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2
docs-cn/10-cluster/01-deploy.md
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@ -22,7 +22,7 @@ title: 集群部署
### 第二步
建议关闭所有物理节点的防火墙，至少保证端口：6030 - 6042 的 TCP 和 UDP 端口都是开放的。强烈建议先关闭防火墙，集群搭建完毕之后，再来配置端口；
确保集群中所有主机在端口 6030-6042 上的 TCP/UDP 协议能够互通。
### 第三步

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docs-cn/14-reference/12-config/index.md
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@ -80,7 +80,7 @@ taos --dump-config
| 补充说明 | RESTful 服务在 2.4.0.0 之前（不含）由 taosd 提供，默认端口为 6041; 在 2.4.0.0 及后续版本由 taosAdapter，默认端口为 6041 |
:::note
对于端口，TDengine 会使用从 serverPort 起 13 个连续的 TCP 和 UDP 端口号，请务必在防火墙打开。因此如果是缺省配置，需要打开从 6030 到 6042 共 13 个端口，而且必须 TCP 和 UDP 都打开。（详细的端口情况请参见下表）
确保集群中所有主机在端口 6030-6042 上的 TCP/UDP 协议能够互通。（详细的端口情况请参见下表）
:::
| 协议 | 默认端口 | 用途说明 | 修改方法 |
| :--- | :-------- | :---------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------- |
@ -590,7 +590,7 @@ charset 的有效值是 UTF-8。
| 适用范围 | 仅服务端适用 |
| 含义 | 每个 DB 中 能够使用的最大 vnode 个数 |
| 取值范围 | 0-8192 |
| 缺省值 | |
| 缺省值 | 0 |
### maxTablesPerVnode

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docs-cn/21-tdinternal/01-arch.md
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@ -41,7 +41,7 @@ TDengine 分布式架构的逻辑结构图如下：
- 集群数据节点对外提供 RESTful 服务占用一个 TCP 端口，是 serverPort+11。
- 集群内数据节点与 Arbitrator 节点之间通讯占用一个 TCP 端口，是 serverPort+12。
因此一个数据节点总的端口范围为 serverPort 到 serverPort+12，总共 13 个 TCP/UDP 端口。使用时，需要确保防火墙将这些端口打开。每个数据节点可以配置不同的 serverPort。详细的端口情况请参见 [TDengine 2.0 端口说明](/train-faq/faq#port)
因此一个数据节点总的端口范围为 serverPort 到 serverPort+12，总共 13 个 TCP/UDP 端口。确保集群中所有主机在端口 6030-6042 上的 TCP/UDP 协议能够互通。详细的端口情况请参见 [TDengine 2.0 端口说明](/train-faq/faq#port)
**集群对外连接：**TDengine 集群可以容纳单个、多个甚至几千个数据节点。应用只需要向集群中任何一个数据节点发起连接即可，连接需要提供的网络参数是一数据节点的 End Point（FQDN 加配置的端口号）。通过命令行 CLI 启动应用 taos 时，可以通过选项-h 来指定数据节点的 FQDN，-P 来指定其配置的端口号，如果端口不配置，将采用 TDengine 的系统配置参数 serverPort。

2
docs-cn/27-train-faq/01-faq.md
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@ -61,7 +61,7 @@ title: 常见问题及反馈
5. ping 服务器 FQDN，如果没有反应，请检查你的网络，DNS 设置，或客户端所在计算机的系统 hosts 文件。如果部署的是 TDengine 集群，客户端需要能 ping 通所有集群节点的 FQDN。
6. 检查防火墙设置（Ubuntu 使用 ufw status，CentOS 使用 firewall-cmd --list-port），确认 TCP/UDP 端口 6030-6042 是打开的
6. 检查防火墙设置（Ubuntu 使用 ufw status，CentOS 使用 firewall-cmd --list-port），确保集群中所有主机在端口 6030-6042 上的 TCP/UDP 协议能够互通。
7. 对于 Linux 上的 JDBC（ODBC, Python, Go 等接口类似）连接, 确保*libtaos.so*在目录*/usr/local/taos/driver*里, 并且*/usr/local/taos/driver*在系统库函数搜索路径*LD_LIBRARY_PATH*里

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docs-en/07-develop/02-model/index.mdx
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@ -2,19 +2,26 @@
title: Data Model
---
The data model employed by TDengine is similar to a relational database, you need to create databases and tables. Design the data model based on your own application scenarios and you should design the STable (abbreviation for super table) schema to fit your data. This chapter will explain the big picture without getting into syntax details.
The data model employed by TDengine is similar to that of a relational database. You have to create databases and tables. You must design the data model based on your own business and application requirements. You should design the STable (an abbreviation for super table) schema to fit your data. This chapter will explain the big picture without getting into syntactical details.
## Create Database
The characteristics of data from different data collection points may be different, such as collection frequency, days to keep, number of replicas, data block size, whether it's allowed to update data, etc. For TDengine to operate with the best performance, it's strongly suggested to put the data with different characteristics into different databases because different storage policies can be set for each database. When creating a database, there are a lot of parameters that can be configured, such as the days to keep data, the number of replicas, the number of memory blocks, time precision, the minimum and maximum number of rows in each data block, compress or not, the time range of the data in single data file, etc. Below is an example of the SQL statement for creating a database.
The [characteristics of time-series data](https://www.taosdata.com/blog/2019/07/09/86.html) from different data collection points may be different. Characteristics include collection frequency, retention policy and others which determine how you create and configure the database. For e.g. days to keep, number of replicas, data block size, whether data updates are allowed and other configurable parameters would be determined by the characteristics of your data and your business requirements. For TDengine to operate with the best performance, we strongly recommend that you create and configure different databases for data with different characteristics. This allows you, for example, to set up different storage and retention policies. When creating a database, there are a lot of parameters that can be configured such as, the days to keep data, the number of replicas, the number of memory blocks, time precision, the minimum and maximum number of rows in each data block, whether compression is enabled, the time range of the data in single data file and so on. Below is an example of the SQL statement to create a database.
```sql
CREATE DATABASE power KEEP 365 DAYS 10 BLOCKS 6 UPDATE 1;
```
In the above SQL statement, a database named "power" will be created, the data in it will be kept for 365 days, which means the data older than 365 days will be deleted automatically, a new data file will be created every 10 days, the number of memory blocks is 6, data is allowed to be updated. For more details please refer to [Database](/taos-sql/database).
In the above SQL statement:
- a database named "power" will be created
- the data in it will be kept for 365 days, which means that data older than 365 days will be deleted automatically
- a new data file will be created every 10 days
- the number of memory blocks is 6
- data is allowed to be updated
After creating a database, the current database in use can be switched using SQL command `USE`, for example below SQL statement switches the current database to `power`. Without the current database specified, table name must be preceded with the corresponding database name.
For more details please refer to [Database](/taos-sql/database).
After creating a database, the current database in use can be switched using SQL command `USE`. For example the SQL statement below switches the current database to `power`. Without the current database specified, table name must be preceded with the corresponding database name.
```sql
USE power;
@ -30,7 +37,7 @@ USE power;
## Create STable
In a time-series application, there may be multiple kinds of data collection points. For example, in the electrical power system there are meters, transformers, bus bars, switches, etc. For easy and efficient aggregation of multiple tables, one STable needs to be created for each kind of data collection point. For example, for the meters in [table 1](/tdinternal/arch#model_table1), the below SQL statement can be used to create the super table.
In a time-series application, there may be multiple kinds of data collection points. For example, in the electrical power system there are meters, transformers, bus bars, switches, etc. For easy and efficient aggregation of multiple tables, one STable needs to be created for each kind of data collection point. For example, for the meters in [table 1](/tdinternal/arch#model_table1), the SQL statement below can be used to create the super table.
```sql
CREATE STable meters (ts timestamp, current float, voltage int, phase float) TAGS (location binary(64), groupId int);
@ -41,15 +48,15 @@ If you are using versions prior to 2.0.15, the `STable` keyword needs to be repl
:::
Similar to creating a regular table, when creating a STable, the name and schema need to be provided. In the STable schema, the first column must be timestamp (like ts in the example), and the other columns (like current, voltage and phase in the example) are the data collected. The column type can be integer, float, double, string ,etc. Besides, the schema for tags need to be provided, like location and groupId in the example. The tag type can be integer, float, string, etc. The static properties of a data collection point can be defined as tags, like the location, device type, device group ID, manager ID, etc. Tags in the schema can be added, removed or updated. Please refer to [STable](/taos-sql/stable) for more details.
Similar to creating a regular table, when creating a STable, the name and schema need to be provided. In the STable schema, the first column must always be a timestamp (like ts in the example), and the other columns (like current, voltage and phase in the example) are the data collected. The remaining columns can [contain data of type](/taos-sql/data-type/) integer, float, double, string etc. In addition, the schema for tags, like location and groupId in the example, must be provided. The tag type can be integer, float, string, etc. Tags are essentially the static properties of a data collection point. For example, properties like the location, device type, device group ID, manager ID are tags. Tags in the schema can be added, removed or updated. Please refer to [STable](/taos-sql/stable) for more details.
For each kind of data collection point, a corresponding STable must be created. There may be many STables in an application. For electrical power system, we need to create a STable respectively for meters, transformers, busbars, switches. There may be multiple kinds of data collection points on a single device, for example there may be one data collection point for electrical data like current and voltage and another point for environmental data like temperature, humidity and wind direction, multiple STables are required for such kind of device.
For each kind of data collection point, a corresponding STable must be created. There may be many STables in an application. For electrical power system, we need to create a STable respectively for meters, transformers, busbars, switches. There may be multiple kinds of data collection points on a single device, for example there may be one data collection point for electrical data like current and voltage and another data collection point for environmental data like temperature, humidity and wind direction. Multiple STables are required for these kinds of devices.
At most 4096 (or 1024 prior to version 2.1.7.0) columns are allowed in a STable. If there are more than 4096 of metrics to be collected for a data collection point, multiple STables are required. There can be multiple databases in a system, while one or more STables can exist in a database.
## Create Table
A specific table needs to be created for each data collection point. Similar to RDBMS, table name and schema are required to create a table. Beside, one or more tags can be created for each table. To create a table, a STable needs to be used as template and the values need to be specified for the tags. For example, for the meters in [Table 1](/tdinternal/arch#model_table1), the table can be created using below SQL statement.
A specific table needs to be created for each data collection point. Similar to RDBMS, table name and schema are required to create a table. Additionally, one or more tags can be created for each table. To create a table, a STable needs to be used as template and the values need to be specified for the tags. For example, for the meters in [Table 1](/tdinternal/arch#model_table1), the table can be created using below SQL statement.
```sql
CREATE TABLE d1001 USING meters TAGS ("California.SanFrancisco", 2);
@ -57,17 +64,17 @@ CREATE TABLE d1001 USING meters TAGS ("California.SanFrancisco", 2);
In the above SQL statement, "d1001" is the table name, "meters" is the STable name, followed by the value of tag "Location" and the value of tag "groupId", which are "California.SanFrancisco" and "2" respectively in the example. The tag values can be updated after the table is created. Please refer to [Tables](/taos-sql/table) for details.
In TDengine system, it's recommended to create a table for a data collection point via STable. A table created via STable is called subtable in some parts of the TDengine documentation. All SQL commands applied on regular tables can be applied on subtables.
In the TDengine system, it's recommended to create a table for a data collection point via STable. A table created via STable is called subtable in some parts of the TDengine documentation. All SQL commands applied on regular tables can be applied on subtables.
:::warning
It's not recommended to create a table in a database while using a STable from another database as template.
:::tip
It's suggested to use the global unique ID of a data collection point as the table name, for example the device serial number. If there isn't such a unique ID, multiple IDs that are not global unique can be combined to form a global unique ID. It's not recommended to use a global unique ID as tag value.
It's suggested to use the globally unique ID of a data collection point as the table name. For example the device serial number could be used as a unique ID. If a unique ID doesn't exist, multiple IDs that are not globally unique can be combined to form a globally unique ID. It's not recommended to use a globally unique ID as tag value.
## Create Table Automatically
In some circumstances, it's unknown whether the table already exists when inserting rows. The table can be created automatically using the SQL statement below, and nothing will happen if the table already exist.
In some circumstances, it's unknown whether the table already exists when inserting rows. The table can be created automatically using the SQL statement below, and nothing will happen if the table already exists.
```sql
INSERT INTO d1001 USING meters TAGS ("California.SanFrancisco", 2) VALUES (now, 10.2, 219, 0.32);
@ -79,6 +86,8 @@ For more details please refer to [Create Table Automatically](/taos-sql/insert#a
## Single Column vs Multiple Column
A multiple columns data model is supported in TDengine. As long as multiple metrics are collected by the same data collection point at the same time, i.e. the timestamp are identical, these metrics can be put in a single STable as columns. However, there is another kind of design, i.e. single column data model, a table is created for each metric, which means a STable is required for each kind of metric. For example, 3 STables are required for current, voltage and phase.
A multiple columns data model is supported in TDengine. As long as multiple metrics are collected by the same data collection point at the same time, i.e. the timestamps are identical, these metrics can be put in a single STable as columns.
It's recommended to use a multiple column data model as much as possible because it's better in the performance of inserting or querying rows. In some cases, however, the metrics to be collected vary frequently and correspondingly the STable schema needs to be changed frequently too. In such case, it's more convenient to use single column data model.
However, there is another kind of design, i.e. single column data model in which a table is created for each metric. This means that a STable is required for each kind of metric. For example in a single column model, 3 STables would be required for current, voltage and phase.
It's recommended to use a multiple column data model as much as possible because insert and query performance is higher. In some cases, however, the collected metrics may vary frequently and so the corresponding STable schema needs to be changed frequently too. In such cases, it's more convenient to use single column data model.

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docs-en/07-develop/03-insert-data/02-influxdb-line.mdx
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@ -15,13 +15,13 @@ import CLine from "./_c_line.mdx";
## Introduction
A single line of text is used in InfluxDB Line protocol format represents one row of data, each line contains 4 parts as shown below.
In the InfluxDB Line protocol format, a single line of text is used to represent one row of data. Each line contains 4 parts as shown below.
```
measurement,tag_set field_set timestamp
```
- `measurement` will be used as the STable name
- `measurement` will be used as the name of the STable
- `tag_set` will be used as tags, with format like `<tag_key>=<tag_value>,<tag_key>=<tag_value>`
- `field_set`will be used as data columns, with format like `<field_key>=<field_value>,<field_key>=<field_value>`
- `timestamp` is the primary key timestamp corresponding to this row of data
@ -34,8 +34,8 @@ meters,location=California.LoSangeles,groupid=2 current=13.4,voltage=223,phase=0
:::note
- All the data in `tag_set` will be converted to ncahr type automatically .
- Each data in `field_set` must be self-description for its data type. For example 1.2f32 means a value 1.2 of float type, it will be treated as double without the "f" type suffix.
- All the data in `tag_set` will be converted to nchar type automatically .
- Each data in `field_set` must be self-descriptive for its data type. For example 1.2f32 means a value 1.2 of float type. Without the "f" type suffix, it will be treated as type double.
- Multiple kinds of precision can be used for the `timestamp` field. Time precision can be from nanosecond (ns) to hour (h).
:::

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docs-en/07-develop/03-insert-data/03-opentsdb-telnet.mdx
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@ -15,7 +15,7 @@ import CTelnet from "./_c_opts_telnet.mdx";
## Introduction
A single line of text is used in OpenTSDB line protocol to represent one row of data. OpenTSDB employs single column data model, so one line can only contain a single data column. There can be multiple tags. Each line contains 4 parts as below:
A single line of text is used in OpenTSDB line protocol to represent one row of data. OpenTSDB employs a single column data model, so each line can only contain a single data column. There can be multiple tags. Each line contains 4 parts as below:
```
<metric> <timestamp> <value> <tagk_1>=<tagv_1>[ <tagk_n>=<tagv_n>]
@ -60,7 +60,7 @@ Please refer to [OpenTSDB Telnet API](http://opentsdb.net/docs/build/html/api_te
</TabItem>
</Tabs>
2 STables will be crated automatically while each STable has 4 rows of data in the above sample code.
2 STables will be created automatically and each STable has 4 rows of data in the above sample code.
```cmd
taos> use test;

2
docs-en/07-develop/03-insert-data/04-opentsdb-json.mdx
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@ -47,7 +47,7 @@ Please refer to [OpenTSDB HTTP API](http://opentsdb.net/docs/build/html/api_http
:::note
- In JSON protocol, strings will be converted to nchar type and numeric values will be converted to double type.
- Only data in array format is accepted, array must be used even there is only one row.
- Only data in array format is accepted and so an array must be used even if there is only one row.
:::

24
docs-en/07-develop/04-query-data/index.mdx
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@ -20,7 +20,7 @@ import CAsync from "./_c_async.mdx";
## Introduction
SQL is used by TDengine as the query language. Application programs can send SQL statements to TDengine through REST API or connectors. TDengine CLI `taos` can also be used to execute SQL Ad-Hoc queries. Here is the list of major query functionalities supported by TDengine：
SQL is used by TDengine as its query language. Application programs can send SQL statements to TDengine through REST API or connectors. TDengine's CLI `taos` can also be used to execute ad hoc SQL queries. Here is the list of major query functionalities supported by TDengine：
- Query on single column or multiple columns
- Filter on tags or data columns：>, <, =, <\>, like
@ -31,7 +31,7 @@ SQL is used by TDengine as the query language. Application programs can send SQL
- Join query with timestamp alignment
- Aggregate functions: count, max, min, avg, sum, twa, stddev, leastsquares, top, bottom, first, last, percentile, apercentile, last_row, spread, diff
For example, the SQL statement below can be executed in TDengine CLI `taos` to select the rows whose voltage column is bigger than 215 and limit the output to only 2 rows.
For example, the SQL statement below can be executed in TDengine CLI `taos` to select records with voltage greater than 215 and limit the output to only 2 rows.
```sql
select * from d1001 where voltage > 215 order by ts desc limit 2;
@ -46,46 +46,46 @@ taos> select * from d1001 where voltage > 215 order by ts desc limit 2;
Query OK, 2 row(s) in set (0.001100s)
```
To meet the requirements of many use cases, some special functions have been added in TDengine, for example `twa` (Time Weighted Average), `spared` (The difference between the maximum and the minimum), and `last_row` (the last row). Furthermore, continuous query is also supported in TDengine.
To meet the requirements of varied use cases, some special functions have been added in TDengine. Some examples are `twa` (Time Weighted Average), `spread` (The difference between the maximum and the minimum), and `last_row` (the last row). Furthermore, continuous query is also supported in TDengine.
For detailed query syntax please refer to [Select](/taos-sql/select).
## Aggregation among Tables
In many use cases, there are always multiple kinds of data collection points. A new concept, called STable (abbreviated for super table), is used in TDengine to represent a kind of data collection point, and a subtable is used to represent a specific data collection point. Tags are used by TDengine to represent the static properties of data collection points. A specific data collection point has its own values for static properties. By specifying filter conditions on tags, aggregation can be performed efficiently among all the subtables created via the same STable, i.e. same kind of data collection points. Aggregate functions applicable for tables can be used directly on STables, the syntax is exactly the same.
In most use cases, there are always multiple kinds of data collection points. A new concept, called STable (abbreviation for super table), is used in TDengine to represent one type of data collection point, and a subtable is used to represent a specific data collection point of that type. Tags are used by TDengine to represent the static properties of data collection points. A specific data collection point has its own values for static properties. By specifying filter conditions on tags, aggregation can be performed efficiently among all the subtables created via the same STable, i.e. same type of data collection points. Aggregate functions applicable for tables can be used directly on STables; the syntax is exactly the same.
In summary, for a STable, its subtables can be aggregated by a simple query on the STable, it's a kind of join operation. But tables belong to different STables can not be aggregated.
In summary, records across subtables can be aggregated by a simple query on their STable. It is like a join operation. However, tables belonging to different STables can not be aggregated.
### Example 1
In TDengine CLI `taos`, use below SQL to get the average voltage of all the meters in California grouped by location.
In TDengine CLI `taos`, use the SQL below to get the average voltage of all the meters in California grouped by location.
```
taos> SELECT AVG(voltage) FROM meters GROUP BY location;
avg(voltage) | location |
=============================================================
222.000000000 | California.LoSangeles |
222.000000000 | California.LosAngeles |
219.200000000 | California.SanFrancisco |
Query OK, 2 row(s) in set (0.002136s)
```
### Example 2
In TDengine CLI `taos`, use below SQL to get the number of rows and the maximum current in the past 24 hours from meters whose groupId is 2.
In TDengine CLI `taos`, use the SQL below to get the number of rows and the maximum current in the past 24 hours from meters whose groupId is 2.
```
taos> SELECT count(*), max(current) FROM meters where groupId = 2 and ts > now - 24h;
cunt(*) | max(current) |
count(*) | max(current) |
==================================
5 | 13.4 |
Query OK, 1 row(s) in set (0.002136s)
```
Join queries are only allowed between the subtables of the same STable. In [Select](/taos-sql/select), all query operations are marked as to whether they supports STables or not.
Join queries are only allowed between subtables of the same STable. In [Select](/taos-sql/select), all query operations are marked as to whether they support STables or not.
## Down Sampling and Interpolation
In IoT use cases, down sampling is widely used to aggregate the data by time range. The `INTERVAL` keyword in TDengine can be used to simplify the query by time window. For example, the SQL statement below can be used to get the sum of current every 10 seconds from meters table d1001.
In IoT use cases, down sampling is widely used to aggregate data by time range. The `INTERVAL` keyword in TDengine can be used to simplify the query by time window. For example, the SQL statement below can be used to get the sum of current every 10 seconds from meters table d1001.
```
taos> SELECT sum(current) FROM d1001 INTERVAL(10s);
@ -169,7 +169,7 @@ In the section describing [Insert](/develop/insert-data/sql-writing), a database
### Asynchronous Query
Besides synchronous queries, an asynchronous query API is also provided by TDengine to insert or query data more efficiently. With a similar hardware and software environment, the async API is 2~4 times faster than sync APIs. Async API works in non-blocking mode, which means an operation can be returned without finishing so that the calling thread can switch to other works to improve the performance of the whole application system. Async APIs perform especially better in the case of poor networks.
Besides synchronous queries, an asynchronous query API is also provided by TDengine to insert or query data more efficiently. With a similar hardware and software environment, the async API is 2~4 times faster than sync APIs. Async API works in non-blocking mode, which means an operation can be returned without finishing so that the calling thread can switch to other work to improve the performance of the whole application system. Async APIs perform especially better in the case of poor networks.
Please note that async query can only be used with a native connection.

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docs-en/07-develop/05-continuous-query.mdx
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@ -1,12 +1,12 @@
---
sidebar_label: Continuous Query
description: "Continuous query is a query that's executed automatically according to predefined frequency to provide aggregate query capability by time window, it's actually a simplified time driven stream computing."
description: "Continuous query is a query that's executed automatically at a predefined frequency to provide aggregate query capability by time window. It is essentially simplified, time driven, stream computing."
title: "Continuous Query"
---
Continuous query is a query that's executed automatically according to a predefined frequency to provide aggregate query capability by time window, it's actually a simplified time driven stream computing. Continuous query can be performed on a table or STable in TDengine. The result of continuous query can be pushed to clients or written back to TDengine. Each query is executed on a time window, which moves forward with time. The size of time window and the forward sliding time need to be specified with parameter `INTERVAL` and `SLIDING` respectively.
A continuous query is a query that's executed automatically at a predefined frequency to provide aggregate query capability by time window. It is essentially simplified, time driven, stream computing. A continuous query can be performed on a table or STable in TDengine. The results of a continuous query can be pushed to clients or written back to TDengine. Each query is executed on a time window, which moves forward with time. The size of time window and the forward sliding time need to be specified with parameter `INTERVAL` and `SLIDING` respectively.
Continuous query in TDengine is time driven, and can be defined using TAOS SQL directly without any extra operations. With continuous query, the result can be generated according to a time window to achieve down sampling of the original data. Once a continuous query is defined using TAOS SQL, the query is automatically executed at the end of each time window and the result is pushed back to clients or written to TDengine.
A continuous query in TDengine is time driven, and can be defined using TAOS SQL directly without any extra operations. With a continuous query, the result can be generated based on a time window to achieve down sampling of the original data. Once a continuous query is defined using TAOS SQL, the query is automatically executed at the end of each time window and the result is pushed back to clients or written to TDengine.
There are some differences between continuous query in TDengine and time window computation in stream computing：
@ -35,7 +35,7 @@ In this section the use case of meters will be used to introduce how to use cont
```sql
create table meters (ts timestamp, current float, voltage int, phase float) tags (location binary(64), groupId int);
create table D1001 using meters tags ("California.SanFrancisco", 2);
create table D1002 using meters tags ("California.LoSangeles", 2);
create table D1002 using meters tags ("California.LosAngeles", 2);
```
The SQL statement below retrieves the average voltage for a one minute time window, with each time window moving forward by 30 seconds.
@ -68,7 +68,7 @@ taos> select * from avg_vol;
2020-07-29 13:39:00.000 | 223.0800000 |
```
Please note that the minimum allowed time window is 10 milliseconds, and no upper limit.
Please note that the minimum allowed time window is 10 milliseconds, and there is no upper limit.
It's possible to specify the start and end time of a continuous query. If the start time is not specified, the timestamp of the first row will be considered as the start time; if the end time is not specified, the continuous query will be performed indefinitely, otherwise it will be terminated once the end time is reached. For example, the continuous query in the SQL statement below will be started from now and terminated one hour later.

38
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@ -1,6 +1,6 @@
---
sidebar_label: Subscription
description: "Lightweight service for data subscription and pushing, the time series data inserted into TDengine continuously can be pushed automatically to the subscribing clients."
description: "Lightweight service for data subscription and publishing. Time series data inserted into TDengine continuously can be pushed automatically to subscribing clients."
title: Data Subscription
---
@ -16,9 +16,9 @@ import CDemo from "./_sub_c.mdx";
## Introduction
Due to the nature of time series data, data inserting in TDengine is similar to data publishing in message queues. Data is stored in ascending order of timestamp inside TDengine, so each table in TDengine can essentially be considered as a message queue.
Due to the nature of time series data, data insertion into TDengine is similar to data publishing in message queues. Data is stored in ascending order of timestamp inside TDengine, and so each table in TDengine can essentially be considered as a message queue.
A lightweight service for data subscription and pushing is built in TDengine. With the API provided by TDengine, client programs can use `select` statements to subscribe to data from one or more tables. The subscription and state maintenance is performed on the client side, the client programs poll the server to check whether there is new data, and if so the new data will be pushed back to the client side. If the client program is restarted, where to start for retrieving new data is up to the client side.
A lightweight service for data subscription and publishing is built into TDengine. With the API provided by TDengine, client programs can use `select` statements to subscribe to data from one or more tables. The subscription and state maintenance is performed on the client side. The client programs poll the server to check whether there is new data, and if so the new data will be pushed back to the client side. If the client program is restarted, where to start retrieving new data is up to the client side.
There are 3 major APIs related to subscription provided in the TDengine client driver.
@ -32,7 +32,7 @@ For more details about these APIs please refer to [C/C++ Connector](/reference/c
If we want to get a notification and take some actions if the current exceeds a threshold, like 10A, from some meters, there are two ways:
The first way is to query on each sub table and record the last timestamp matching the criteria, then after some time query on the data later than recorded timestamp and repeat this process. The SQL statements for this way are as below.
The first way is to query each sub table and record the last timestamp matching the criteria. Then after some time, query the data later than the recorded timestamp, and repeat this process. The SQL statements for this way are as below.
```sql
select * from D1001 where ts > {last_timestamp1} and current > 10;
@ -50,7 +50,7 @@ select * from meters where ts > {last_timestamp} and current > 10;
However, this presents a new problem in how to choose `last_timestamp`. First, the timestamp when the data is generated is different from the timestamp when the data is inserted into the database, sometimes the difference between them may be very big. Second, the time when the data from different meters arrives at the database may be different too. If the timestamp of the "slowest" meter is used as `last_timestamp` in the query, the data from other meters may be selected repeatedly; but if the timestamp of the "fastest" meter is used as `last_timestamp`, some data from other meters may be missed.
All the problems mentioned above can be resolved thoroughly using subscription provided by TDengine.
All the problems mentioned above can be resolved easily using the subscription functionality provided by TDengine.
The first step is to create subscription using `taos_subscribe`.
@ -65,31 +65,33 @@ if (async) {
}
```
The subscription in TDengine can be either synchronous or asynchronous. In the above sample code, the value of variable `async` is determined from the CLI input, then it's used to create either an async or sync subscription. Sync subscription means the client program needs to invoke `taos_consume` to retrieve data, and async subscription means another thread created by `taos_subscribe` internally invokes `taos_consume` to retrieve data and pass the data to `subscribe_callback` for processing, `subscribe_callback` is a call back function provided by the client program and it's suggested not to do time consuming operation in the call back function.
The subscription in TDengine can be either synchronous or asynchronous. In the above sample code, the value of variable `async` is determined from the CLI input, then it's used to create either an async or sync subscription. Sync subscription means the client program needs to invoke `taos_consume` to retrieve data, and async subscription means another thread created by `taos_subscribe` internally invokes `taos_consume` to retrieve data and pass the data to `subscribe_callback` for processing. `subscribe_callback` is a callback function provided by the client program. You should not perform time consuming operations in the callback function.
The parameter `taos` is an established connection. There is nothing special in sync subscription mode. In async subscription, it should be exclusively by current thread, otherwise unpredictable error may occur.
The parameter `taos` is an established connection. Nothing special needs to be done for thread safety for synchronous subscription. For asynchronous subscription, the taos_subscribe function should be called exclusively by the current thread, to avoid unpredictable errors.
The parameter `sql` is a `select` statement in which `where` clause can be used to specify filter conditions. In our example, the data whose current exceeds 10A needs to be subscribed like below SQL statement:
The parameter `sql` is a `select` statement in which the `where` clause can be used to specify filter conditions. In our example, we can subscribe to the records in which the current exceeds 10A, with the following SQL statement:
```sql
select * from meters where current > 10;
```
Please note that, all the data will be processed because no start time is specified. If only the data from one day ago needs to be processed, a time related condition can be added:
Please note that, all the data will be processed because no start time is specified. If we only want to process data for the past day, a time related condition can be added:
```sql
select * from meters where ts > now - 1d and current > 10;
```
The parameter `topic` is the name of the subscription, it needs to be guaranteed unique in the client program, but it's not necessary to be globally unique because subscription is implemented in the APIs on the client side.
The parameter `topic` is the name of the subscription. The client application must guarantee that the name is unique. However, it doesn't have to be globally unique because subscription is implemented in the APIs on the client side.
If the subscription named as `topic` doesn't exist, the parameter `restart` will be ignored. If the subscription named as `topic` has been created before by the client program, when the client program is restarted with the subscription named `topic`, parameter `restart` is used to determine whether to retrieve data from the beginning or from the last point where the subscription was broken. If the value of `restart` is **true** (i.e. a non-zero value), the data will be retrieved from beginning, or if it is **false** (i.e. zero), the data already consumed before will not be processed again.
If the subscription named as `topic` doesn't exist, the parameter `restart` will be ignored. If the subscription named as `topic` has been created before by the client program, when the client program is restarted with the subscription named `topic`, parameter `restart` is used to determine whether to retrieve data from the beginning or from the last point where the subscription was broken.
The last parameter of `taos_subscribe` is the polling interval in unit of millisecond. In sync mode, if the time difference between two continuous invocations to `taos_consume` is smaller than the interval specified by `taos_subscribe`, `taos_consume` will be blocked until the interval is reached. In async mode, this interval is the minimum interval between two invocations to the call back function.
If the value of `restart` is **true** (i.e. a non-zero value), data will be retrieved from the beginning. If it is **false** (i.e. zero), the data already consumed before will not be processed again.
The last parameter of `taos_subscribe` is the polling interval in units of millisecond. In sync mode, if the time difference between two continuous invocations to `taos_consume` is smaller than the interval specified by `taos_subscribe`, `taos_consume` will be blocked until the interval is reached. In async mode, this interval is the minimum interval between two invocations to the call back function.
The second to last parameter of `taos_subscribe` is used to pass arguments to the call back function. `taos_subscribe` doesn't process this parameter and simply passes it to the call back function. This parameter is simply ignored in sync mode.
After a subscription is created, its data can be consumed and processed, below is the sample code of how to consume data in sync mode, in the else part if `if (async)`.
After a subscription is created, its data can be consumed and processed. Shown below is the sample code to consume data in sync mode, in the else condition of `if (async)`.
```c
if (async) {
@ -106,7 +108,7 @@ if (async) {
}
```
In the above sample code, there is an infinite loop, each time carriage return is entered `taos_consume` is invoked, the return value of `taos_consume` is the selected result set, exactly as the input of `taos_use_result`, in the above sample `print_result` is used instead to simplify the sample. Below is the implementation of `print_result`.
In the above sample code in the else condition, there is an infinite loop. Each time carriage return is entered `taos_consume` is invoked. The return value of `taos_consume` is the selected result set. In the above sample, `print_result` is used to simplify the printing of the result set. Below is the implementation of `print_result`.
```c
void print_result(TAOS_RES* res, int blockFetch) {
@ -133,9 +135,9 @@ void print_result(TAOS_RES* res, int blockFetch) {
}
```
In the above code `taos_print_row` is used to process the data consumed. All the matching rows will be printed.
In the above code `taos_print_row` is used to process the data consumed. All matching rows are printed.
In async mode, the data consuming is simpler as below.
In async mode, consuming data is simpler as shown below.
```c
void subscribe_callback(TAOS_SUB* tsub, TAOS_RES *res, void* param, int code) {
@ -175,7 +177,7 @@ Then, this row of data will be shown by the example program on the first termina
## Examples
Below example program demonstrates how to subscribe the data rows whose current exceeds 10A using connectors.
The example program below demonstrates how to subscribe, using connectors, to data rows in which current exceeds 10A.
### Prepare Data
@ -250,7 +252,7 @@ taos> use power;
taos> insert into d1001 values(now, 12.4, 220, 1);
```
Because the current in inserted row exceeds 10A, it will be consumed by the example program.
Because the current in the inserted row exceeds 10A, it will be consumed by the example program.
```
ts: 1651146662805 current: 12.4 voltage: 220 phase: 1 location: California.SanFrancisco groupid: 2

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@ -6,29 +6,35 @@ title: Deployment
### Step 1
The FQDN of all hosts needs to be setup properly, all the FQDNs need to be configured in the /etc/hosts of each host. It must be confirmed that each FQDN can be accessed (by ping, for example) from any other hosts.
The FQDN of all hosts must be setup properly. For e.g. FQDNs may have to be configured in the /etc/hosts file on each host. You must confirm that each FQDN can be accessed from any other host. For e.g. you can do this by using the `ping` command.
On each host the command `hostname -f` can be executed to get the hostname. `ping` command can be executed on each host to check whether any other host is accessible from it. If any host is not accessible, the network configuration, like /etc/hosts or DNS configuration, need to be checked and revised to make any two hosts accessible to each other.
To get the hostname on any host, the command `hostname -f` can be executed. `ping <FQDN>` command can be executed on each host to check whether any other host is accessible from it. If any host is not accessible, the network configuration, like /etc/hosts or DNS configuration, needs to be checked and revised, to make any two hosts accessible to each other.
:::note
- The host where the client program runs also needs to be configured properly for FQDN, to make sure all hosts for client or server can be accessed from any other. In other words, the hosts where the client is running are also considered as a part of the cluster.
- It's suggested to disable the firewall for all hosts in the cluster. At least TCP/UDP for port 6030~6042 need to be open if a firewall is enabled.
- Please ensure that your firewall rules do not block TCP/UDP on ports 6030-6042 on all hosts in the cluster.
:::
### Step 2
If any previous version of TDengine has been installed and configured on any host, the installation needs to be removed and the data needs to be cleaned up. For details about uninstalling please refer to [Install and Uninstall](/operation/pkg-install). To clean up the data, please use `rm -rf /var/lib/taos/\*` assuming the `dataDir` is configured as `/var/lib/taos`.
If any previous version of TDengine has been installed and configured on any host, the installation needs to be removed and the data needs to be cleaned up. For details about uninstalling please refer to [Install and Uninstall](/operation/pkg-install). To clean up the data, please use `rm -rf /var/lib/taos/\*` assuming the `dataDir` is configured as `/var/lib/taos`.
:::note
As a best practice, before cleaning up any data files or directories, please ensure that your data has been backed up correctly, if required by your data integrity, backup, security, or other standard operating protocols (SOP).
:::
### Step 3
Now it's time to install TDengine on all hosts without starting `taosd`, the versions on all hosts should be same. If it's prompted to input the existing TDengine cluster, simply press carriage return to ignore it. `install.sh -e no` can also be used to disable this prompt. For details please refer to [Install and Uninstall](/operation/pkg-install).
Now it's time to install TDengine on all hosts but without starting `taosd`. Note that the versions on all hosts should be same. If you are prompted to input the existing TDengine cluster, simply press carriage return to ignore the prompt. `install.sh -e no` can also be used to disable this prompt. For details please refer to [Install and Uninstall](/operation/pkg-install).
### Step 4
Now each physical node (referred to as `dnode` hereinafter, it's abbreviation for "data node") of TDengine needs to be configured properly. Please note that one dnode doesn't stand for one host, multiple TDengine nodes can be started on single host as long as they are configured properly without conflicting. More specifically each instance of the configuration file `taos.cfg` stands for a dnode. Assuming the first dnode of TDengine cluster is "h1.taosdata.com:6030", its `taos.cfg` is configured as following.
Now each physical node (referred to, hereinafter, as `dnode` which is an abbreviation for "data node") of TDengine needs to be configured properly. Please note that one dnode doesn't stand for one host. Multiple TDengine dnodes can be started on a single host as long as they are configured properly without conflicting. More specifically each instance of the configuration file `taos.cfg` stands for a dnode. Assuming the first dnode of TDengine cluster is "h1.taosdata.com:6030", its `taos.cfg` is configured as following.
```c
// firstEp is the end point to connect to when any dnode starts
@ -67,9 +73,11 @@ Prior to version 2.0.19.0, besides the above parameters, `locale` and `charset`
## Start Cluster
In the following example we assume that first dnode has FQDN h1.taosdata.com and the second dnode has FQDN h2.taosdata.com.
### Start The First DNODE
The first dnode can be started following the instructions in [Get Started](/get-started/), for example h1.taosdata.com. Then TDengine CLI `taos` can be launched to execute command `show dnodes`, the output is as following for example:
The first dnode can be started following the instructions in [Get Started](/get-started/). Then TDengine CLI `taos` can be launched to execute command `show dnodes`, the output is as following for example:
```
Welcome to the TDengine shell from Linux, Client Version:2.0.0.0
@ -80,27 +88,41 @@ Copyright (c) 2017 by TAOS Data, Inc. All rights reserved.
taos> show dnodes;
id | end_point | vnodes | cores | status | role | create_time |
=====================================================================================
1 | h1.taos.com:6030 | 0 | 2 | ready | any | 2020-07-31 03:49:29.202 |
1 | h1.taosdata.com:6030 | 0 | 2 | ready | any | 2020-07-31 03:49:29.202 |
Query OK, 1 row(s) in set (0.006385s)
taos>
```
From the above output, it is shown that the end point of the started dnode is "h1.taos.com:6030", which is the `firstEp` of the cluster.
From the above output, it is shown that the end point of the started dnode is "h1.taosdata.com:6030", which is the `firstEp` of the cluster.
### Start Other DNODEs
There are a few steps necessary to add other dnodes in the cluster.
First, start `taosd` as instructed in [Get Started](/get-started/), assuming it's for the second dnode. Before starting `taosd`, please making sure the configuration is correct, especially `firstEp`, `FQDN` and `serverPort`, `firstEp` must be same as the dnode shown in the section "Start First DNODE", i.e. "h1.taosdata.com" in this example.
Let's assume we are starting the second dnode with FQDN, h2.taosdata.com. First we make sure the configuration is correct.
Then, on the first dnode, use TDengine CLI `taos` to execute below command to add the end point of the dnode in the cluster. In the command "fqdn:port" should be quoted using double quotes.
```c
// firstEp is the end point to connect to when any dnode starts
firstEp h1.taosdata.com:6030
// must be configured to the FQDN of the host where the dnode is launched
fqdn h2.taosdata.com
// the port used by the dnode, default is 6030
serverPort 6030
```
Second, we can start `taosd` as instructed in [Get Started](/get-started/).
Then, on the first dnode i.e. h1.taosdata.com in our example, use TDengine CLI `taos` to execute the following command to add the end point of the dnode in the cluster. In the command "fqdn:port" should be quoted using double quotes.
```sql
CREATE DNODE "h2.taos.com:6030";
```
Then on the first dnode, execute `show dnodes` in `taos` to show whether the second dnode has been added in the cluster successfully or not.
Then on the first dnode h1.taosdata.com, execute `show dnodes` in `taos` to show whether the second dnode has been added in the cluster successfully or not.
```sql
SHOW DNODES;

17
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@ -7,12 +7,15 @@ title: Fault Tolerance & Disaster Recovery
TDengine uses **WAL**, i.e. Write Ahead Log, to achieve fault tolerance and high reliability.
When a data block is received by TDengine, the original data block is firstly written into WAL. The log in WAL will be deleted only after the data has been written into data files in the database. Data can be recovered from WAL in case the server is stopped abnormally due to any reason and then restarted.
When a data block is received by TDengine, the original data block is first written into WAL. The log in WAL will be deleted only after the data has been written into data files in the database. Data can be recovered from WAL in case the server is stopped abnormally due to any reason and then restarted.
There are 2 configuration parameters related to WAL:
- walLevel：0：wal is disabled; 1：wal is enabled without fsync; 2：wal is enabled with fsync.
- fsync：only valid when walLevel is set to 2, it specified the interval of invoking fsync. If set to 0, it means fsync is invoked immediately once WAL is written.
- walLevel：
- 0：wal is disabled;
- 1：wal is enabled without fsync;
- 2：wal is enabled with fsync.
- fsync：only valid when walLevel is set to 2, it specifies the interval of invoking fsync. If set to 0, it means fsync is invoked immediately once WAL is written.
To achieve absolutely no data loss, walLevel needs to be set to 2 and fsync needs to be set to 1. The penalty is the performance of data ingestion downgrades. However, if the concurrent threads of data insertion on the client side can reach a big enough number, for example 50, the data ingestion performance would be still good enough, our verification shows that the drop is only 30% compared to fsync is set to 3,000 milliseconds.
@ -20,10 +23,10 @@ To achieve absolutely no data loss, walLevel needs to be set to 2 and fsync need
TDengine uses replications to provide high availability and disaster recovery capability.
TDengine cluster is managed by mnode. To make sure the high availability of mnode, multiple replicas can be configured by system parameter `numOfMnodes`. The data replication between mnode replicas is in synchronous way to guarantee the metadata consistency.
TDengine cluster is managed by mnode. To make sure the high availability of mnode, multiple replicas can be configured by the system parameter `numOfMnodes`. The data replication between mnode replicas is performed in a synchronous way to guarantee the metadata consistency.
The number of replicas for time series data in TDengine is associated with each database, there can be a lot of databases in a cluster while each database can be configured with a different number of replicas. When creating a database, parameter `replica` is used to configure the number of replications. To achieve high availability, `replica` needs to be higher than 1.
The number of replicas for the time series data in TDengine is associated with each database, there can be a lot of databases in a cluster while each database can be configured with a different number of replicas. When creating a database, parameter `replica` is used to configure the number of replications. To achieve high availability, `replica` needs to be higher than 1.
The number of dnodes in a TDengine cluster must NOT be lower than the number of replicas for any database, otherwise it would fail when trying to create table.
The number of dnodes in a TDengine cluster must NOT be lower than the number of replicas for any database, otherwise it would fail when trying to create a table.
As long as the dnodes of a TDengine cluster are deployed on different physical machines and replica number is set to bigger than 1, high availability can be achieved without any other assistance. If dnodes of TDengine cluster are deployed in geographically different data centers, disaster recovery can be achieved too.
As long as the dnodes of a TDengine cluster are deployed on different physical machines and the replica number is set to bigger than 1, high availability can be achieved without any other assistance. If dnodes of TDengine cluster are deployed in geographically different data centers, disaster recovery can be achieved too.

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@ -2,7 +2,7 @@
title: User Management
---
System operator can use TDengine CLI `taos` to create or remove user or change password. The SQL command is as low:
A system operator can use TDengine CLI `taos` to create or remove users or change passwords. The SQL commands are documented below:
## Create User
@ -10,7 +10,7 @@ System operator can use TDengine CLI `taos` to create or remove user or change p
CREATE USER <user_name> PASS <'password'>;
```
When creating a user and specifying the user name and password, password needs to be quoted using single quotes.
When creating a user and specifying the user name and password, the password needs to be quoted using single quotes.
## Drop User
@ -18,7 +18,7 @@ When creating a user and specifying the user name and password, password needs t
DROP USER <user_name>;
```
Drop a user can only be performed by root.
Dropping a user can only be performed by root.
## Change Password
@ -26,7 +26,7 @@ Drop a user can only be performed by root.
ALTER USER <user_name> PASS <'password'>;
```
To keep the case of the password when changing password, password needs to be quoted using single quotes.
To keep the case of the password when changing password, the password needs to be quoted using single quotes.
## Change Privilege
@ -36,7 +36,7 @@ ALTER USER <user_name> PRIVILEGE <write|read>;
The privileges that can be changed to are `read` or `write` without single quotes.
Note：there is another privilege `super`, which not allowed to be authorized to any user.
Note：there is another privilege `super`, which is not allowed to be authorized to any user.
## Show Users
@ -45,6 +45,6 @@ SHOW USERS;
```
:::note
In SQL syntax, `< >` means the part that needs to be input by user, excluding the `< >` itself.
In SQL syntax, `< >` means the part that needs to be input by the user, excluding the `< >` itself.
:::

14
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@ -2,26 +2,26 @@
title: Data Import
---
There are multiple ways of importing data provided byTDengine: import with script, import from data file, import using `taosdump`.
There are multiple ways of importing data provided by TDengine: import with script, import from data file, import using `taosdump`.
## Import Using Script
TDengine CLI `taos` supports `source <filename>` command for executing the SQL statements in the file in batch. The SQL statements for creating databases, creating tables, and inserting rows can be written in single file with one statement on each line, then the file can be executed using `source` command in TDengine CLI `taos` to execute the SQL statements in order and in batch. In the script file, any line beginning with "#" is treated as comments and ignored silently.
TDengine CLI `taos` supports `source <filename>` command for executing the SQL statements in the file in batch. The SQL statements for creating databases, creating tables, and inserting rows can be written in a single file with one statement on each line, then the file can be executed using the `source` command in TDengine CLI `taos` to execute the SQL statements in order and in batch. In the script file, any line beginning with "#" is treated as comments and ignored silently.
## Import from Data File
In TDengine CLI, data can be imported from a CSV file into an existing table. The data in single CSV must belong to same table and must be consistent with the schema of that table. The SQL statement is as below:
In TDengine CLI, data can be imported from a CSV file into an existing table. The data in a single CSV must belong to the same table and must be consistent with the schema of that table. The SQL statement is as below:
```sql
insert into tb1 file 'path/data.csv';
```
:::note
If there is description in the first line of a CSV file, please remove it before importing. If there is no value for a column, please use `NULL` without quotes.
If there is a description in the first line of the CSV file, please remove it before importing. If there is no value for a column, please use `NULL` without quotes.
:::
For example, there is a sub table d1001 whose schema is as below:
For example, there is a subtable d1001 whose schema is as below:
```sql
taos> DESCRIBE d1001
@ -49,7 +49,7 @@ The format of the CSV file to be imported, data.csv, is as below:
'2018-10-12 06:38:05.000',18.30000,219,0.31000
```
Then, below SQL statement can be used to import data from file "data.csv", assuming the file is located under the home directory of current Linux user.
Then, the below SQL statement can be used to import data from file "data.csv", assuming the file is located under the home directory of the current Linux user.
```sql
taos> insert into d1001 file '~/data.csv';
@ -58,4 +58,4 @@ Query OK, 9 row(s) affected (0.004763s)
## Import using taosdump
A convenient tool for importing and exporting data is provided by TDengine, `taosdump`, which can used to export data from one TDengine cluster and import into another one. For the details of using `taosdump` please refer to [Tool for exporting and importing data: taosdump](/reference/taosdump).
A convenient tool for importing and exporting data is provided by TDengine, `taosdump`, which can be used to export data from one TDengine cluster and import into another one. For the details of using `taosdump` please refer to [Tool for exporting and importing data: taosdump](/reference/taosdump).

4
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@ -3,7 +3,7 @@ sidebar_label: Connections & Tasks
title: Manage Connections and Query Tasks
---
System operator can use TDengine CLI to show the connections, ongoing queries, stream computing, and can close connection or stop ongoing query task or stream computing.
A system operator can use TDengine CLI to show the connections, ongoing queries, stream computing, and can close connection or stop ongoing query task or stream computing.
## Show Connections
@ -51,4 +51,4 @@ The first column of the output is stream ID, which is composed of the connection
KILL STREAM <stream-id>;
```
The the above SQL command, `stream-id` is from the first column of the output of `SHOW STREAMS`.
The above SQL command, `stream-id` is from the first column of the output of `SHOW STREAMS`.

16
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@ -2,19 +2,19 @@
title: TDengine Monitoring
---
After TDengine is started, a database named `log` for monitoring is created automatically. The information about CPU, memory, disk, bandwidth, number of requests, disk I/O speed, slow query is written into `log` database on the basis of a predefined interval. Besides, some important system operations, like logon, create user, drop database, and alerts and warnings generated in TDengine are written into `log` database too. System operator can view the data in `log` database from TDengine CLI or from a web console.
After TDengine is started, a database named `log` for monitoring is created automatically. The information about CPU, memory, disk, bandwidth, number of requests, disk I/O speed, slow query is written into `log` database on the basis of a predefined interval. Additionally, some important system operations, like logon, create user, drop database, and alerts and warnings generated in TDengine are written into the `log` database too. A system operator can view the data in `log` database from TDengine CLI or from a web console.
Collection of the monitoring information is enabled by default, but can be disabled by parameter `monitor` in configuration file.
The collection of the monitoring information is enabled by default, but can be disabled by parameter `monitor` in the configuration file.
## TDinsight
TDinsight is a total solution which uses the monitor database `log` mentioned previously and Grafana to monitor a TDengine cluster.
TDinsight is a complete solution which uses the monitor database `log` mentioned previously and Grafana to monitor a TDengine cluster.
From version 2.3.3.0, more monitoring data has been added in the `log` database. Please refer to [TDinsight Grafana Dashboard](https://grafana.com/grafana/dashboards/15167) to learn more details about using TDinsight to monitor TDengine.
A script `TDinsight.sh` is provided to deploy TDinsight in automatic way.
A script `TDinsight.sh` is provided to deploy TDinsight automatically.
Download `TDinsight.sh` with below command:
Download `TDinsight.sh` with the below command:
```bash
wget https://github.com/taosdata/grafanaplugin/raw/master/dashboards/TDinsight.sh
@ -38,7 +38,7 @@ There are two ways to setup Grafana alert notification.
sudo ./TDinsight.sh -a http://localhost:6041 -u root -p taosdata -E <notifier uid>
```
- The AliCloud SMS alert built in TDengine data source plugin can be enabled with parameter `-s`, the parameters of this way are as follows:
- The AliCloud SMS alert built in TDengine data source plugin can be enabled with parameter `-s`, the parameters of enabling this plugin are listed below:
- `-I`: AliCloud SMS Key ID
- `-K`: AliCloud SMS Key Secret
@ -47,7 +47,7 @@ There are two ways to setup Grafana alert notification.
- `-T`: Input parameters in JSON format for the SMS notification template, for example`{"alarm_level":"%s","time":"%s","name":"%s","content":"%s"}`
- `-B`: List of mobile numbers to be notified
Below is an example of the full command using this way.
Below is an example of the full command using the AliCloud SMS alert.
```bash
sudo ./TDinsight.sh -a http://localhost:6041 -u root -p taosdata -s \
@ -55,6 +55,6 @@ There are two ways to setup Grafana alert notification.
-T '{"alarm_level":"%s","time":"%s","name":"%s","content":"%s"}'
```
Launch `TDinsight.sh` as above command and restart Grafana, then open Dashboard `http://localhost:3000/d/tdinsight`.
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/).

42
docs-en/13-operation/17-diagnose.md
View File

@ -10,13 +10,13 @@ The diagnostic for network connection can be executed between Linux and Linux or
Diagnostic steps：
1. If the port range to be diagnosed are being occupied by a `taosd` server process, please firstly stop `taosd.
2. On the server side, execute command `taos -n server -P <port> -l <pktlen>` to monitor the port range starting from the port specified by `-P` parameter with the role of "server.
3. On the client side, execute command `taos -n client -h <fqdn of server> -P <port> -l <pktlen>` to send testing package to the specified server and port.
1. If the port range to be diagnosed are being occupied by a `taosd` server process, please first stop `taosd.
2. On the server side, execute command `taos -n server -P <port> -l <pktlen>` to monitor the port range starting from the port specified by `-P` parameter with the role of "server".
3. On the client side, execute command `taos -n client -h <fqdn of server> -P <port> -l <pktlen>` to send a testing package to the specified server and port.
-l <pktlen\>： The size of the testing package, in bytes. The value range is [11, 64,000] and default value is 1,000. Please be noted that the package length must be same in the above 2 commands executed on server side and client side respectively.
-l <pktlen\>： The size of the testing package, in bytes. The value range is [11, 64,000] and default value is 1,000. Please note that the package length must be same in the above 2 commands executed on server side and client side respectively.
Output of the server side is as below for example:
Output of the server side for the example is below:
```bash
# taos -n server -P 6000
@ -47,7 +47,7 @@ Output of the server side is as below for example:
12/21 14:50:22.721261 0x7f53427ec700 UTL UDP: send:1000 bytes to 172.27.0.8 at 6011
```
Output of the client side is as below for example:
Output of the client side for the example is below:
```bash
# taos -n client -h 172.27.0.7 -P 6000
@ -65,13 +65,13 @@ Output of the client side is as below for example:
12/21 14:50:22.721274 0x7fc95d859200 UTL successed to test UDP port:6011
```
The output needs to be checked carefully for the system operator to find out root cause and solve the problem.
The output needs to be checked carefully for the system operator to find out the root cause and solve the problem.
## Startup Status and RPC Diagnostic
`taos -n startup -h <fqdn of server>` can be used to check the startup status of a `taosd` process. This is a comman task for a system operator to do to determine whether `taosd` has been started successfully, especially in case of cluster.
`taos -n rpc -h <fqdn of server>` can be used to check whether the port of a started `taosd` can be accessed or not. If `taosd` process doesn't respond or work abnormally, this command can be used to initiate a rpc communication with the specified fqdn to determine whether it's network problem or `taosd` is abnormal.
`taos -n rpc -h <fqdn of server>` can be used to check whether the port of a started `taosd` can be accessed or not. If `taosd` process doesn't respond or is working abnormally, this command can be used to initiate a rpc communication with the specified fqdn to determine whether it's a network problem or `taosd` is abnormal.
## Sync and Arbitrator Diagnostic
@ -80,7 +80,7 @@ taos -n sync -P 6040 -h <fqdn of server>
taos -n sync -P 6042 -h <fqdn of server>
```
The above commands can be executed on Linux Shell to check whether the port for sync works well and whether the sync module of the server side works well. Besides, `-P 6042` is used to check whether the arbitrator is configured properly and works well.
The above commands can be executed on Linux Shell to check whether the port for sync is working well and whether the sync module on the server side is working well. Additionally, `-P 6042` is used to check whether the arbitrator is configured properly and is working well.
## Network Speed Diagnostic
@ -88,12 +88,12 @@ The above commands can be executed on Linux Shell to check whether the port for
From version 2.2.0.0, the above command can be executed on Linux Shell to test the network speed, it sends uncompressed package to a running `taosd` server process or a simulated server process started by `taos -n server` to test the network speed. Parameters can be used when testing network speed are as below:
-n：When set to "speed", it means testing network speed
-h：The FQDN or IP of the server process to be connected to; if not set, the FQDN configured in `taos.cfg` is used
-P：The port of the server process to connect to, the default value is 6030
-N：The number of packages that will be sent in the test, range is [1,10000], default value is 100
-l：The size of each package in bytes, range is [1024, 1024 \* 1024 \* 1024], default value is 1024
-S：The type of network packages to send, can be either TCP or UDP, default value is
-n：When set to "speed", it means testing network speed.
-h：The FQDN or IP of the server process to be connected to; if not set, the FQDN configured in `taos.cfg` is used.
-P：The port of the server process to connect to, the default value is 6030.
-N：The number of packages that will be sent in the test, range is [1,10000], default value is 100.
-l：The size of each package in bytes, range is [1024, 1024 \* 1024 \* 1024], default value is 1024.
-S：The type of network packages to send, can be either TCP or UDP, default value is TCP.
## FQDN Resolution Diagnostic
@ -101,22 +101,22 @@ From version 2.2.0.0, the above command can be executed on Linux Shell to test t
From version 2.2.0.0, the above command can be executed on Linux Shell to test the resolution speed of FQDN. It can be used to try to resolve a FQDN to an IP address and record the time spent in this process. The parameters that can be used for this purpose are as below:
-n：When set to "fqdn", it means testing the speed of resolving FQDN
-h：The FQDN to be resolved. If not set, the `FQDN` parameter in `taos.cfg` is used by default.
-n：When set to "fqdn", it means testing the speed of resolving FQDN.
-h：The FQDN to be resolved. If not set, the `FQDN` parameter in `taos.cfg` is used by default.
## Server Log
The parameter `debugFlag` is used to control the log level of `taosd` server process. The default value is 131, for debug purpose it needs to be escalated to 135 or 143.
The parameter `debugFlag` is used to control the log level of the `taosd` server process. The default value is 131, for debug purpose it needs to be escalated to 135 or 143.
Once this parameter is set to 135 or 143, the log file grows very quickly especially when there is huge volume of data insertion and data query requests. If all the logs are stored together, some important information may be missed very easily, so on server side important information is stored at different place from other logs.
Once this parameter is set to 135 or 143, the log file grows very quickly especially when there is a huge volume of data insertion and data query requests. If all the logs are stored together, some important information may be missed very easily, so on server side important information is stored at different place from other logs.
- The log at level of INFO, WARNING and ERROR is stored in `taosinfo` so that it is easy to find important information
- The log at level of DEBUG (135) and TRACE (143) and other information not handled by `taosinfo` are stored in `taosdlog`
## Client Log
An independent log file, named as "taoslog+<seq num\>" is generated for each client program, i.e. a client process. The default value of `debugFlag` is also 131 and only log at level of INFO/ERROR/WARNING is recorded, it and needs to be changed to 135 or 143 so that log at DEBUG or TRACE level can be recorded for debugging purpose.
An independent log file, named as "taoslog+<seq num\>" is generated for each client program, i.e. a client process. The default value of `debugFlag` is also 131 and only logs at level of INFO/ERROR/WARNING are recorded, for debugging purposes it needs to be changed to 135 or 143 so that logs at DEBUG or TRACE level can be recorded.
The maximum length of a single log file is controlled by parameter `numOfLogLines` and only 2 log files are kept for each `taosd` server process.
log file is written in async way to minimize the workload on disk, bu the penalty is that a few log lines may be lost in some extreme conditions.
Log files are written in an async way to minimize the workload on disk, but the trade off for performance is that a few log lines may be lost in some extreme conditions.

15
include/common/tmsgdef.h
View File

@ -195,11 +195,8 @@ enum {
TD_DEF_MSG_TYPE(TDMT_VND_EXPLAIN, "vnode-explain", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_SUBSCRIBE, "vnode-subscribe", SMVSubscribeReq, SMVSubscribeRsp)
TD_DEF_MSG_TYPE(TDMT_VND_CONSUME, "vnode-consume", SMqCVConsumeReq, SMqCVConsumeRsp)
TD_DEF_MSG_TYPE(TDMT_VND_CONSUME, "vnode-consume", SMqPollReq, SMqDataBlkRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TASK_DEPLOY, "vnode-task-deploy", SStreamTaskDeployReq, SStreamTaskDeployRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TASK_PIPE_EXEC, "vnode-task-pipe-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TASK_MERGE_EXEC, "vnode-task-merge-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
TD_DEF_MSG_TYPE(TDMT_VND_TASK_WRITE_EXEC, "vnode-task-write-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
TD_DEF_MSG_TYPE(TDMT_VND_STREAM_TRIGGER, "vnode-stream-trigger", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_VND_TASK_RUN, "vnode-stream-task-run", NULL, NULL)
@ -236,9 +233,13 @@ enum {
// Requests handled by SNODE
TD_NEW_MSG_SEG(TDMT_SND_MSG)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_DEPLOY, "snode-task-deploy", SStreamTaskDeployReq, SStreamTaskDeployRsp)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_EXEC, "snode-task-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_PIPE_EXEC, "snode-task-pipe-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_MERGE_EXEC, "snode-task-merge-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
//TD_DEF_MSG_TYPE(TDMT_SND_TASK_EXEC, "snode-task-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
//TD_DEF_MSG_TYPE(TDMT_SND_TASK_PIPE_EXEC, "snode-task-pipe-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
//TD_DEF_MSG_TYPE(TDMT_SND_TASK_MERGE_EXEC, "snode-task-merge-exec", SStreamTaskExecReq, SStreamTaskExecRsp)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_RUN, "snode-stream-task-run", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_DISPATCH, "snode-stream-task-dispatch", NULL, NULL)
TD_DEF_MSG_TYPE(TDMT_SND_TASK_RECOVER, "snode-stream-task-recover", NULL, NULL)
// Requests handled by SCHEDULER
TD_NEW_MSG_SEG(TDMT_SCH_MSG)

1
include/libs/catalog/catalog.h
View File

@ -101,6 +101,7 @@ typedef struct SDbVgVersion {
typedef struct STbSVersion {
char* tbFName;
int32_t sver;
int32_t tver;
} STbSVersion;
typedef struct SUserAuthVersion {

5
include/libs/sync/sync.h
View File

@ -80,6 +80,7 @@ typedef struct SFsmCbMeta {
uint64_t seqNum;
SyncTerm term;
SyncTerm currentTerm;
uint64_t flag;
} SFsmCbMeta;
typedef struct SReConfigCbMeta {
@ -87,6 +88,9 @@ typedef struct SReConfigCbMeta {
SyncIndex index;
SyncTerm term;
SyncTerm currentTerm;
SSyncCfg oldCfg;
bool isDrop;
uint64_t flag;
} SReConfigCbMeta;
typedef struct SSyncFSM {
@ -162,6 +166,7 @@ void syncCleanUp();
int64_t syncOpen(const SSyncInfo* pSyncInfo);
void syncStart(int64_t rid);
void syncStop(int64_t rid);
int32_t syncSetStandby(int64_t rid);
int32_t syncReconfig(int64_t rid, const SSyncCfg* pSyncCfg);
ESyncState syncGetMyRole(int64_t rid);
const char* syncGetMyRoleStr(int64_t rid);

14
source/client/src/clientImpl.c
View File

@ -413,7 +413,7 @@ int32_t validateSversion(SRequestObj* pRequest, void* res) {
for (int32_t i = 0; i < tbNum; ++i) {
STbVerInfo* tbInfo = taosArrayGet(pTbArray, i);
STbSVersion tbSver = {.tbFName = tbInfo->tbFName, .sver = tbInfo->sversion};
STbSVersion tbSver = {.tbFName = tbInfo->tbFName, .sver = tbInfo->sversion, .tver = tbInfo->tversion};
taosArrayPush(pArray, &tbSver);
}
}
@ -745,12 +745,12 @@ void processMsgFromServer(void* parent, SRpcMsg* pMsg, SEpSet* pEpSet) {
pRequest->metric.rsp = taosGetTimestampUs();
STscObj* pTscObj = pRequest->pTscObj;
if (pEpSet) {
if (!isEpsetEqual(&pTscObj->pAppInfo->mgmtEp.epSet, pEpSet)) {
updateEpSet_s(&pTscObj->pAppInfo->mgmtEp, pEpSet);
}
}
//STscObj* pTscObj = pRequest->pTscObj;
//if (pEpSet) {
// if (!isEpsetEqual(&pTscObj->pAppInfo->mgmtEp.epSet, pEpSet)) {
// updateEpSet_s(&pTscObj->pAppInfo->mgmtEp, pEpSet);
// }
//}
/*
* There is not response callback function for submit response.

7
source/dnode/mgmt/mgmt_dnode/src/dmHandle.c
View File

@ -92,6 +92,13 @@ void dmSendStatusReq(SDnodeMgmt *pMgmt) {
SEpSet epSet = {0};
dmGetMnodeEpSet(pMgmt->pData, &epSet);
rpcSendRecv(pMgmt->msgCb.clientRpc, &epSet, &rpcMsg, &rpcRsp);
if (rpcRsp.code != 0) {
dError("failed to send status msg since %s, numOfEps:%d inUse:%d", tstrerror(rpcRsp.code), epSet.numOfEps,
epSet.inUse);
for (int32_t i = 0; i < epSet.numOfEps; ++i) {
dDebug("index:%d, mnode ep:%s:%u", i, epSet.eps[i].fqdn, epSet.eps[i].port);
}
}
dmProcessStatusRsp(pMgmt, &rpcRsp);
}

2
source/dnode/mgmt/mgmt_snode/src/smHandle.c
View File

@ -96,7 +96,7 @@ SArray *smGetMsgHandles() {
// Requests handled by SNODE
if (dmSetMgmtHandle(pArray, TDMT_SND_TASK_DEPLOY, smPutNodeMsgToMgmtQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_SND_TASK_EXEC, smPutNodeMsgToExecQueue, 0) == NULL) goto _OVER;
/*if (dmSetMgmtHandle(pArray, TDMT_SND_TASK_EXEC, smPutNodeMsgToExecQueue, 0) == NULL) goto _OVER;*/
code = 0;
_OVER:

3
source/dnode/mgmt/mgmt_vnode/src/vmHandle.c
View File

@ -310,9 +310,6 @@ SArray *vmGetMsgHandles() {
if (dmSetMgmtHandle(pArray, TDMT_VND_CONSUME, vmPutNodeMsgToFetchQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_TASK_DEPLOY, vmPutNodeMsgToWriteQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_QUERY_HEARTBEAT, vmPutNodeMsgToFetchQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_TASK_PIPE_EXEC, vmPutNodeMsgToFetchQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_TASK_MERGE_EXEC, vmPutNodeMsgToMergeQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_TASK_WRITE_EXEC, vmPutNodeMsgToWriteQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_STREAM_TRIGGER, vmPutNodeMsgToFetchQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_TASK_RUN, vmPutNodeMsgToFetchQueue, 0) == NULL) goto _OVER;
if (dmSetMgmtHandle(pArray, TDMT_VND_TASK_DISPATCH, vmPutNodeMsgToFetchQueue, 0) == NULL) goto _OVER;

1
source/dnode/mnode/impl/src/mndCluster.c
View File

@ -144,6 +144,7 @@ _OVER:
static int32_t mndClusterActionInsert(SSdb *pSdb, SClusterObj *pCluster) {
mTrace("cluster:%" PRId64 ", perform insert action, row:%p", pCluster->id, pCluster);
pSdb->pMnode->clusterId = pCluster->id;
return 0;
}

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

@ -441,7 +441,7 @@ static int32_t mndProcessStatusReq(SRpcMsg *pReq) {
pDnode->numOfSupportVnodes = statusReq.numOfSupportVnodes;
SStatusRsp statusRsp = {0};
statusRsp.dnodeVer = sdbGetTableVer(pMnode->pSdb, SDB_DNODE);
statusRsp.dnodeVer = sdbGetTableVer(pMnode->pSdb, SDB_DNODE) + sdbGetTableVer(pMnode->pSdb, SDB_MNODE);
statusRsp.dnodeCfg.dnodeId = pDnode->id;
statusRsp.dnodeCfg.clusterId = pMnode->clusterId;
statusRsp.pDnodeEps = taosArrayInit(mndGetDnodeSize(pMnode), sizeof(SDnodeEp));

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

@ -233,7 +233,7 @@ void mndGetMnodeEpSet(SMnode *pMnode, SEpSet *pEpSet) {
if (pObj->pDnode == NULL) {
mError("mnode:%d, no corresponding dnode exists", pObj->id);
} else {
if (pObj->state == TAOS_SYNC_STATE_LEADER) {
if (pObj->id == pMnode->selfDnodeId || pObj->state == TAOS_SYNC_STATE_LEADER) {
pEpSet->inUse = pEpSet->numOfEps;
}
addEpIntoEpSet(pEpSet, pObj->pDnode->fqdn, pObj->pDnode->port);

9
source/dnode/mnode/impl/src/mndScheduler.c
View File

@ -359,7 +359,8 @@ int32_t mndScheduleStream(SMnode* pMnode, STrans* pTrans, SStreamObj* pStream) {
// one merge only
ASSERT(taosArrayGetSize(pArray) == 1);
SStreamTask* lastLevelTask = taosArrayGetP(pArray, 0);
pTask->dispatchMsgType = TDMT_VND_TASK_MERGE_EXEC;
/*pTask->dispatchMsgType = TDMT_VND_TASK_MERGE_EXEC;*/
pTask->dispatchMsgType = TDMT_VND_TASK_DISPATCH;
pTask->dispatchType = TASK_DISPATCH__FIXED;
pTask->fixedEpDispatcher.taskId = lastLevelTask->taskId;
@ -404,7 +405,8 @@ int32_t mndScheduleStream(SMnode* pMnode, STrans* pTrans, SStreamObj* pStream) {
if (pStream->fixedSinkVgId == 0) {
pTask->dispatchType = TASK_DISPATCH__SHUFFLE;
pTask->dispatchMsgType = TDMT_VND_TASK_WRITE_EXEC;
/*pTask->dispatchMsgType = TDMT_VND_TASK_WRITE_EXEC;*/
pTask->dispatchMsgType = TDMT_VND_TASK_DISPATCH;
SDbObj* pDb = mndAcquireDb(pMnode, pStream->sourceDb);
ASSERT(pDb);
if (mndExtractDbInfo(pMnode, pDb, &pTask->shuffleDispatcher.dbInfo, NULL) < 0) {
@ -434,7 +436,8 @@ int32_t mndScheduleStream(SMnode* pMnode, STrans* pTrans, SStreamObj* pStream) {
}
} else {
pTask->dispatchType = TASK_DISPATCH__FIXED;
pTask->dispatchMsgType = TDMT_VND_TASK_WRITE_EXEC;
/*pTask->dispatchMsgType = TDMT_VND_TASK_WRITE_EXEC;*/
pTask->dispatchMsgType = TDMT_VND_TASK_DISPATCH;
SArray* pArray = taosArrayGetP(pStream->tasks, 0);
// one sink only
ASSERT(taosArrayGetSize(pArray) == 1);

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

@ -1503,6 +1503,7 @@ static int32_t mndBuildStbSchemaImp(SDbObj *pDb, SStbObj *pStb, const char *tbNa
pRsp->precision = pDb->cfg.precision;
pRsp->tableType = TSDB_SUPER_TABLE;
pRsp->sversion = pStb->colVer;
pRsp->tversion = pStb->tagVer;
pRsp->suid = pStb->uid;
pRsp->tuid = pStb->uid;
@ -1629,7 +1630,7 @@ int32_t mndValidateStbInfo(SMnode *pMnode, SSTableMetaVersion *pStbVersions, int
metaRsp.suid = pStbVersion->suid;
}
if (pStbVersion->sversion != metaRsp.sversion) {
if (pStbVersion->sversion != metaRsp.sversion || pStbVersion->tversion != metaRsp.tversion) {
taosArrayPush(batchMetaRsp.pArray, &metaRsp);
} else {
tFreeSTableMetaRsp(&metaRsp);

1
source/dnode/mnode/impl/src/mndSync.c
View File

@ -51,6 +51,7 @@ int32_t mndSyncGetSnapshot(struct SSyncFSM *pFsm, SSnapshot *pSnapshot) {
void mndRestoreFinish(struct SSyncFSM *pFsm) {
SMnode *pMnode = pFsm->data;
if (!pMnode->deploy) {
mInfo("mnode sync restore finished");
mndTransPullup(pMnode);
pMnode->syncMgmt.restored = true;
}

2
source/dnode/mnode/impl/test/stb/stb.cpp
View File

@ -344,7 +344,7 @@ TEST_F(MndTestStb, 01_Create_Show_Meta_Drop_Restart_Stb) {
EXPECT_EQ(metaRsp.precision, TSDB_TIME_PRECISION_MILLI);
EXPECT_EQ(metaRsp.tableType, TSDB_SUPER_TABLE);
EXPECT_EQ(metaRsp.sversion, 1);
EXPECT_EQ(metaRsp.tversion, 0);
EXPECT_EQ(metaRsp.tversion, 1);
EXPECT_GT(metaRsp.suid, 0);
EXPECT_GT(metaRsp.tuid, 0);
EXPECT_EQ(metaRsp.vgId, 0);

14
source/dnode/snode/src/snode.c
View File

@ -103,8 +103,8 @@ void sndProcessUMsg(SSnode *pSnode, SRpcMsg *pMsg) {
tDecoderClear(&decoder);
sndMetaDeployTask(pSnode->pMeta, pTask);
} else if (pMsg->msgType == TDMT_SND_TASK_EXEC) {
sndProcessTaskExecReq(pSnode, pMsg);
/*} else if (pMsg->msgType == TDMT_SND_TASK_EXEC) {*/
/*sndProcessTaskExecReq(pSnode, pMsg);*/
} else {
ASSERT(0);
}
@ -112,9 +112,9 @@ void sndProcessUMsg(SSnode *pSnode, SRpcMsg *pMsg) {
void sndProcessSMsg(SSnode *pSnode, SRpcMsg *pMsg) {
// operator exec
if (pMsg->msgType == TDMT_SND_TASK_EXEC) {
sndProcessTaskExecReq(pSnode, pMsg);
} else {
ASSERT(0);
}
/*if (pMsg->msgType == TDMT_SND_TASK_EXEC) {*/
/*sndProcessTaskExecReq(pSnode, pMsg);*/
/*} else {*/
ASSERT(0);
/*}*/
}

2
source/libs/catalog/inc/catalogInt.h
View File

@ -447,7 +447,7 @@ void ctgReleaseVgInfo(SCtgDBCache *dbCache);
int32_t ctgAcquireVgInfoFromCache(SCatalog* pCtg, const char *dbFName, SCtgDBCache **pCache);
int32_t ctgTbMetaExistInCache(SCatalog* pCtg, char *dbFName, char* tbName, int32_t *exist);
int32_t ctgReadTbMetaFromCache(SCatalog* pCtg, SCtgTbMetaCtx* ctx, STableMeta** pTableMeta);
int32_t ctgReadTbSverFromCache(SCatalog *pCtg, const SName *pTableName, int32_t *sver, int32_t *tbType, uint64_t *suid, char *stbName);
int32_t ctgReadTbVerFromCache(SCatalog *pCtg, const SName *pTableName, int32_t *sver, int32_t *tver, int32_t *tbType, uint64_t *suid, char *stbName);
int32_t ctgChkAuthFromCache(SCatalog* pCtg, const char* user, const char* dbFName, AUTH_TYPE type, bool *inCache, bool *pass);
int32_t ctgPutRmDBToQueue(SCatalog* pCtg, const char *dbFName, int64_t dbId);
int32_t ctgPutRmStbToQueue(SCatalog* pCtg, const char *dbFName, int64_t dbId, const char *stbName, uint64_t suid, bool syncReq);

5
source/libs/catalog/src/catalog.c
View File

@ -812,6 +812,7 @@ int32_t catalogChkTbMetaVersion(SCatalog* pCtg, void *pTrans, const SEpSet* pMgm
SName name;
int32_t sver = 0;
int32_t tver = 0;
int32_t tbNum = taosArrayGetSize(pTables);
for (int32_t i = 0; i < tbNum; ++i) {
STbSVersion* pTb = (STbSVersion*)taosArrayGet(pTables, i);
@ -828,8 +829,8 @@ int32_t catalogChkTbMetaVersion(SCatalog* pCtg, void *pTrans, const SEpSet* pMgm
int32_t tbType = 0;
uint64_t suid = 0;
char stbName[TSDB_TABLE_FNAME_LEN];
ctgReadTbSverFromCache(pCtg, &name, &sver, &tbType, &suid, stbName);
if (sver >= 0 && sver < pTb->sver) {
ctgReadTbVerFromCache(pCtg, &name, &sver, &tver, &tbType, &suid, stbName);
if ((sver >= 0 && sver < pTb->sver) || (tver >= 0 && tver < pTb->tver)) {
switch (tbType) {
case TSDB_CHILD_TABLE: {
SName stb = name;

9
source/libs/catalog/src/ctgCache.c
View File

@ -322,9 +322,10 @@ _return:
CTG_RET(code);
}
int32_t ctgReadTbSverFromCache(SCatalog *pCtg, const SName *pTableName, int32_t *sver, int32_t *tbType, uint64_t *suid,
int32_t ctgReadTbVerFromCache(SCatalog *pCtg, const SName *pTableName, int32_t *sver, int32_t *tver, int32_t *tbType, uint64_t *suid,
char *stbName) {
*sver = -1;
*tver = -1;
if (NULL == pCtg->dbCache) {
ctgDebug("empty tbmeta cache, tbName:%s", pTableName->tname);
@ -348,6 +349,7 @@ int32_t ctgReadTbSverFromCache(SCatalog *pCtg, const SName *pTableName, int32_t
*suid = tbMeta->suid;
if (*tbType != TSDB_CHILD_TABLE) {
*sver = tbMeta->sversion;
*tver = tbMeta->tversion;
}
}
CTG_UNLOCK(CTG_READ, &dbCache->tbCache.metaLock);
@ -359,7 +361,7 @@ int32_t ctgReadTbSverFromCache(SCatalog *pCtg, const SName *pTableName, int32_t
if (*tbType != TSDB_CHILD_TABLE) {
ctgReleaseDBCache(pCtg, dbCache);
ctgDebug("Got sver %d from cache, type:%d, dbFName:%s, tbName:%s", *sver, *tbType, dbFName, pTableName->tname);
ctgDebug("Got sver %d tver %d from cache, type:%d, dbFName:%s, tbName:%s", *sver, *tver, *tbType, dbFName, pTableName->tname);
return TSDB_CODE_SUCCESS;
}
@ -391,12 +393,13 @@ int32_t ctgReadTbSverFromCache(SCatalog *pCtg, const SName *pTableName, int32_t
stbName[nameLen] = 0;
*sver = (*stbMeta)->sversion;
*tver = (*stbMeta)->tversion;
CTG_UNLOCK(CTG_READ, &dbCache->tbCache.stbLock);
ctgReleaseDBCache(pCtg, dbCache);
ctgDebug("Got sver %d from cache, type:%d, dbFName:%s, tbName:%s", *sver, *tbType, dbFName, pTableName->tname);
ctgDebug("Got sver %d tver %d from cache, type:%d, dbFName:%s, tbName:%s", *sver, *tver, *tbType, dbFName, pTableName->tname);
return TSDB_CODE_SUCCESS;
}

4
source/libs/function/inc/builtinsimpl.h
View File

@ -84,9 +84,9 @@ int32_t diffFunction(SqlFunctionCtx *pCtx);
bool getFirstLastFuncEnv(struct SFunctionNode* pFunc, SFuncExecEnv* pEnv);
int32_t firstFunction(SqlFunctionCtx *pCtx);
int32_t firstCombine(SqlFunctionCtx* pDestCtx, SqlFunctionCtx* pSourceCtx);
int32_t lastFunction(SqlFunctionCtx *pCtx);
int32_t firstlastFinalize(SqlFunctionCtx* pCtx, SSDataBlock* pBlock);
int32_t firstLastFinalize(SqlFunctionCtx* pCtx, SSDataBlock* pBlock);
int32_t firstCombine(SqlFunctionCtx* pDestCtx, SqlFunctionCtx* pSourceCtx);
int32_t lastCombine(SqlFunctionCtx* pDestCtx, SqlFunctionCtx* pSourceCtx);
bool getTopBotFuncEnv(SFunctionNode* UNUSED_PARAM(pFunc), SFuncExecEnv* pEnv);

16
source/libs/function/src/builtins.c
View File

@ -318,6 +318,11 @@ static int32_t translateElapsed(SFunctionNode* pFunc, char* pErrBuf, int32_t len
if (!IS_INTEGER_TYPE(paraType)) {
return invaildFuncParaTypeErrMsg(pErrBuf, len, pFunc->functionName);
}
if (pValue->datum.i == 0) {
return buildFuncErrMsg(pErrBuf, len, TSDB_CODE_FUNC_FUNTION_ERROR,
"ELAPSED function time unit parameter should be greater than db precision");
}
}
pFunc->node.resType = (SDataType){.bytes = tDataTypes[TSDB_DATA_TYPE_DOUBLE].bytes, .type = TSDB_DATA_TYPE_DOUBLE};
@ -803,9 +808,14 @@ static int32_t translateCast(SFunctionNode* pFunc, char* pErrBuf, int32_t len) {
(para2Type == TSDB_DATA_TYPE_BINARY && para1Type == TSDB_DATA_TYPE_NCHAR)) {
return invaildFuncParaTypeErrMsg(pErrBuf, len, pFunc->functionName);
}
int32_t para2Bytes = pFunc->node.resType.bytes;
if (IS_VAR_DATA_TYPE(para2Type)) {
para2Bytes -= VARSTR_HEADER_SIZE;
}
if (para2Bytes <= 0 || para2Bytes > 1000) { // cast dst var type length limits to 1000
return invaildFuncParaValueErrMsg(pErrBuf, len, pFunc->functionName);
return buildFuncErrMsg(pErrBuf, len, TSDB_CODE_FUNC_FUNTION_ERROR,
"CAST function converted length should be in range [0, 1000]");
}
return TSDB_CODE_SUCCESS;
}
@ -1063,7 +1073,7 @@ const SBuiltinFuncDefinition funcMgtBuiltins[] = {
.getEnvFunc = getFirstLastFuncEnv,
.initFunc = functionSetup,
.processFunc = firstFunction,
.finalizeFunc = firstlastFinalize,
.finalizeFunc = firstLastFinalize,
.combineFunc = firstCombine,
},
{
@ -1074,7 +1084,7 @@ const SBuiltinFuncDefinition funcMgtBuiltins[] = {
.getEnvFunc = getFirstLastFuncEnv,
.initFunc = functionSetup,
.processFunc = lastFunction,
.finalizeFunc = firstlastFinalize,
.finalizeFunc = firstLastFinalize,
.combineFunc = lastCombine,
},
{

2
source/libs/function/src/builtinsimpl.c
View File

@ -2227,7 +2227,7 @@ int32_t lastFunction(SqlFunctionCtx* pCtx) {
return TSDB_CODE_SUCCESS;
}
int32_t firstlastFinalize(SqlFunctionCtx* pCtx, SSDataBlock* pBlock) {
int32_t firstLastFinalize(SqlFunctionCtx* pCtx, SSDataBlock* pBlock) {
int32_t slotId = pCtx->pExpr->base.resSchema.slotId;
SColumnInfoData* pCol = taosArrayGet(pBlock->pDataBlock, slotId);

1
source/libs/qworker/inc/qworkerInt.h
View File

@ -227,6 +227,7 @@ typedef struct SQWorkerMgmt {
#define QW_ELOG(_param, ...) qError("QW:%p " _param, mgmt, __VA_ARGS__)
#define QW_DLOG(_param, ...) qDebug("QW:%p " _param, mgmt, __VA_ARGS__)
#define QW_TLOG(_param, ...) qTrace("QW:%p " _param, mgmt, __VA_ARGS__)
#define QW_DUMP(_param, ...) \
do { \

2
source/libs/qworker/src/qworker.c
View File

@ -1409,7 +1409,7 @@ void qwProcessHbTimerEvent(void *param, void *tmrId) {
SQWSchStatus *sch = (SQWSchStatus *)pIter;
if (NULL == sch->hbConnInfo.handle) {
uint64_t *sId = taosHashGetKey(pIter, NULL);
QW_DLOG("cancel send hb to sch %" PRIx64 " cause of no connection handle", *sId);
QW_TLOG("cancel send hb to sch %" PRIx64 " cause of no connection handle", *sId);
pIter = taosHashIterate(mgmt->schHash, pIter);
continue;
}

9
source/libs/scheduler/src/schRemote.c
View File

@ -557,7 +557,9 @@ int32_t schMakeHbCallbackParam(SSchJob *pJob, SSchTask *pTask, void **pParam) {
SQueryNodeAddr *addr = taosArrayGet(pTask->candidateAddrs, pTask->candidateIdx);
param->nodeEpId.nodeId = addr->nodeId;
memcpy(&param->nodeEpId.ep, SCH_GET_CUR_EP(addr), sizeof(SEp));
SEp* pEp = SCH_GET_CUR_EP(addr);
strcpy(param->nodeEpId.ep.fqdn, pEp->fqdn);
param->nodeEpId.ep.port = pEp->port;
param->pTrans = pJob->pTrans;
*pParam = param;
@ -788,7 +790,10 @@ int32_t schEnsureHbConnection(SSchJob *pJob, SSchTask *pTask) {
SQueryNodeEpId epId = {0};
epId.nodeId = addr->nodeId;
memcpy(&epId.ep, SCH_GET_CUR_EP(addr), sizeof(SEp));
SEp* pEp = SCH_GET_CUR_EP(addr);
strcpy(epId.ep.fqdn, pEp->fqdn);
epId.ep.port = pEp->port;
SSchHbTrans *hb = taosHashGet(schMgmt.hbConnections, &epId, sizeof(SQueryNodeEpId));
if (NULL == hb) {

12
source/libs/stream/src/tstream.c
View File

@ -278,13 +278,13 @@ int32_t streamSink(SStreamTask* pTask, SMsgCb* pMsgCb) {
}
int32_t qType;
if (pTask->dispatchMsgType == TDMT_VND_TASK_PIPE_EXEC || pTask->dispatchMsgType == TDMT_SND_TASK_PIPE_EXEC) {
if (pTask->dispatchMsgType == TDMT_VND_TASK_DISPATCH || pTask->dispatchMsgType == TDMT_SND_TASK_DISPATCH) {
qType = FETCH_QUEUE;
} else if (pTask->dispatchMsgType == TDMT_VND_TASK_MERGE_EXEC ||
pTask->dispatchMsgType == TDMT_SND_TASK_MERGE_EXEC) {
qType = MERGE_QUEUE;
} else if (pTask->dispatchMsgType == TDMT_VND_TASK_WRITE_EXEC) {
qType = WRITE_QUEUE;
/*} else if (pTask->dispatchMsgType == TDMT_VND_TASK_MERGE_EXEC ||*/
/*pTask->dispatchMsgType == TDMT_SND_TASK_MERGE_EXEC) {*/
/*qType = MERGE_QUEUE;*/
/*} else if (pTask->dispatchMsgType == TDMT_VND_TASK_WRITE_EXEC) {*/
/*qType = WRITE_QUEUE;*/
} else {
ASSERT(0);
}

2
source/libs/sync/inc/syncInt.h
View File

@ -182,7 +182,7 @@ int32_t syncNodeSendMsgByInfo(const SNodeInfo* nodeInfo, SSyncNode* pSyncNode, S
cJSON* syncNode2Json(const SSyncNode* pSyncNode);
char* syncNode2Str(const SSyncNode* pSyncNode);
char* syncNode2SimpleStr(const SSyncNode* pSyncNode);
void syncNodeUpdateConfig(SSyncNode* pSyncNode, SSyncCfg* newConfig);
void syncNodeUpdateConfig(SSyncNode* pSyncNode, SSyncCfg* newConfig, bool* isDrop);
SSyncNode* syncNodeAcquire(int64_t rid);
void syncNodeRelease(SSyncNode* pNode);

49
source/libs/sync/src/syncAppendEntries.c
View File

@ -333,7 +333,7 @@ int32_t syncNodeOnAppendEntriesCb(SSyncNode* ths, SyncAppendEntries* pMsg) {
cbMeta.seqNum = pEntry->seqNum;
cbMeta.term = pEntry->term;
cbMeta.currentTerm = ths->pRaftStore->currentTerm;
ths->pFsm->FpCommitCb(ths->pFsm, &rpcMsg, cbMeta);
cbMeta.flag = 0x11;
bool needExecute = true;
if (ths->pSnapshot != NULL && cbMeta.index <= ths->pSnapshot->lastApplyIndex) {
@ -347,24 +347,55 @@ int32_t syncNodeOnAppendEntriesCb(SSyncNode* ths, SyncAppendEntries* pMsg) {
// config change
if (pEntry->originalRpcType == TDMT_VND_SYNC_CONFIG_CHANGE) {
SSyncCfg oldSyncCfg = ths->pRaftCfg->cfg;
SSyncCfg newSyncCfg;
int32_t ret = syncCfgFromStr(rpcMsg.pCont, &newSyncCfg);
ASSERT(ret == 0);
syncNodeUpdateConfig(ths, &newSyncCfg);
if (ths->state == TAOS_SYNC_STATE_LEADER) {
syncNodeBecomeLeader(ths);
} else {
syncNodeBecomeFollower(ths);
// update new config myIndex
bool hit = false;
for (int i = 0; i < newSyncCfg.replicaNum; ++i) {
if (strcmp(ths->myNodeInfo.nodeFqdn, (newSyncCfg.nodeInfo)[i].nodeFqdn) == 0 &&
ths->myNodeInfo.nodePort == (newSyncCfg.nodeInfo)[i].nodePort) {
newSyncCfg.myIndex = i;
hit = true;
break;
}
}
// maybe newSyncCfg.myIndex is updated in syncNodeUpdateConfig
if (ths->pFsm->FpReConfigCb != NULL) {
SReConfigCbMeta cbMeta = {0};
SReConfigCbMeta cbMeta = {0};
bool isDrop;
// I am in newConfig
if (hit) {
syncNodeUpdateConfig(ths, &newSyncCfg, &isDrop);
// change isStandBy to normal
if (!isDrop) {
if (ths->state == TAOS_SYNC_STATE_LEADER) {
syncNodeBecomeLeader(ths);
} else {
syncNodeBecomeFollower(ths);
}
}
char* sOld = syncCfg2Str(&oldSyncCfg);
char* sNew = syncCfg2Str(&newSyncCfg);
sInfo("==config change== 0x11 old:%s new:%s isDrop:%d \n", sOld, sNew, isDrop);
taosMemoryFree(sOld);
taosMemoryFree(sNew);
}
// always call FpReConfigCb
if (ths->pFsm->FpReConfigCb != NULL) {
cbMeta.code = 0;
cbMeta.currentTerm = ths->pRaftStore->currentTerm;
cbMeta.index = pEntry->index;
cbMeta.term = pEntry->term;
cbMeta.oldCfg = oldSyncCfg;
cbMeta.flag = 0x11;
cbMeta.isDrop = isDrop;
ths->pFsm->FpReConfigCb(ths->pFsm, newSyncCfg, cbMeta);
}
}

43
source/libs/sync/src/syncCommit.c
View File

@ -111,6 +111,7 @@ void syncMaybeAdvanceCommitIndex(SSyncNode* pSyncNode) {
cbMeta.seqNum = pEntry->seqNum;
cbMeta.term = pEntry->term;
cbMeta.currentTerm = pSyncNode->pRaftStore->currentTerm;
cbMeta.flag = 0x1;
bool needExecute = true;
if (pSyncNode->pSnapshot != NULL && cbMeta.index <= pSyncNode->pSnapshot->lastApplyIndex) {
@ -124,24 +125,54 @@ void syncMaybeAdvanceCommitIndex(SSyncNode* pSyncNode) {
// config change
if (pEntry->originalRpcType == TDMT_VND_SYNC_CONFIG_CHANGE) {
SSyncCfg oldSyncCfg = pSyncNode->pRaftCfg->cfg;
SSyncCfg newSyncCfg;
int32_t ret = syncCfgFromStr(rpcMsg.pCont, &newSyncCfg);
ASSERT(ret == 0);
syncNodeUpdateConfig(pSyncNode, &newSyncCfg);
if (pSyncNode->state == TAOS_SYNC_STATE_LEADER) {
syncNodeBecomeLeader(pSyncNode);
} else {
syncNodeBecomeFollower(pSyncNode);
// update new config myIndex
bool hit = false;
for (int i = 0; i < newSyncCfg.replicaNum; ++i) {
if (strcmp(pSyncNode->myNodeInfo.nodeFqdn, (newSyncCfg.nodeInfo)[i].nodeFqdn) == 0 &&
pSyncNode->myNodeInfo.nodePort == (newSyncCfg.nodeInfo)[i].nodePort) {
newSyncCfg.myIndex = i;
hit = true;
break;
}
}
// maybe newSyncCfg.myIndex is updated in syncNodeUpdateConfig
if (pSyncNode->state == TAOS_SYNC_STATE_LEADER) {
ASSERT(hit == true);
}
bool isDrop;
syncNodeUpdateConfig(pSyncNode, &newSyncCfg, &isDrop);
// change isStandBy to normal
if (!isDrop) {
if (pSyncNode->state == TAOS_SYNC_STATE_LEADER) {
syncNodeBecomeLeader(pSyncNode);
} else {
syncNodeBecomeFollower(pSyncNode);
}
}
char* sOld = syncCfg2Str(&oldSyncCfg);
char* sNew = syncCfg2Str(&newSyncCfg);
sInfo("==config change== 0x1 old:%s new:%s isDrop:%d \n", sOld, sNew, isDrop);
taosMemoryFree(sOld);
taosMemoryFree(sNew);
if (pSyncNode->pFsm->FpReConfigCb != NULL) {
SReConfigCbMeta cbMeta = {0};
cbMeta.code = 0;
cbMeta.currentTerm = pSyncNode->pRaftStore->currentTerm;
cbMeta.index = pEntry->index;
cbMeta.term = pEntry->term;
cbMeta.oldCfg = oldSyncCfg;
cbMeta.flag = 0x1;
cbMeta.isDrop = isDrop;
pSyncNode->pFsm->FpReConfigCb(pSyncNode->pFsm, newSyncCfg, cbMeta);
}
}

69
source/libs/sync/src/syncMain.c
View File

@ -141,9 +141,38 @@ void syncStop(int64_t rid) {
taosRemoveRef(tsNodeRefId, rid);
}
int32_t syncSetStandby(int64_t rid) {
SSyncNode* pSyncNode = (SSyncNode*)taosAcquireRef(tsNodeRefId, rid);
if (pSyncNode == NULL) {
return -1;
}
if (pSyncNode->state != TAOS_SYNC_STATE_LEADER) {
taosReleaseRef(tsNodeRefId, pSyncNode->rid);
return -1;
}
// state change
pSyncNode->state = TAOS_SYNC_STATE_FOLLOWER;
syncNodeStopHeartbeatTimer(pSyncNode);
// reset elect timer, long enough
int32_t electMS = TIMER_MAX_MS;
int32_t ret = syncNodeRestartElectTimer(pSyncNode, electMS);
ASSERT(ret == 0);
pSyncNode->pRaftCfg->isStandBy = 1;
raftCfgPersist(pSyncNode->pRaftCfg);
taosReleaseRef(tsNodeRefId, pSyncNode->rid);
return 0;
}
int32_t syncReconfig(int64_t rid, const SSyncCfg* pSyncCfg) {
int32_t ret = 0;
char* configChange = syncCfg2Str((SSyncCfg*)pSyncCfg);
sInfo("==syncReconfig== newconfig:%s", configChange);
SRpcMsg rpcMsg = {0};
rpcMsg.msgType = TDMT_VND_SYNC_CONFIG_CHANGE;
rpcMsg.info.noResp = 1;
@ -941,30 +970,19 @@ char* syncNode2SimpleStr(const SSyncNode* pSyncNode) {
int len = 256;
char* s = (char*)taosMemoryMalloc(len);
snprintf(s, len,
"syncNode2SimpleStr vgId:%d currentTerm:%lu, commitIndex:%ld, state:%d %s, electTimerLogicClock:%lu, "
"syncNode2SimpleStr vgId:%d currentTerm:%lu, commitIndex:%ld, state:%d %s, isStandBy:%d, "
"electTimerLogicClock:%lu, "
"electTimerLogicClockUser:%lu, "
"electTimerMS:%d",
pSyncNode->vgId, pSyncNode->pRaftStore->currentTerm, pSyncNode->commitIndex, pSyncNode->state,
syncUtilState2String(pSyncNode->state), pSyncNode->electTimerLogicClock, pSyncNode->electTimerLogicClockUser,
pSyncNode->electTimerMS);
syncUtilState2String(pSyncNode->state), pSyncNode->pRaftCfg->isStandBy, pSyncNode->electTimerLogicClock,
pSyncNode->electTimerLogicClockUser, pSyncNode->electTimerMS);
return s;
}
void syncNodeUpdateConfig(SSyncNode* pSyncNode, SSyncCfg* newConfig) {
bool hit = false;
for (int i = 0; i < newConfig->replicaNum; ++i) {
if (strcmp(pSyncNode->myNodeInfo.nodeFqdn, (newConfig->nodeInfo)[i].nodeFqdn) == 0 &&
pSyncNode->myNodeInfo.nodePort == (newConfig->nodeInfo)[i].nodePort) {
newConfig->myIndex = i;
hit = true;
break;
}
}
ASSERT(hit == true);
void syncNodeUpdateConfig(SSyncNode* pSyncNode, SSyncCfg* newConfig, bool* isDrop) {
pSyncNode->pRaftCfg->cfg = *newConfig;
int32_t ret = raftCfgPersist(pSyncNode->pRaftCfg);
ASSERT(ret == 0);
int32_t ret = 0;
// init internal
pSyncNode->myNodeInfo = pSyncNode->pRaftCfg->cfg.nodeInfo[pSyncNode->pRaftCfg->cfg.myIndex];
@ -994,9 +1012,22 @@ void syncNodeUpdateConfig(SSyncNode* pSyncNode, SSyncCfg* newConfig) {
voteGrantedUpdate(pSyncNode->pVotesGranted, pSyncNode);
votesRespondUpdate(pSyncNode->pVotesRespond, pSyncNode);
pSyncNode->pRaftCfg->isStandBy = 0;
raftCfgPersist(pSyncNode->pRaftCfg);
// isDrop
*isDrop = true;
for (int i = 0; i < newConfig->replicaNum; ++i) {
if (strcmp((newConfig->nodeInfo)[i].nodeFqdn, pSyncNode->myNodeInfo.nodeFqdn) == 0 &&
(newConfig->nodeInfo)[i].nodePort == pSyncNode->myNodeInfo.nodePort) {
*isDrop = false;
break;
}
}
if (!(*isDrop)) {
// change isStandBy to normal
pSyncNode->pRaftCfg->isStandBy = 0;
}
raftCfgPersist(pSyncNode->pRaftCfg);
syncNodeLog2("==syncNodeUpdateConfig==", pSyncNode);
}

43
source/libs/sync/test/syncConfigChangeTest.cpp
View File

@ -43,8 +43,9 @@ void CommitCb(struct SSyncFSM* pFsm, const SRpcMsg* pMsg, SFsmCbMeta cbMeta) {
if (cbMeta.index > beginIndex) {
char logBuf[256];
snprintf(logBuf, sizeof(logBuf), "==callback== ==CommitCb== pFsm:%p, index:%ld, isWeak:%d, code:%d, state:%d %s \n",
pFsm, cbMeta.index, cbMeta.isWeak, cbMeta.code, cbMeta.state, syncUtilState2String(cbMeta.state));
snprintf(logBuf, sizeof(logBuf),
"==callback== ==CommitCb== pFsm:%p, index:%ld, isWeak:%d, code:%d, state:%d %s flag:%lu\n", pFsm,
cbMeta.index, cbMeta.isWeak, cbMeta.code, cbMeta.state, syncUtilState2String(cbMeta.state), cbMeta.flag);
syncRpcMsgLog2(logBuf, (SRpcMsg*)pMsg);
} else {
sTrace("==callback== ==CommitCb== do not apply again %ld", cbMeta.index);
@ -54,15 +55,16 @@ void CommitCb(struct SSyncFSM* pFsm, const SRpcMsg* pMsg, SFsmCbMeta cbMeta) {
void PreCommitCb(struct SSyncFSM* pFsm, const SRpcMsg* pMsg, SFsmCbMeta cbMeta) {
char logBuf[256];
snprintf(logBuf, sizeof(logBuf),
"==callback== ==PreCommitCb== pFsm:%p, index:%ld, isWeak:%d, code:%d, state:%d %s \n", pFsm, cbMeta.index,
cbMeta.isWeak, cbMeta.code, cbMeta.state, syncUtilState2String(cbMeta.state));
"==callback== ==PreCommitCb== pFsm:%p, index:%ld, isWeak:%d, code:%d, state:%d %s flag:%lu\n", pFsm,
cbMeta.index, cbMeta.isWeak, cbMeta.code, cbMeta.state, syncUtilState2String(cbMeta.state), cbMeta.flag);
syncRpcMsgLog2(logBuf, (SRpcMsg*)pMsg);
}
void RollBackCb(struct SSyncFSM* pFsm, const SRpcMsg* pMsg, SFsmCbMeta cbMeta) {
char logBuf[256];
snprintf(logBuf, sizeof(logBuf), "==callback== ==RollBackCb== pFsm:%p, index:%ld, isWeak:%d, code:%d, state:%d %s \n",
pFsm, cbMeta.index, cbMeta.isWeak, cbMeta.code, cbMeta.state, syncUtilState2String(cbMeta.state));
snprintf(logBuf, sizeof(logBuf),
"==callback== ==RollBackCb== pFsm:%p, index:%ld, isWeak:%d, code:%d, state:%d %s flag:%lu\n", pFsm,
cbMeta.index, cbMeta.isWeak, cbMeta.code, cbMeta.state, syncUtilState2String(cbMeta.state), cbMeta.flag);
syncRpcMsgLog2(logBuf, (SRpcMsg*)pMsg);
}
@ -75,13 +77,23 @@ int32_t GetSnapshotCb(struct SSyncFSM* pFsm, SSnapshot* pSnapshot) {
void RestoreFinishCb(struct SSyncFSM* pFsm) { sTrace("==callback== ==RestoreFinishCb=="); }
void ReConfigCb(struct SSyncFSM* pFsm, SSyncCfg newCfg, SReConfigCbMeta cbMeta) {
sTrace("==callback== ==ReConfigCb== flag:0x%lX, isDrop:%d, index:%ld, code:%d, currentTerm:%lu, term:%lu", cbMeta.flag, cbMeta.isDrop, cbMeta.index, cbMeta.code, cbMeta.currentTerm, cbMeta.term);
}
SSyncFSM* createFsm() {
SSyncFSM* pFsm = (SSyncFSM*)taosMemoryMalloc(sizeof(SSyncFSM));
pFsm->FpCommitCb = CommitCb;
pFsm->FpPreCommitCb = PreCommitCb;
pFsm->FpRollBackCb = RollBackCb;
pFsm->FpGetSnapshot = GetSnapshotCb;
pFsm->FpRestoreFinishCb = RestoreFinishCb;
pFsm->FpSnapshotApply = NULL;
pFsm->FpSnapshotRead = NULL;
pFsm->FpReConfigCb = ReConfigCb;
return pFsm;
}
@ -109,6 +121,7 @@ int64_t createSyncNode(int32_t replicaNum, int32_t myIndex, int32_t vgId, SWal*
syncInfo.pFsm = createFsm();
snprintf(syncInfo.path, sizeof(syncInfo.path), "%s_sync_replica%d_index%d", path, replicaNum, myIndex);
syncInfo.pWal = pWal;
syncInfo.isStandBy = isStandBy;
SSyncCfg* pCfg = &syncInfo.syncCfg;
@ -180,7 +193,7 @@ SRpcMsg* createRpcMsg(int i, int count, int myIndex) {
int main(int argc, char** argv) {
tsAsyncLog = 0;
sDebugFlag = DEBUG_TRACE + DEBUG_SCREEN + DEBUG_FILE;
sDebugFlag = DEBUG_TRACE + DEBUG_SCREEN + DEBUG_FILE + DEBUG_INFO;
if (argc != 7) {
usage(argv[0]);
exit(-1);
@ -212,17 +225,21 @@ int main(int argc, char** argv) {
int64_t rid = createSyncNode(replicaNum, myIndex, gVgId, pWal, (char*)gDir, isStandBy);
assert(rid > 0);
if (isStandBy) {
syncStartStandBy(rid);
} else {
syncStart(rid);
}
syncStart(rid);
/*
if (isStandBy) {
syncStartStandBy(rid);
} else {
syncStart(rid);
}
*/
SSyncNode* pSyncNode = (SSyncNode*)syncNodeAcquire(rid);
assert(pSyncNode != NULL);
if (isConfigChange) {
configChange(rid, 3, myIndex);
configChange(rid, 2, myIndex);
}
//---------------------------

1
source/libs/transport/inc/transComm.h
View File

@ -318,6 +318,7 @@ void transDQDestroy(SDelayQueue* queue);
int transDQSched(SDelayQueue* queue, void (*func)(void* arg), void* arg, uint64_t timeoutMs);
void transPrintEpSet(SEpSet* pEpSet);
/*
* init global func
*/

13
source/libs/transport/src/transCli.c
View File

@ -921,16 +921,19 @@ int cliAppCb(SCliConn* pConn, STransMsg* pResp, SCliMsg* pMsg) {
STransConnCtx* pCtx = pMsg->ctx;
SEpSet* pEpSet = &pCtx->epSet;
transPrintEpSet(pEpSet);
/*
* upper layer handle retry if code equal TSDB_CODE_RPC_NETWORK_UNAVAIL
*/
tmsg_t msgType = pCtx->msgType;
if ((pTransInst->retry != NULL && (pTransInst->retry(pResp->code))) ||
((pResp->code == TSDB_CODE_RPC_NETWORK_UNAVAIL) && msgType == TDMT_MND_CONNECT)) {
(pResp->code == TSDB_CODE_RPC_NETWORK_UNAVAIL || pResp->code == TSDB_CODE_APP_NOT_READY ||
pResp->code == TSDB_CODE_NODE_NOT_DEPLOYED || pResp->code == TSDB_CODE_SYN_NOT_LEADER)) {
pMsg->sent = 0;
pMsg->st = taosGetTimestampUs();
pCtx->retryCount += 1;
if (msgType == TDMT_MND_CONNECT && pResp->code == TSDB_CODE_RPC_NETWORK_UNAVAIL) {
if (pResp->code == TSDB_CODE_RPC_NETWORK_UNAVAIL) {
if (pCtx->retryCount < pEpSet->numOfEps) {
pEpSet->inUse = (++pEpSet->inUse) % pEpSet->numOfEps;
@ -972,7 +975,11 @@ int cliAppCb(SCliConn* pConn, STransMsg* pResp, SCliMsg* pMsg) {
pCtx->pRsp = NULL;
} else {
tTrace("%s cli conn %p handle resp", pTransInst->label, pConn);
pTransInst->cfp(pTransInst->parent, pResp, pEpSet);
if (pResp->code != 0) {
pTransInst->cfp(pTransInst->parent, pResp, NULL);
} else {
pTransInst->cfp(pTransInst->parent, pResp, pEpSet);
}
}
return 0;
}

12
source/libs/transport/src/transComm.c
View File

@ -446,4 +446,16 @@ int transDQSched(SDelayQueue* queue, void (*func)(void* arg), void* arg, uint64_
uv_timer_start(queue->timer, transDQTimeout, timeoutMs, 0);
return 0;
}
void transPrintEpSet(SEpSet* pEpSet) {
if (pEpSet == NULL) {
tTrace("NULL epset");
return;
}
tTrace("epset begin: inUse: %d", pEpSet->inUse);
for (int i = 0; i < pEpSet->numOfEps; i++) {
tTrace("ip: %s, port: %d", pEpSet->eps[i].fqdn, pEpSet->eps[i].port);
}
tTrace("epset end");
}
#endif

2
tests/script/jenkins/basic.txt
View File

@ -56,7 +56,7 @@
# ---- mnode
#./test.sh -f tsim/mnode/basic1.sim
#./test.sh -f tsim/mnode/basic2.sim
./test.sh -f tsim/mnode/basic2.sim
# ---- show
./test.sh -f tsim/show/basic.sim

149
tests/script/tsim/mnode/basic1.sim
View File

@ -6,15 +6,6 @@ system sh/exec.sh -n dnode2 -s start
sql connect
print =============== show dnodes
sql show dnodes;
if $rows != 1 then
return -1
endi
if $data00 != 1 then
return -1
endi
sql show mnodes;
if $rows != 1 then
return -1
@ -30,63 +21,55 @@ endi
print =============== create dnodes
sql create dnode $hostname port 7200
sleep 2000
sql show dnodes;
if $rows != 2 then
return -1
$x = 0
step1:
$x = $x + 1
sleep 500
if $x == 20 then
return -1
endi
sql show dnodes -x step1
if $data(1)[4] != ready then
goto step1
endi
if $data00 != 1 then
return -1
endi
if $data10 != 2 then
return -1
endi
print $data02
if $data02 != 0 then
return -1
endi
if $data12 != 0 then
return -1
endi
if $data04 != ready then
return -1
endi
if $data14 != ready then
return -1
endi
sql show mnodes;
if $rows != 1 then
return -1
endi
if $data00 != 1 then
return -1
endi
if $data02 != LEADER then
return -1
if $data(2)[4] != ready then
goto step1
endi
print =============== create drop mnode 1
sql_error create mnode on dnode 1
sql_error drop mnode on dnode 1
print =============== create drop mnode 2
sql create mnode on dnode 2
$x = 0
step1:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
if $rows != 2 then
return -1
endi
sql_error create mnode on dnode 2
if $data(1)[0] != 1 then
return -1
endi
if $data(1)[2] != LEADER then
return -1
endi
if $data(2)[0] != 2 then
return -1
endi
if $data(2)[2] != FOLLOWER then
goto step1
endi
sleep 2000
print ============ drop mnodes
sql drop mnode on dnode 2
sql show mnodes
if $rows != 1 then
@ -94,6 +77,35 @@ if $rows != 1 then
endi
sql_error drop mnode on dnode 2
$x = 0
step2:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
if $rows != 2 then
return -1
endi
if $data(1)[0] != 1 then
return -1
endi
if $data(1)[2] != LEADER then
return -1
endi
if $data(2)[0] != NULL then
goto step2
endi
if $data(2)[2] != NULL then
goto step2
endi
sleep 2000
print =============== create drop mnodes
sql create mnode on dnode 2
sql show mnodes
@ -101,17 +113,32 @@ if $rows != 2 then
return -1
endi
print =============== restart
system sh/exec.sh -n dnode1 -s stop -x SIGINT
system sh/exec.sh -n dnode2 -s stop -x SIGINT
system sh/exec.sh -n dnode1 -s start
system sh/exec.sh -n dnode2 -s start
sleep 2000
$x = 0
step3:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
if $rows != 2 then
return -1
endi
if $data(1)[0] != 1 then
return -1
endi
if $data(1)[2] != LEADER then
return -1
endi
if $data(2)[0] != 2 then
return -1
endi
if $data(2)[2] != FOLLOWER then
goto step3
endi
system sh/exec.sh -n dnode1 -s stop -x SIGINT
system sh/exec.sh -n dnode2 -s stop -x SIGINT

91
tests/script/tsim/mnode/basic2.sim
View File

@ -21,29 +21,31 @@ endi
print =============== create dnodes
sql create dnode $hostname port 7200
sql create dnode $hostname port 7300
sleep 2000
sql show dnodes;
if $rows != 3 then
return -1
$x = 0
step1:
$x = $x + 1
sleep 500
if $x == 20 then
return -1
endi
sql show dnodes -x step1
if $data(1)[4] != ready then
goto step1
endi
sql show mnodes;
if $rows != 1 then
return -1
endi
if $data00 != 1 then
return -1
endi
if $data02 != LEADER then
return -1
if $data(2)[4] != ready then
goto step1
endi
print =============== create mnode 2
sql create mnode on dnode 2
$x = 0
step2:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
@ -60,8 +62,8 @@ endi
if $data(2)[0] != 2 then
return -1
endi
if $data(2)[2] == LEADER then
return -1
if $data(2)[2] != FOLLOWER then
goto step2
endi
print =============== create user
@ -71,42 +73,55 @@ if $rows != 2 then
return -1
endi
#sql create database db
#sql show databases
#if $rows != 3 then
# return -1
#endi
sql create database db
sql show databases
if $rows != 3 then
return -1
endi
sleep 5000
print =============== restart
system sh/exec.sh -n dnode1 -s stop
system sh/exec.sh -n dnode2 -s stop
sleep 100
system sh/exec.sh -n dnode1 -s start
system sh/exec.sh -n dnode2 -s start
sql connect
sql show mnodes
if $rows != 2 then
return -1
endi
if $data(1)[0] != 1 then
return -1
endi
if $data(1)[2] != LEADER then
return -1
endi
sql show users
if $rows != 2 then
return -1
endi
#sql show databases
#if $rows != 3 then
# return -1
#endi
sql show databases
if $rows != 3 then
return -1
endi
return
$x = 0
step3:
$x = $x + 1
sleep 500
if $x == 20 then
return -1
endi
sql show dnodes -x step3
if $data(1)[4] != ready then
goto step3
endi
if $data(2)[4] != ready then
goto step3
endi
print =============== insert data
#sql create table db.stb (ts timestamp, c1 int, c2 binary(4)) tags(t1 int, t2 float, t3 binary(16)) comment "abd"
#sql create table db.ctb using db.stb tags(101, 102, "103")
#sql insert into db.ctb values(now, 1, "2")
system sh/exec.sh -n dnode1 -s stop
system sh/exec.sh -n dnode2 -s stop

137
tests/script/tsim/mnode/basic3.sim Normal file
View File

@ -0,0 +1,137 @@
system sh/stop_dnodes.sh
system sh/deploy.sh -n dnode1 -i 1
system sh/deploy.sh -n dnode2 -i 2
system sh/deploy.sh -n dnode3 -i 3
system sh/exec.sh -n dnode1 -s start
system sh/exec.sh -n dnode2 -s start
system sh/exec.sh -n dnode3 -s start
sql connect
print =============== step1: create dnodes
sql create dnode $hostname port 7200
sql create dnode $hostname port 7300
$x = 0
step1:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show dnodes -x step1
if $data(1)[4] != ready then
goto step1
endi
if $data(2)[4] != ready then
goto step1
endi
if $data(3)[4] != ready then
goto step1
endi
print =============== step2: create mnode 2
sql create mnode on dnode 2
sql create mnode on dnode 3
$x = 0
step2:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes -x step2
if $data(1)[2] != LEADER then
goto step2
endi
if $data(2)[2] != FOLLOWER then
goto step2
endi
if $data(3)[2] != FOLLOWER then
goto step2
endi
print =============== step3: create user
sql create user user1 PASS 'user1'
sql show users
if $rows != 2 then
return -1
endi
# wait mnode2 mnode3 recv data finish
sleep 10000
print =============== step4: stop dnode1
system sh/exec.sh -n dnode1 -s stop
$x = 0
step4:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes -x step4
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
print $data(3)[0] $data(3)[1] $data(3)[2]
sql show users
if $rows != 2 then
return -1
endi
sleep 1000
sql show dnodes
if $data(2)[4] != ready then
return -1
endi
if $data(3)[4] != ready then
return -1
endi
print =============== step5: stop dnode1
system sh/exec.sh -n dnode1 -s start
system sh/exec.sh -n dnode2 -s stop
$x = 0
step5:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes -x step5
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
print $data(3)[0] $data(3)[1] $data(3)[2]
sql show users
if $rows != 2 then
return -1
endi
print =============== step6: stop dnode1
system sh/exec.sh -n dnode2 -s start
system sh/exec.sh -n dnode3 -s stop
$x = 0
step6:
$x = $x + 1
sleep 1000
if $x == 20 then
return -1
endi
sql show mnodes -x step6
print $data(1)[0] $data(1)[1] $data(1)[2]
print $data(2)[0] $data(2)[1] $data(2)[2]
print $data(3)[0] $data(3)[1] $data(3)[2]
sql show users
if $rows != 2 then
return -1
endi
system sh/exec.sh -n dnode1 -s stop
system sh/exec.sh -n dnode2 -s stop
system sh/exec.sh -n dnode3 -s stop