 232
#define TK_NOW 233
#define TK_TODAY 234
#define TK_TIMEZONE 235
#define TK_CLIENT_VERSION 236
#define TK_SERVER_VERSION 237
#define TK_SERVER_STATUS 238
#define TK_CURRENT_USER 239
#define TK_CASE 240
#define TK_WHEN 241
#define TK_THEN 242
#define TK_ELSE 243
#define TK_BETWEEN 244
#define TK_IS 245
#define TK_NK_LT 246
#define TK_NK_GT 247
#define TK_NK_LE 248
#define TK_NK_GE 249
#define TK_NK_NE 250
#define TK_MATCH 251
#define TK_NMATCH 252
#define TK_CONTAINS 253
#define TK_IN 254
#define TK_JOIN 255
#define TK_INNER 256
#define TK_SELECT 257
#define TK_DISTINCT 258
#define TK_WHERE 259
#define TK_PARTITION 260
#define TK_BY 261
#define TK_SESSION 262
#define TK_STATE_WINDOW 263
#define TK_EVENT_WINDOW 264
#define TK_SLIDING 265
#define TK_FILL 266
#define TK_VALUE 267
#define TK_VALUE_F 268
#define TK_NONE 269
#define TK_PREV 270
#define TK_NULL_F 271
#define TK_LINEAR 272
#define TK_NEXT 273
#define TK_HAVING 274
#define TK_RANGE 275
#define TK_EVERY 276
#define TK_ORDER 277
#define TK_SLIMIT 278
#define TK_SOFFSET 279
#define TK_LIMIT 280
#define TK_OFFSET 281
#define TK_ASC 282
#define TK_NULLS 283
#define TK_ABORT 284
#define TK_AFTER 285
#define TK_ATTACH 286
#define TK_BEFORE 287
#define TK_BEGIN 288
#define TK_BITAND 289
#define TK_BITNOT 290
#define TK_BITOR 291
#define TK_BLOCKS 292
#define TK_CHANGE 293
#define TK_COMMA 294
#define TK_CONCAT 295
#define TK_CONFLICT 296
#define TK_COPY 297
#define TK_DEFERRED 298
#define TK_DELIMITERS 299
#define TK_DETACH 300
#define TK_DIVIDE 301
#define TK_DOT 302
#define TK_EACH 303
#define TK_FAIL 304
#define TK_FILE 305
#define TK_FOR 306
#define TK_GLOB 307
#define TK_ID 308
#define TK_IMMEDIATE 309
#define TK_IMPORT 310
#define TK_INITIALLY 311
#define TK_INSTEAD 312
#define TK_ISNULL 313
#define TK_KEY 314
#define TK_MODULES 315
#define TK_NK_BITNOT 316
#define TK_NK_SEMI 317
#define TK_NOTNULL 318
#define TK_OF 319
#define TK_PLUS 320
#define TK_PRIVILEGE 321
#define TK_RAISE 322
#define TK_RESTRICT 323
#define TK_ROW 324
#define TK_SEMI 325
#define TK_STAR 326
#define TK_STATEMENT 327
#define TK_STRICT 328
#define TK_STRING 329
#define TK_TIMES 330
#define TK_VALUES 331
#define TK_VARIABLE 332
#define TK_VIEW 333
#define TK_WAL 334
#define TK_NK_SPACE 600
#define TK_NK_COMMENT 601

9
include/dnode/mnode/mnode.h
View File

@ -20,6 +20,7 @@
#include "tmsg.h"
#include "tmsgcb.h"
#include "trpc.h"
#include "sync.h"
#ifdef __cplusplus
extern "C" {
@ -33,8 +34,11 @@ typedef struct {
bool deploy;
int8_t selfIndex;
int8_t numOfReplicas;
SReplica replicas[TSDB_MAX_REPLICA];
int8_t numOfTotalReplicas;
SReplica replicas[TSDB_MAX_REPLICA + TSDB_MAX_LEARNER_REPLICA];
int32_t nodeRoles[TSDB_MAX_REPLICA + TSDB_MAX_LEARNER_REPLICA];
SMsgCb msgCb;
int64_t lastIndex;
} SMnodeOpt;
/* ------------------------ SMnode ------------------------ */
@ -69,6 +73,9 @@ int32_t mndStart(SMnode *pMnode);
*/
void mndStop(SMnode *pMnode);
int32_t mndIsCatchUp(SMnode *pMnode);
ESyncRole mndGetRole(SMnode *pMnode);
/**
* @brief Get mnode monitor info.
*

10
include/libs/function/function.h
View File

@ -99,11 +99,11 @@ typedef struct SSubsidiaryResInfo {
} SSubsidiaryResInfo;
typedef struct SResultDataInfo {
int16_t precision;
int16_t scale;
int16_t type;
int16_t bytes;
int32_t interBufSize;
int16_t precision;
int16_t scale;
int16_t type;
uint16_t bytes;
int32_t interBufSize;
} SResultDataInfo;
#define GET_RES_INFO(ctx) ((ctx)->resultInfo)

5
include/libs/nodes/cmdnodes.h
View File

@ -350,6 +350,11 @@ typedef struct SDropComponentNodeStmt {
int32_t dnodeId;
} SDropComponentNodeStmt;
typedef struct SRestoreComponentNodeStmt {
ENodeType type;
int32_t dnodeId;
} SRestoreComponentNodeStmt;
typedef struct SCreateTopicStmt {
ENodeType type;
char topicName[TSDB_TABLE_NAME_LEN];

4
include/libs/nodes/nodes.h
View File

@ -211,6 +211,10 @@ typedef enum ENodeType {
QUERY_NODE_SHOW_DB_ALIVE_STMT,
QUERY_NODE_SHOW_CLUSTER_ALIVE_STMT,
QUERY_NODE_BALANCE_VGROUP_LEADER_STMT,
QUERY_NODE_RESTORE_DNODE_STMT,
QUERY_NODE_RESTORE_QNODE_STMT,
QUERY_NODE_RESTORE_MNODE_STMT,
QUERY_NODE_RESTORE_VNODE_STMT,
QUERY_NODE_PAUSE_STREAM_STMT,
QUERY_NODE_RESUME_STREAM_STMT,

2
include/libs/nodes/plannodes.h
View File

@ -185,6 +185,7 @@ typedef struct SMergeLogicNode {
int32_t numOfChannels;
int32_t srcGroupId;
bool groupSort;
bool ignoreGroupId;
} SMergeLogicNode;
typedef enum EWindowType {
@ -444,6 +445,7 @@ typedef struct SMergePhysiNode {
int32_t numOfChannels;
int32_t srcGroupId;
bool groupSort;
bool ignoreGroupId;
} SMergePhysiNode;
typedef struct SWinodwPhysiNode {

2
include/libs/parser/parser.h
View File

@ -114,7 +114,7 @@ STableDataCxt* smlInitTableDataCtx(SQuery* query, STableMeta* pTableMeta);
int32_t smlBindData(SQuery* handle, bool dataFormat, SArray* tags, SArray* colsSchema, SArray* cols,
STableMeta* pTableMeta, char* tableName, const char* sTableName, int32_t sTableNameLen, int32_t ttl,
char* msgBuf, int16_t msgBufLen);
char* msgBuf, int32_t msgBufLen);
int32_t smlBuildOutput(SQuery* handle, SHashObj* pVgHash);
int rawBlockBindData(SQuery *query, STableMeta* pTableMeta, void* data, SVCreateTbReq* pCreateTb, TAOS_FIELD *fields, int numFields, bool needChangeLength);

3
include/libs/stream/tstream.h
View File

@ -204,8 +204,6 @@ static FORCE_INLINE void streamQueueProcessFail(SStreamQueue* queue) {
atomic_store_8(&queue->status, STREAM_QUEUE__FAILED);
}
static FORCE_INLINE void* streamQueueCurItem(SStreamQueue* queue) { return queue->qItem; }
void* streamQueueNextItem(SStreamQueue* queue);
SStreamDataSubmit2* streamDataSubmitNew(SPackedData submit, int32_t type);
@ -238,6 +236,7 @@ typedef struct {
void* vnode; // not available to encoder and decoder
FTbSink* tbSinkFunc;
STSchema* pTSchema;
SSHashObj* pTblInfo;
} STaskSinkTb;
typedef void FSmaSink(void* vnode, int64_t smaId, const SArray* data);

25
include/libs/sync/sync.h
View File

@ -55,6 +55,8 @@ extern "C" {
#define SYNC_INDEX_INVALID -1
#define SYNC_TERM_INVALID -1
#define SYNC_LEARNER_CATCHUP 10
typedef enum {
SYNC_STRATEGY_NO_SNAPSHOT = 0,
SYNC_STRATEGY_STANDARD_SNAPSHOT = 1,
@ -76,19 +78,29 @@ typedef enum {
TAOS_SYNC_STATE_CANDIDATE = 101,
TAOS_SYNC_STATE_LEADER = 102,
TAOS_SYNC_STATE_ERROR = 103,
TAOS_SYNC_STATE_LEARNER = 104,
} ESyncState;
typedef enum {
TAOS_SYNC_ROLE_VOTER = 0,
TAOS_SYNC_ROLE_LEARNER = 1,
TAOS_SYNC_ROLE_ERROR = 2,
} ESyncRole;
typedef struct SNodeInfo {
int64_t clusterId;
int32_t nodeId;
uint16_t nodePort;
char nodeFqdn[TSDB_FQDN_LEN];
int64_t clusterId;
int32_t nodeId;
uint16_t nodePort;
char nodeFqdn[TSDB_FQDN_LEN];
ESyncRole nodeRole;
} SNodeInfo;
typedef struct SSyncCfg {
int32_t totalReplicaNum;
int32_t replicaNum;
int32_t myIndex;
SNodeInfo nodeInfo[TSDB_MAX_REPLICA];
SNodeInfo nodeInfo[TSDB_MAX_REPLICA + TSDB_MAX_LEARNER_REPLICA];
SyncIndex lastIndex;
} SSyncCfg;
typedef struct SFsmCbMeta {
@ -155,6 +167,7 @@ typedef struct SSyncFSM {
void (*FpBecomeLeaderCb)(const struct SSyncFSM* pFsm);
void (*FpBecomeFollowerCb)(const struct SSyncFSM* pFsm);
void (*FpBecomeLearnerCb)(const struct SSyncFSM* pFsm);
int32_t (*FpGetSnapshot)(const struct SSyncFSM* pFsm, SSnapshot* pSnapshot, void* pReaderParam, void** ppReader);
void (*FpGetSnapshotInfo)(const struct SSyncFSM* pFsm, SSnapshot* pSnapshot);
@ -236,6 +249,8 @@ void syncStop(int64_t rid);
void syncPreStop(int64_t rid);
void syncPostStop(int64_t rid);
int32_t syncPropose(int64_t rid, SRpcMsg* pMsg, bool isWeak, int64_t* seq);
int32_t syncIsCatchUp(int64_t rid);
ESyncRole syncGetRole(int64_t rid);
int32_t syncProcessMsg(int64_t rid, SRpcMsg* pMsg);
int32_t syncReconfig(int64_t rid, SSyncCfg* pCfg);
int32_t syncBeginSnapshot(int64_t rid, int64_t lastApplyIndex);

10
include/libs/tfs/tfs.h
View File

@ -133,6 +133,16 @@ int32_t tfsMkdirAt(STfs *pTfs, const char *rname, SDiskID diskId);
*/
int32_t tfsMkdirRecurAt(STfs *pTfs, const char *rname, SDiskID diskId);
/**
* @brief check directories exist in tfs.
*
* @param pTfs The fs object.
* @param rname The rel name of directory.
* @param diskId The disk ID.
* @return true for exist, false for not exist.
*/
bool tfsDirExistAt(STfs *pTfs, const char *rname, SDiskID diskId);
/**
* @brief Remove directory at all levels in tfs.
*

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

@ -127,12 +127,12 @@ typedef struct SWal {
typedef struct {
int64_t refId;
int64_t refVer;
// int64_t refFile;
SWal *pWal;
// int64_t refFile;
SWal *pWal;
} SWalRef;
typedef struct {
// int8_t scanUncommited;
int8_t scanUncommited;
int8_t scanNotApplied;
int8_t scanMeta;
int8_t enableRef;
@ -190,15 +190,16 @@ int32_t walApplyVer(SWal *, int64_t ver);
// int32_t walDataCorrupted(SWal*);
// read
// wal reader
SWalReader *walOpenReader(SWal *, SWalFilterCond *pCond);
void walCloseReader(SWalReader *pRead);
void walReadReset(SWalReader *pReader);
int32_t walReadVer(SWalReader *pRead, int64_t ver);
int32_t walReaderSeekVer(SWalReader *pRead, int64_t ver);
int32_t walNextValidMsg(SWalReader *pRead);
int64_t walReaderGetCurrentVer(const SWalReader* pReader);
int64_t walReaderGetValidFirstVer(const SWalReader* pReader);
int64_t walReaderGetCurrentVer(const SWalReader *pReader);
int64_t walReaderGetValidFirstVer(const SWalReader *pReader);
void walReaderValidVersionRange(SWalReader *pReader, int64_t *sver, int64_t *ever);
// only for tq usage
void walSetReaderCapacity(SWalReader *pRead, int32_t capacity);

76
include/util/taoserror.h
View File

@ -103,7 +103,7 @@ int32_t* taosGetErrno();
#define TSDB_CODE_CHECKSUM_ERROR TAOS_DEF_ERROR_CODE(0, 0x011F) // internal
#define TSDB_CODE_COMPRESS_ERROR TAOS_DEF_ERROR_CODE(0, 0x0120)
#define TSDB_CODE_MSG_NOT_PROCESSED TAOS_DEF_ERROR_CODE(0, 0x0121) //
#define TSDB_CODE_MSG_NOT_PROCESSED TAOS_DEF_ERROR_CODE(0, 0x0121)
#define TSDB_CODE_CFG_NOT_FOUND TAOS_DEF_ERROR_CODE(0, 0x0122)
#define TSDB_CODE_REPEAT_INIT TAOS_DEF_ERROR_CODE(0, 0x0123)
#define TSDB_CODE_DUP_KEY TAOS_DEF_ERROR_CODE(0, 0x0124)
@ -118,9 +118,10 @@ int32_t* taosGetErrno();
#define TSDB_CODE_MSG_ENCODE_ERROR TAOS_DEF_ERROR_CODE(0, 0x012D)
#define TSDB_CODE_NO_ENOUGH_DISKSPACE TAOS_DEF_ERROR_CODE(0, 0x012E)
#define TSDB_CODE_APP_IS_STARTING TAOS_DEF_ERROR_CODE(0, 0x0130) //
#define TSDB_CODE_APP_IS_STOPPING TAOS_DEF_ERROR_CODE(0, 0x0131) //
#define TSDB_CODE_IVLD_DATA_FMT TAOS_DEF_ERROR_CODE(0, 0x0132) //
#define TSDB_CODE_APP_IS_STARTING TAOS_DEF_ERROR_CODE(0, 0x0130)
#define TSDB_CODE_APP_IS_STOPPING TAOS_DEF_ERROR_CODE(0, 0x0131)
#define TSDB_CODE_INVALID_DATA_FMT TAOS_DEF_ERROR_CODE(0, 0x0132)
#define TSDB_CODE_INVALID_CFG_VALUE TAOS_DEF_ERROR_CODE(0, 0x0133)
//client
#define TSDB_CODE_TSC_INVALID_OPERATION TAOS_DEF_ERROR_CODE(0, 0x0200)
@ -404,6 +405,9 @@ int32_t* taosGetErrno();
#define TSDB_CODE_SNODE_ALREADY_DEPLOYED TAOS_DEF_ERROR_CODE(0, 0x040F)
#define TSDB_CODE_SNODE_NOT_FOUND TAOS_DEF_ERROR_CODE(0, 0x0410)
#define TSDB_CODE_SNODE_NOT_DEPLOYED TAOS_DEF_ERROR_CODE(0, 0x0411)
#define TSDB_CODE_MNODE_NOT_CATCH_UP TAOS_DEF_ERROR_CODE(0, 0x0412) // internal
#define TSDB_CODE_MNODE_ALREADY_IS_VOTER TAOS_DEF_ERROR_CODE(0, 0x0413) // internal
#define TSDB_CODE_MNODE_ONLY_TWO_MNODE TAOS_DEF_ERROR_CODE(0, 0x0414) // internal
// vnode
// #define TSDB_CODE_VND_ACTION_IN_PROGRESS TAOS_DEF_ERROR_CODE(0, 0x0500) // 2.x
@ -438,6 +442,9 @@ int32_t* taosGetErrno();
#define TSDB_CODE_VND_STOPPED TAOS_DEF_ERROR_CODE(0, 0x0529)
#define TSDB_CODE_VND_DUP_REQUEST TAOS_DEF_ERROR_CODE(0, 0x0530)
#define TSDB_CODE_VND_QUERY_BUSY TAOS_DEF_ERROR_CODE(0, 0x0531)
#define TSDB_CODE_VND_NOT_CATCH_UP TAOS_DEF_ERROR_CODE(0, 0x0532) // internal
#define TSDB_CODE_VND_ALREADY_IS_VOTER TAOS_DEF_ERROR_CODE(0, 0x0533) // internal
#define TSDB_CODE_VND_DIR_ALREADY_EXIST TAOS_DEF_ERROR_CODE(0, 0x0534)
// tsdb
#define TSDB_CODE_TDB_INVALID_TABLE_ID TAOS_DEF_ERROR_CODE(0, 0x0600)
@ -535,20 +542,20 @@ int32_t* taosGetErrno();
// #define TSDB_CODE_SYN_INVALID_CHECKSUM TAOS_DEF_ERROR_CODE(0, 0x0908) // 2.x
// #define TSDB_CODE_SYN_INVALID_MSGLEN TAOS_DEF_ERROR_CODE(0, 0x0909) // 2.x
// #define TSDB_CODE_SYN_INVALID_MSGTYPE TAOS_DEF_ERROR_CODE(0, 0x090A) // 2.x
#define TSDB_CODE_SYN_IS_LEADER TAOS_DEF_ERROR_CODE(0, 0x090B)
// #define TSDB_CODE_SYN_IS_LEADER TAOS_DEF_ERROR_CODE(0, 0x090B) // unused
#define TSDB_CODE_SYN_NOT_LEADER TAOS_DEF_ERROR_CODE(0, 0x090C)
#define TSDB_CODE_SYN_ONE_REPLICA TAOS_DEF_ERROR_CODE(0, 0x090D)
#define TSDB_CODE_SYN_NOT_IN_NEW_CONFIG TAOS_DEF_ERROR_CODE(0, 0x090E)
#define TSDB_CODE_SYN_NEW_CONFIG_ERROR TAOS_DEF_ERROR_CODE(0, 0x090F) // internal
#define TSDB_CODE_SYN_RECONFIG_NOT_READY TAOS_DEF_ERROR_CODE(0, 0x0910)
// #define TSDB_CODE_SYN_ONE_REPLICA TAOS_DEF_ERROR_CODE(0, 0x090D) // unused
// #define TSDB_CODE_SYN_NOT_IN_NEW_CONFIG TAOS_DEF_ERROR_CODE(0, 0x090E) // unused
#define TSDB_CODE_SYN_NEW_CONFIG_ERROR TAOS_DEF_ERROR_CODE(0, 0x090F) // internal
// #define TSDB_CODE_SYN_RECONFIG_NOT_READY TAOS_DEF_ERROR_CODE(0, 0x0910) // unused
#define TSDB_CODE_SYN_PROPOSE_NOT_READY TAOS_DEF_ERROR_CODE(0, 0x0911)
#define TSDB_CODE_SYN_STANDBY_NOT_READY TAOS_DEF_ERROR_CODE(0, 0x0912)
#define TSDB_CODE_SYN_BATCH_ERROR TAOS_DEF_ERROR_CODE(0, 0x0913)
// #define TSDB_CODE_SYN_STANDBY_NOT_READY TAOS_DEF_ERROR_CODE(0, 0x0912) // unused
// #define TSDB_CODE_SYN_BATCH_ERROR TAOS_DEF_ERROR_CODE(0, 0x0913) // unused
#define TSDB_CODE_SYN_RESTORING TAOS_DEF_ERROR_CODE(0, 0x0914)
#define TSDB_CODE_SYN_INVALID_SNAPSHOT_MSG TAOS_DEF_ERROR_CODE(0, 0x0915) // internal
#define TSDB_CODE_SYN_INVALID_SNAPSHOT_MSG TAOS_DEF_ERROR_CODE(0, 0x0915) // internal
#define TSDB_CODE_SYN_BUFFER_FULL TAOS_DEF_ERROR_CODE(0, 0x0916)
#define TSDB_CODE_SYN_WRITE_STALL TAOS_DEF_ERROR_CODE(0, 0x0917)
#define TSDB_CODE_SYN_NEGO_WIN_EXCEEDED TAOS_DEF_ERROR_CODE(0, 0X0918)
#define TSDB_CODE_SYN_NEGOTIATION_WIN_FULL TAOS_DEF_ERROR_CODE(0, 0x0918)
#define TSDB_CODE_SYN_INTERNAL_ERROR TAOS_DEF_ERROR_CODE(0, 0x09FF)
// tq
@ -569,7 +576,7 @@ int32_t* taosGetErrno();
// wal
// #define TSDB_CODE_WAL_APP_ERROR TAOS_DEF_ERROR_CODE(0, 0x1000) // 2.x
#define TSDB_CODE_WAL_FILE_CORRUPTED TAOS_DEF_ERROR_CODE(0, 0x1001)
#define TSDB_CODE_WAL_SIZE_LIMIT TAOS_DEF_ERROR_CODE(0, 0x1002)
// #define TSDB_CODE_WAL_SIZE_LIMIT TAOS_DEF_ERROR_CODE(0, 0x1002) // unused
#define TSDB_CODE_WAL_INVALID_VER TAOS_DEF_ERROR_CODE(0, 0x1003)
// #define TSDB_CODE_WAL_OUT_OF_MEMORY TAOS_DEF_ERROR_CODE(0, 0x1004) // 2.x
#define TSDB_CODE_WAL_LOG_NOT_EXIST TAOS_DEF_ERROR_CODE(0, 0x1005)
@ -713,15 +720,13 @@ int32_t* taosGetErrno();
#define TSDB_CODE_UDF_STOPPING TAOS_DEF_ERROR_CODE(0, 0x2901)
#define TSDB_CODE_UDF_PIPE_READ_ERR TAOS_DEF_ERROR_CODE(0, 0x2902)
#define TSDB_CODE_UDF_PIPE_CONNECT_ERR TAOS_DEF_ERROR_CODE(0, 0x2903)
#define TSDB_CODE_UDF_PIPE_NO_PIPE TAOS_DEF_ERROR_CODE(0, 0x2904)
#define TSDB_CODE_UDF_PIPE_NOT_EXIST TAOS_DEF_ERROR_CODE(0, 0x2904)
#define TSDB_CODE_UDF_LOAD_UDF_FAILURE TAOS_DEF_ERROR_CODE(0, 0x2905)
#define TSDB_CODE_UDF_INVALID_STATE TAOS_DEF_ERROR_CODE(0, 0x2906)
#define TSDB_CODE_UDF_INVALID_INPUT TAOS_DEF_ERROR_CODE(0, 0x2907)
#define TSDB_CODE_UDF_NO_FUNC_HANDLE TAOS_DEF_ERROR_CODE(0, 0x2908)
#define TSDB_CODE_UDF_INVALID_BUFSIZE TAOS_DEF_ERROR_CODE(0, 0x2909)
#define TSDB_CODE_UDF_INVALID_OUTPUT_TYPE TAOS_DEF_ERROR_CODE(0, 0x290A)
#define TSDB_CODE_UDF_SCRIPT_NOT_SUPPORTED TAOS_DEF_ERROR_CODE(0, 0x290B)
#define TSDB_CODE_UDF_FUNC_EXEC_FAILURE TAOS_DEF_ERROR_CODE(0, 0x290C)
#define TSDB_CODE_UDF_INVALID_INPUT TAOS_DEF_ERROR_CODE(0, 0x2906)
#define TSDB_CODE_UDF_INVALID_BUFSIZE TAOS_DEF_ERROR_CODE(0, 0x2907)
#define TSDB_CODE_UDF_INVALID_OUTPUT_TYPE TAOS_DEF_ERROR_CODE(0, 0x2908)
#define TSDB_CODE_UDF_SCRIPT_NOT_SUPPORTED TAOS_DEF_ERROR_CODE(0, 0x2909)
#define TSDB_CODE_UDF_FUNC_EXEC_FAILURE TAOS_DEF_ERROR_CODE(0, 0x290A)
// sml
#define TSDB_CODE_SML_INVALID_PROTOCOL_TYPE TAOS_DEF_ERROR_CODE(0, 0x3000)
@ -734,28 +739,21 @@ int32_t* taosGetErrno();
//tsma
#define TSDB_CODE_TSMA_INIT_FAILED TAOS_DEF_ERROR_CODE(0, 0x3100)
#define TSDB_CODE_TSMA_ALREADY_EXIST TAOS_DEF_ERROR_CODE(0, 0x3101)
#define TSDB_CODE_TSMA_NO_INDEX_IN_META TAOS_DEF_ERROR_CODE(0, 0x3102)
#define TSDB_CODE_TSMA_INVALID_ENV TAOS_DEF_ERROR_CODE(0, 0x3103)
#define TSDB_CODE_TSMA_INVALID_STAT TAOS_DEF_ERROR_CODE(0, 0x3104)
#define TSDB_CODE_TSMA_INVALID_PTR TAOS_DEF_ERROR_CODE(0, 0x3105)
#define TSDB_CODE_TSMA_INVALID_PARA TAOS_DEF_ERROR_CODE(0, 0x3106)
#define TSDB_CODE_TSMA_NO_INDEX_IN_CACHE TAOS_DEF_ERROR_CODE(0, 0x3107)
#define TSDB_CODE_TSMA_INVALID_ENV TAOS_DEF_ERROR_CODE(0, 0x3102)
#define TSDB_CODE_TSMA_INVALID_STAT TAOS_DEF_ERROR_CODE(0, 0x3103)
#define TSDB_CODE_TSMA_INVALID_PTR TAOS_DEF_ERROR_CODE(0, 0x3104)
#define TSDB_CODE_TSMA_INVALID_PARA TAOS_DEF_ERROR_CODE(0, 0x3105)
//rsma
#define TSDB_CODE_RSMA_INVALID_ENV TAOS_DEF_ERROR_CODE(0, 0x3150)
#define TSDB_CODE_RSMA_INVALID_STAT TAOS_DEF_ERROR_CODE(0, 0x3151)
#define TSDB_CODE_RSMA_QTASKINFO_CREATE TAOS_DEF_ERROR_CODE(0, 0x3152)
#define TSDB_CODE_RSMA_FS_COMMIT TAOS_DEF_ERROR_CODE(0, 0x3153)
#define TSDB_CODE_RSMA_REMOVE_EXISTS TAOS_DEF_ERROR_CODE(0, 0x3154)
#define TSDB_CODE_RSMA_FETCH_MSG_MSSED_UP TAOS_DEF_ERROR_CODE(0, 0x3155)
#define TSDB_CODE_RSMA_EMPTY_INFO TAOS_DEF_ERROR_CODE(0, 0x3156)
#define TSDB_CODE_RSMA_INVALID_SCHEMA TAOS_DEF_ERROR_CODE(0, 0x3157)
#define TSDB_CODE_RSMA_REGEX_MATCH TAOS_DEF_ERROR_CODE(0, 0x3158)
#define TSDB_CODE_RSMA_STREAM_STATE_OPEN TAOS_DEF_ERROR_CODE(0, 0x3159)
#define TSDB_CODE_RSMA_STREAM_STATE_COMMIT TAOS_DEF_ERROR_CODE(0, 0x3160)
#define TSDB_CODE_RSMA_FS_REF TAOS_DEF_ERROR_CODE(0, 0x3161)
#define TSDB_CODE_RSMA_FS_SYNC TAOS_DEF_ERROR_CODE(0, 0x3162)
#define TSDB_CODE_RSMA_FS_UPDATE TAOS_DEF_ERROR_CODE(0, 0x3163)
#define TSDB_CODE_RSMA_INVALID_SCHEMA TAOS_DEF_ERROR_CODE(0, 0x3153)
#define TSDB_CODE_RSMA_STREAM_STATE_OPEN TAOS_DEF_ERROR_CODE(0, 0x3154)
#define TSDB_CODE_RSMA_STREAM_STATE_COMMIT TAOS_DEF_ERROR_CODE(0, 0x3155)
#define TSDB_CODE_RSMA_FS_REF TAOS_DEF_ERROR_CODE(0, 0x3156)
#define TSDB_CODE_RSMA_FS_SYNC TAOS_DEF_ERROR_CODE(0, 0x3157)
#define TSDB_CODE_RSMA_FS_UPDATE TAOS_DEF_ERROR_CODE(0, 0x3158)
//index
#define TSDB_CODE_INDEX_REBUILDING TAOS_DEF_ERROR_CODE(0, 0x3200)

19
include/util/tdef.h
View File

@ -232,13 +232,7 @@ typedef enum ELogicConditionType {
#define TSDB_QUERY_ID_LEN 26
#define TSDB_TRANS_OPER_LEN 16
/**
* In some scenarios uint16_t (0~65535) is used to store the row len.
* - Firstly, we use 65531(65535 - 4), as the SDataRow/SKVRow contains 4 bits header.
* - Secondly, if all cols are VarDataT type except primary key, we need 4 bits to store the offset, thus
* the final value is 65531-(4096-1)*4 = 49151.
*/
#define TSDB_MAX_BYTES_PER_ROW 49151
#define TSDB_MAX_BYTES_PER_ROW 65531 // 49151:65531
#define TSDB_MAX_TAGS_LEN 16384
#define TSDB_MAX_TAGS 128
@ -273,6 +267,9 @@ typedef enum ELogicConditionType {
#define TSDB_DNODE_CONFIG_LEN 128
#define TSDB_DNODE_VALUE_LEN 256
#define TSDB_ACTIVE_KEY_LEN 109 // history 109:?
#define TSDB_CONN_ACTIVE_KEY_LEN 257 // history 257:?
#define TSDB_DEFAULT_PKT_SIZE 65480 // same as RPC_MAX_UDP_SIZE
#define TSDB_PAYLOAD_SIZE TSDB_DEFAULT_PKT_SIZE
@ -285,7 +282,7 @@ typedef enum ELogicConditionType {
#define TSDB_DNODE_ROLE_VNODE 2
#define TSDB_MAX_REPLICA 5
#define TSDB_MAX_LEARNER_REPLICA 10
#define TSDB_SYNC_LOG_BUFFER_SIZE 4096
#define TSDB_SYNC_LOG_BUFFER_RETENTION 256
#define TSDB_SYNC_APPLYQ_SIZE_LIMIT 512
@ -410,9 +407,9 @@ typedef enum ELogicConditionType {
#define TSDB_EXPLAIN_RESULT_ROW_SIZE (16 * 1024)
#define TSDB_EXPLAIN_RESULT_COLUMN_NAME "QUERY_PLAN"
#define TSDB_MAX_FIELD_LEN 16384
#define TSDB_MAX_BINARY_LEN (TSDB_MAX_FIELD_LEN - TSDB_KEYSIZE) // keep 16384
#define TSDB_MAX_NCHAR_LEN (TSDB_MAX_FIELD_LEN - TSDB_KEYSIZE) // keep 16384
#define TSDB_MAX_FIELD_LEN 65519 // 16384:65519
#define TSDB_MAX_BINARY_LEN TSDB_MAX_FIELD_LEN // 16384-8:65519
#define TSDB_MAX_NCHAR_LEN TSDB_MAX_FIELD_LEN // 16384-8:65519
#define PRIMARYKEY_TIMESTAMP_COL_ID 1
#define COL_REACH_END(colId, maxColId) ((colId) > (maxColId))

6
include/util/tlog.h
View File

@ -83,6 +83,12 @@ void taosPrintLongString(const char *flags, ELogLevel level, int32_t dflag, cons
#endif
;
void taosPrintSlowLog(const char *format, ...)
#ifdef __GNUC__
__attribute__((format(printf, 1, 2)))
#endif
;
bool taosAssertDebug(bool condition, const char *file, int32_t line, const char *format, ...);
bool taosAssertRelease(bool condition);

10
source/client/inc/clientInt.h
View File

@ -63,6 +63,7 @@ typedef struct {
// statistics
int32_t reportCnt;
int32_t connKeyCnt;
int32_t passKeyCnt; // with passVer call back
int64_t reportBytes; // not implemented
int64_t startTime;
// ctl
@ -126,6 +127,12 @@ typedef struct SAppInfo {
TdThreadMutex mutex;
} SAppInfo;
typedef struct {
int32_t ver;
void* param;
__taos_notify_fn_t fp;
} SPassInfo;
typedef struct STscObj {
char user[TSDB_USER_LEN];
char pass[TSDB_PASSWORD_LEN];
@ -141,6 +148,7 @@ typedef struct STscObj {
int32_t numOfReqs; // number of sqlObj bound to this connection
SAppInstInfo* pAppInfo;
SHashObj* pRequests;
SPassInfo passInfo;
} STscObj;
typedef struct STscDbg {
@ -354,7 +362,7 @@ void stopAllRequests(SHashObj* pRequests);
// conn level
int hbRegisterConn(SAppHbMgr* pAppHbMgr, int64_t tscRefId, int64_t clusterId, int8_t connType);
void hbDeregisterConn(SAppHbMgr* pAppHbMgr, SClientHbKey connKey);
void hbDeregisterConn(STscObj* pTscObj, SClientHbKey connKey);
typedef struct SSqlCallbackWrapper {
SParseContext* pParseCtx;

23
source/client/src/clientEnv.c
View File

@ -42,7 +42,7 @@ SAppInfo appInfo;
int64_t lastClusterId = 0;
int32_t clientReqRefPool = -1;
int32_t clientConnRefPool = -1;
int32_t clientStop = 0;
int32_t clientStop = -1;
int32_t timestampDeltaLimit = 900; // s
@ -69,7 +69,6 @@ static int32_t registerRequest(SRequestObj *pRequest, STscObj *pTscObj) {
}
static void deregisterRequest(SRequestObj *pRequest) {
const static int64_t SLOW_QUERY_INTERVAL = 3000000L; // todo configurable
if (pRequest == NULL) {
tscError("pRequest == NULL");
return;
@ -80,6 +79,7 @@ static void deregisterRequest(SRequestObj *pRequest) {
int32_t currentInst = atomic_sub_fetch_64((int64_t *)&pActivity->currentRequests, 1);
int32_t num = atomic_sub_fetch_32(&pTscObj->numOfReqs, 1);
int32_t reqType = SLOW_LOG_TYPE_OTHERS;
int64_t duration = taosGetTimestampUs() - pRequest->metric.start;
tscDebug("0x%" PRIx64 " free Request from connObj: 0x%" PRIx64 ", reqId:0x%" PRIx64
@ -95,6 +95,7 @@ static void deregisterRequest(SRequestObj *pRequest) {
duration, pRequest->metric.parseCostUs, pRequest->metric.ctgCostUs, pRequest->metric.analyseCostUs,
pRequest->metric.planCostUs, pRequest->metric.execCostUs);
atomic_add_fetch_64((int64_t *)&pActivity->insertElapsedTime, duration);
reqType = SLOW_LOG_TYPE_INSERT;
} else if (QUERY_NODE_SELECT_STMT == pRequest->stmtType) {
tscDebug("query duration %" PRId64 "us: parseCost:%" PRId64 "us, ctgCost:%" PRId64 "us, analyseCost:%" PRId64
"us, planCost:%" PRId64 "us, exec:%" PRId64 "us",
@ -102,12 +103,16 @@ static void deregisterRequest(SRequestObj *pRequest) {
pRequest->metric.planCostUs, pRequest->metric.execCostUs);
atomic_add_fetch_64((int64_t *)&pActivity->queryElapsedTime, duration);
reqType = SLOW_LOG_TYPE_QUERY;
}
}
if (duration >= SLOW_QUERY_INTERVAL) {
if (duration >= (tsSlowLogThreshold * 1000000UL)) {
atomic_add_fetch_64((int64_t *)&pActivity->numOfSlowQueries, 1);
tscWarnL("slow query: %s, duration:%" PRId64, pRequest->sqlstr, duration);
if (tsSlowLogScope & reqType) {
taosPrintSlowLog("PID:%d, Conn:%u, QID:0x%" PRIx64 ", Start:%" PRId64 ", Duration:%" PRId64 "us, SQL:%s",
taosGetPId(), pTscObj->connId, pRequest->requestId, pRequest->metric.start, duration, pRequest->sqlstr);
}
}
releaseTscObj(pTscObj->id);
@ -239,7 +244,7 @@ void destroyTscObj(void *pObj) {
tscTrace("begin to destroy tscObj %" PRIx64 " p:%p", tscId, pTscObj);
SClientHbKey connKey = {.tscRid = pTscObj->id, .connType = pTscObj->connType};
hbDeregisterConn(pTscObj->pAppInfo->pAppHbMgr, connKey);
hbDeregisterConn(pTscObj, connKey);
destroyAllRequests(pTscObj->pRequests);
taosHashCleanup(pTscObj->pRequests);
@ -427,8 +432,12 @@ static void *tscCrashReportThreadFp(void *param) {
}
#endif
if (-1 != atomic_val_compare_exchange_32(&clientStop, -1, 0)) {
return NULL;
}
while (1) {
if (clientStop) break;
if (clientStop > 0) break;
if (loopTimes++ < reportPeriodNum) {
taosMsleep(sleepTime);
continue;
@ -466,7 +475,7 @@ static void *tscCrashReportThreadFp(void *param) {
loopTimes = 0;
}
clientStop = -1;
clientStop = -2;
return NULL;
}

191
source/client/src/clientHb.c
View File

@ -19,6 +19,15 @@
#include "scheduler.h"
#include "trpc.h"
typedef struct {
union {
struct {
int64_t clusterId;
int32_t passKeyCnt;
};
};
} SHbParam;
static SClientHbMgr clientHbMgr = {0};
static int32_t hbCreateThread();
@ -49,14 +58,60 @@ static int32_t hbProcessUserAuthInfoRsp(void *value, int32_t valueLen, struct SC
return TSDB_CODE_SUCCESS;
}
static int32_t hbProcessUserPassInfoRsp(void *value, int32_t valueLen, SClientHbKey *connKey, SAppHbMgr *pAppHbMgr) {
int32_t code = 0;
int32_t numOfBatchs = 0;
SUserPassBatchRsp batchRsp = {0};
if (tDeserializeSUserPassBatchRsp(value, valueLen, &batchRsp) != 0) {
code = TSDB_CODE_INVALID_MSG;
return code;
}
numOfBatchs = taosArrayGetSize(batchRsp.pArray);
SClientHbReq *pReq = NULL;
while ((pReq = taosHashIterate(pAppHbMgr->activeInfo, pReq))) {
STscObj *pTscObj = (STscObj *)acquireTscObj(pReq->connKey.tscRid);
if (!pTscObj) {
continue;
}
SPassInfo *passInfo = &pTscObj->passInfo;
if (!passInfo->fp) {
releaseTscObj(pReq->connKey.tscRid);
continue;
}
for (int32_t i = 0; i < numOfBatchs; ++i) {
SGetUserPassRsp *rsp = taosArrayGet(batchRsp.pArray, i);
if (0 == strncmp(rsp->user, pTscObj->user, TSDB_USER_LEN)) {
int32_t oldVer = atomic_load_32(&passInfo->ver);
if (oldVer < rsp->version) {
atomic_store_32(&passInfo->ver, rsp->version);
if (passInfo->fp) {
(*passInfo->fp)(passInfo->param, &passInfo->ver, TAOS_NOTIFY_PASSVER);
}
tscDebug("update passVer of user %s from %d to %d, tscRid:%" PRIi64, rsp->user, oldVer,
atomic_load_32(&passInfo->ver), pTscObj->id);
}
break;
}
}
releaseTscObj(pReq->connKey.tscRid);
}
taosArrayDestroy(batchRsp.pArray);
return code;
}
static int32_t hbGenerateVgInfoFromRsp(SDBVgInfo **pInfo, SUseDbRsp *rsp) {
int32_t code = 0;
int32_t code = 0;
SDBVgInfo *vgInfo = taosMemoryCalloc(1, sizeof(SDBVgInfo));
if (NULL == vgInfo) {
code = TSDB_CODE_OUT_OF_MEMORY;
return code;
}
vgInfo->vgVersion = rsp->vgVersion;
vgInfo->stateTs = rsp->stateTs;
vgInfo->hashMethod = rsp->hashMethod;
@ -69,7 +124,7 @@ static int32_t hbGenerateVgInfoFromRsp(SDBVgInfo **pInfo, SUseDbRsp *rsp) {
code = TSDB_CODE_OUT_OF_MEMORY;
goto _return;
}
for (int32_t j = 0; j < rsp->vgNum; ++j) {
SVgroupInfo *pInfo = taosArrayGet(rsp->pVgroupInfos, j);
if (taosHashPut(vgInfo->vgHash, &pInfo->vgId, sizeof(int32_t), pInfo, sizeof(SVgroupInfo)) != 0) {
@ -123,7 +178,8 @@ static int32_t hbProcessDBInfoRsp(void *value, int32_t valueLen, struct SCatalog
goto _return;
}
catalogUpdateDBVgInfo(pCatalog, (rsp->db[0] == 'i') ? TSDB_PERFORMANCE_SCHEMA_DB : TSDB_INFORMATION_SCHEMA_DB, rsp->uid, vgInfo);
catalogUpdateDBVgInfo(pCatalog, (rsp->db[0] == 'i') ? TSDB_PERFORMANCE_SCHEMA_DB : TSDB_INFORMATION_SCHEMA_DB,
rsp->uid, vgInfo);
}
}
@ -291,6 +347,15 @@ static int32_t hbQueryHbRspHandle(SAppHbMgr *pAppHbMgr, SClientHbRsp *pRsp) {
hbProcessStbInfoRsp(kv->value, kv->valueLen, pCatalog);
break;
}
case HEARTBEAT_KEY_USER_PASSINFO: {
if (kv->valueLen <= 0 || NULL == kv->value) {
tscError("invalid hb user pass info, len:%d, value:%p", kv->valueLen, kv->value);
break;
}
hbProcessUserPassInfoRsp(kv->value, kv->valueLen, &pRsp->connKey, pAppHbMgr);
break;
}
default:
tscError("invalid hb key type:%d", kv->key);
break;
@ -308,7 +373,7 @@ static int32_t hbAsyncCallBack(void *param, SDataBuf *pMsg, int32_t code) {
}
static int32_t emptyRspNum = 0;
int32_t idx = *(int32_t *)param;
int32_t idx = *(int32_t *)param;
SClientHbBatchRsp pRsp = {0};
if (TSDB_CODE_SUCCESS == code) {
tDeserializeSClientHbBatchRsp(pMsg->pData, pMsg->len, &pRsp);
@ -339,8 +404,7 @@ static int32_t hbAsyncCallBack(void *param, SDataBuf *pMsg, int32_t code) {
if (code != 0) {
pInst->onlineDnodes = pInst->totalDnodes ? 0 : -1;
tscDebug("hb rsp error %s, update server status %d/%d", tstrerror(code), pInst->onlineDnodes,
pInst->totalDnodes);
tscDebug("hb rsp error %s, update server status %d/%d", tstrerror(code), pInst->onlineDnodes, pInst->totalDnodes);
}
if (rspNum) {
@ -472,6 +536,49 @@ int32_t hbGetQueryBasicInfo(SClientHbKey *connKey, SClientHbReq *req) {
return TSDB_CODE_SUCCESS;
}
static int32_t hbGetUserBasicInfo(SClientHbKey *connKey, SClientHbReq *req) {
STscObj *pTscObj = (STscObj *)acquireTscObj(connKey->tscRid);
if (!pTscObj) {
tscWarn("tscObj rid %" PRIx64 " not exist", connKey->tscRid);
return TSDB_CODE_APP_ERROR;
}
int32_t code = 0;
SUserPassVersion *user = taosMemoryMalloc(sizeof(SUserPassVersion));
if (!user) {
code = TSDB_CODE_OUT_OF_MEMORY;
goto _return;
}
strncpy(user->user, pTscObj->user, TSDB_USER_LEN);
user->version = htonl(pTscObj->passInfo.ver);
SKv kv = {
.key = HEARTBEAT_KEY_USER_PASSINFO,
.valueLen = sizeof(SUserPassVersion),
.value = user,
};
tscDebug("hb got user basic info, valueLen:%d, user:%s, passVer:%d, tscRid:%" PRIi64, kv.valueLen, user->user,
pTscObj->passInfo.ver, connKey->tscRid);
if (!req->info) {
req->info = taosHashInit(64, hbKeyHashFunc, 1, HASH_ENTRY_LOCK);
}
if (taosHashPut(req->info, &kv.key, sizeof(kv.key), &kv, sizeof(kv)) < 0) {
code = terrno ? terrno : TSDB_CODE_APP_ERROR;
goto _return;
}
_return:
releaseTscObj(connKey->tscRid);
if (code) {
tscError("hb got user basic info failed since %s", terrstr(code));
}
return code;
}
int32_t hbGetExpiredUserInfo(SClientHbKey *connKey, struct SCatalog *pCatalog, SClientHbReq *req) {
SUserAuthVersion *users = NULL;
uint32_t userNum = 0;
@ -526,8 +633,8 @@ int32_t hbGetExpiredDBInfo(SClientHbKey *connKey, struct SCatalog *pCatalog, SCl
for (int32_t i = 0; i < dbNum; ++i) {
SDbVgVersion *db = &dbs[i];
tscDebug("the %dth expired dbFName:%s, dbId:%" PRId64 ", vgVersion:%d, numOfTable:%d, startTs:%" PRId64,
i, db->dbFName, db->dbId, db->vgVersion, db->numOfTable, db->stateTs);
tscDebug("the %dth expired dbFName:%s, dbId:%" PRId64 ", vgVersion:%d, numOfTable:%d, startTs:%" PRId64, i,
db->dbFName, db->dbId, db->vgVersion, db->numOfTable, db->stateTs);
db->dbId = htobe64(db->dbId);
db->vgVersion = htonl(db->vgVersion);
@ -607,19 +714,23 @@ int32_t hbGetAppInfo(int64_t clusterId, SClientHbReq *req) {
}
int32_t hbQueryHbReqHandle(SClientHbKey *connKey, void *param, SClientHbReq *req) {
int64_t *clusterId = (int64_t *)param;
SHbParam *hbParam = (SHbParam *)param;
struct SCatalog *pCatalog = NULL;
int32_t code = catalogGetHandle(*clusterId, &pCatalog);
int32_t code = catalogGetHandle(hbParam->clusterId, &pCatalog);
if (code != TSDB_CODE_SUCCESS) {
tscWarn("catalogGetHandle failed, clusterId:%" PRIx64 ", error:%s", *clusterId, tstrerror(code));
tscWarn("catalogGetHandle failed, clusterId:%" PRIx64 ", error:%s", hbParam->clusterId, tstrerror(code));
return code;
}
hbGetAppInfo(*clusterId, req);
hbGetAppInfo(hbParam->clusterId, req);
hbGetQueryBasicInfo(connKey, req);
if (hbParam->passKeyCnt > 0) {
hbGetUserBasicInfo(connKey, req);
}
code = hbGetExpiredUserInfo(connKey, pCatalog, req);
if (TSDB_CODE_SUCCESS != code) {
return code;
@ -673,7 +784,26 @@ SClientHbBatchReq *hbGatherAllInfo(SAppHbMgr *pAppHbMgr) {
while (pIter != NULL) {
pOneReq = taosArrayPush(pBatchReq->reqs, pOneReq);
code = (*clientHbMgr.reqHandle[pOneReq->connKey.connType])(&pOneReq->connKey, &pOneReq->clusterId, pOneReq);
SHbParam param;
switch (pOneReq->connKey.connType) {
case CONN_TYPE__QUERY: {
param.clusterId = pOneReq->clusterId;
param.passKeyCnt = atomic_load_32(&pAppHbMgr->passKeyCnt);
break;
}
default:
break;
}
if (clientHbMgr.reqHandle[pOneReq->connKey.connType]) {
code = (*clientHbMgr.reqHandle[pOneReq->connKey.connType])(&pOneReq->connKey, &param, pOneReq);
if (code) {
tscWarn("hbGatherAllInfo failed since %s, tscRid:%" PRIi64 ", connType:%" PRIi8, tstrerror(code),
pOneReq->connKey.tscRid, pOneReq->connKey.connType);
}
}
break;
#if 0
if (code) {
pIter = taosHashIterate(pAppHbMgr->activeInfo, pIter);
pOneReq = pIter;
@ -682,6 +812,7 @@ SClientHbBatchReq *hbGatherAllInfo(SAppHbMgr *pAppHbMgr) {
pIter = taosHashIterate(pAppHbMgr->activeInfo, pIter);
pOneReq = pIter;
#endif
}
releaseTscObj(rid);
@ -856,7 +987,7 @@ static void hbStopThread() {
}
SAppHbMgr *appHbMgrInit(SAppInstInfo *pAppInstInfo, char *key) {
if(hbMgrInit() != 0){
if (hbMgrInit() != 0) {
terrno = TSDB_CODE_TSC_INTERNAL_ERROR;
return NULL;
}
@ -868,6 +999,7 @@ SAppHbMgr *appHbMgrInit(SAppInstInfo *pAppInstInfo, char *key) {
// init stat
pAppHbMgr->startTime = taosGetTimestampMs();
pAppHbMgr->connKeyCnt = 0;
pAppHbMgr->passKeyCnt = 0;
pAppHbMgr->reportCnt = 0;
pAppHbMgr->reportBytes = 0;
pAppHbMgr->key = taosStrdup(key);
@ -946,27 +1078,23 @@ int hbMgrInit() {
TdThreadMutexAttr attr = {0};
int ret = taosThreadMutexAttrInit(&attr);
if(ret != 0){
uError("hbMgrInit:taosThreadMutexAttrInit error")
return ret;
if (ret != 0) {
uError("hbMgrInit:taosThreadMutexAttrInit error") return ret;
}
ret = taosThreadMutexAttrSetType(&attr, PTHREAD_MUTEX_RECURSIVE);
if(ret != 0){
uError("hbMgrInit:taosThreadMutexAttrSetType error")
return ret;
if (ret != 0) {
uError("hbMgrInit:taosThreadMutexAttrSetType error") return ret;
}
ret = taosThreadMutexInit(&clientHbMgr.lock, &attr);
if(ret != 0){
uError("hbMgrInit:taosThreadMutexInit error")
return ret;
if (ret != 0) {
uError("hbMgrInit:taosThreadMutexInit error") return ret;
}
ret = taosThreadMutexAttrDestroy(&attr);
if(ret != 0){
uError("hbMgrInit:taosThreadMutexAttrDestroy error")
return ret;
if (ret != 0) {
uError("hbMgrInit:taosThreadMutexAttrDestroy error") return ret;
}
// init handle funcs
@ -1028,7 +1156,8 @@ int hbRegisterConn(SAppHbMgr *pAppHbMgr, int64_t tscRefId, int64_t clusterId, in
}
}
void hbDeregisterConn(SAppHbMgr *pAppHbMgr, SClientHbKey connKey) {
void hbDeregisterConn(STscObj *pTscObj, SClientHbKey connKey) {
SAppHbMgr *pAppHbMgr = pTscObj->pAppInfo->pAppHbMgr;
SClientHbReq *pReq = taosHashAcquire(pAppHbMgr->activeInfo, &connKey, sizeof(SClientHbKey));
if (pReq) {
tFreeClientHbReq(pReq);
@ -1041,6 +1170,12 @@ void hbDeregisterConn(SAppHbMgr *pAppHbMgr, SClientHbKey connKey) {
}
atomic_sub_fetch_32(&pAppHbMgr->connKeyCnt, 1);
taosThreadMutexLock(&pTscObj->mutex);
if (pTscObj->passInfo.fp) {
atomic_sub_fetch_32(&pAppHbMgr->passKeyCnt, 1);
}
taosThreadMutexUnlock(&pTscObj->mutex);
}
// set heart beat thread quit mode , if quicByKill 1 then kill thread else quit from inner

7
source/client/src/clientImpl.c
View File

@ -1248,6 +1248,11 @@ STscObj* taosConnectImpl(const char* user, const char* auth, const char* db, __t
return NULL;
}
pRequest->sqlstr = taosStrdup("taos_connect");
if (pRequest->sqlstr) {
pRequest->sqlLen = strlen(pRequest->sqlstr);
}
SMsgSendInfo* body = buildConnectMsg(pRequest);
int64_t transporterId = 0;
@ -1257,7 +1262,7 @@ STscObj* taosConnectImpl(const char* user, const char* auth, const char* db, __t
if (pRequest->code != TSDB_CODE_SUCCESS) {
const char* errorMsg =
(pRequest->code == TSDB_CODE_RPC_FQDN_ERROR) ? taos_errstr(pRequest) : tstrerror(pRequest->code);
fprintf(stderr, "failed to connect to server, reason: %s\n\n", errorMsg);
tscError("failed to connect to server, reason: %s", errorMsg);
terrno = pRequest->code;
destroyRequest(pRequest);

41
source/client/src/clientMain.c
View File

@ -119,6 +119,43 @@ TAOS *taos_connect(const char *ip, const char *user, const char *pass, const cha
return NULL;
}
int taos_set_notify_cb(TAOS *taos, __taos_notify_fn_t fp, void *param, int type) {
if (taos == NULL) {
terrno = TSDB_CODE_INVALID_PARA;
return terrno;
}
STscObj *pObj = acquireTscObj(*(int64_t *)taos);
if (NULL == pObj) {
terrno = TSDB_CODE_TSC_DISCONNECTED;
tscError("invalid parameter for %s", __func__);
return terrno;
}
switch (type) {
case TAOS_NOTIFY_PASSVER: {
taosThreadMutexLock(&pObj->mutex);
if (fp && !pObj->passInfo.fp) {
atomic_add_fetch_32(&pObj->pAppInfo->pAppHbMgr->passKeyCnt, 1);
} else if (!fp && pObj->passInfo.fp) {
atomic_sub_fetch_32(&pObj->pAppInfo->pAppHbMgr->passKeyCnt, 1);
}
pObj->passInfo.fp = fp;
pObj->passInfo.param = param;
taosThreadMutexUnlock(&pObj->mutex);
break;
}
default: {
terrno = TSDB_CODE_INVALID_PARA;
releaseTscObj(*(int64_t *)taos);
return terrno;
}
}
releaseTscObj(*(int64_t *)taos);
return 0;
}
void taos_close_internal(void *taos) {
if (taos == NULL) {
return;
@ -1307,6 +1344,8 @@ int taos_load_table_info(TAOS *taos, const char *tableNameList) {
goto _return;
}
pRequest->syncQuery = true;
STscObj *pTscObj = pRequest->pTscObj;
code = transferTableNameList(tableNameList, pTscObj->acctId, pTscObj->db, &catalogReq.pTableMeta);
if (code) {
@ -1333,7 +1372,7 @@ int taos_load_table_info(TAOS *taos, const char *tableNameList) {
tsem_wait(&pParam->sem);
_return:
taosArrayDestroy(catalogReq.pTableMeta);
taosArrayDestroyEx(catalogReq.pTableMeta, destoryTablesReq);
destroyRequest(pRequest);
return code;
}

1
source/client/src/clientMsgHandler.c
View File

@ -129,6 +129,7 @@ int32_t processConnectRsp(void* param, SDataBuf* pMsg, int32_t code) {
lastClusterId = connectRsp.clusterId;
pTscObj->connType = connectRsp.connType;
pTscObj->passInfo.ver = connectRsp.passVer;
hbRegisterConn(pTscObj->pAppInfo->pAppHbMgr, pTscObj->id, connectRsp.clusterId, connectRsp.connType);

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

@ -1511,7 +1511,7 @@ static int32_t tmqWriteRawDataImpl(TAOS* taos, void* data, int32_t dataLen) {
rspObj.resType = RES_TYPE__TMQ;
tDecoderInit(&decoder, data, dataLen);
code = tDecodeSMqDataRsp(&decoder, &rspObj.rsp);
code = tDecodeMqDataRsp(&decoder, &rspObj.rsp);
if (code != 0) {
uError("WriteRaw:decode smqDataRsp error");
code = TSDB_CODE_INVALID_MSG;
@ -1615,7 +1615,7 @@ static int32_t tmqWriteRawDataImpl(TAOS* taos, void* data, int32_t dataLen) {
code = pRequest->code;
end:
tDeleteSMqDataRsp(&rspObj.rsp);
tDeleteMqDataRsp(&rspObj.rsp);
tDecoderClear(&decoder);
qDestroyQuery(pQuery);
destroyRequest(pRequest);
@ -1858,7 +1858,7 @@ int32_t tmq_get_raw(TAOS_RES* res, tmq_raw_data* raw) {
int32_t len = 0;
int32_t code = 0;
tEncodeSize(tEncodeSMqDataRsp, &rspObj->rsp, len, code);
tEncodeSize(tEncodeMqDataRsp, &rspObj->rsp, len, code);
if (code < 0) {
return -1;
}
@ -1866,7 +1866,7 @@ int32_t tmq_get_raw(TAOS_RES* res, tmq_raw_data* raw) {
void* buf = taosMemoryCalloc(1, len);
SEncoder encoder = {0};
tEncoderInit(&encoder, buf, len);
tEncodeSMqDataRsp(&encoder, &rspObj->rsp);
tEncodeMqDataRsp(&encoder, &rspObj->rsp);
tEncoderClear(&encoder);
raw->raw = buf;

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