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TDengine
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# 贡献指南
我们感谢所有开发者提交贡献。随时关注我们，Fork 存储库，报告错误，以及在 GitHub 上提交您的代码。但是，我们希望开发者遵循我们的指南，才能更好的做出贡献。
## 报告错误
- 任何用户都可以通过 **[GitHub issue tracker](https://github.com/taosdata/TDengine/issues)** 向我们报告错误。请您对所遇到的问题进行**详细描述**，最好提供重现错误的详细步骤。
- 欢迎提供包含由 Bug 生成的日志文件的附录。
## 需要强调的代码提交规则
- 在提交代码之前，需要**同意贡献者许可协议（CLA）**。点击 [TaosData CLA](https://cla-assistant.io/taosdata/TDengine) 阅读并签署协议。如果您不接受该协议，请停止提交。
- 请在 [GitHub issue tracker](https://github.com/taosdata/TDengine/issues) 中解决问题或添加注册功能。
- 如果在 [GitHub issue tracker](https://github.com/taosdata/TDengine/issues) 中没有找到相应的问题或功能，请**创建一个新的 issue**。
- 将代码提交到我们的存储库时，请创建**包含问题编号的 PR**。
## 贡献指南
1. 请用友好的语气书写。
2. **主动语态**总体上优于被动语态。主动语态中的句子会突出执行动作的人，而不是被动语态突出动作的接受者。
3. 文档写作建议
- 正确拼写产品名称 “TDengine”。 “TD” 用大写字母，“TD” 和 “engine” 之间没有空格 **（正确拼写：TDengine）**。
- 在句号或其他标点符号后只留一个空格。
4. 尽量**使用简单句**，而不是复杂句。
## 给贡献者的礼品
只要您是为 TDengine 做贡献的开发者，不管是代码贡献、修复 bug 或功能请求，还是文档更改，您都将会获得一份**特别的贡献者纪念品礼物**！
<p align="left">
<img
src="docs/assets/contributing-cup.jpg"
alt=""
width="200"
/>
<img
src="docs/assets/contributing-notebook.jpg"
alt=""
width="200"
/>
<img
src="docs/assets/contributing-shirt.jpg"
alt=""
width="200"
/>
TDengine 社区致力于让更多的开发者理解和使用它。
请填写**贡献者提交表**以选择您想收到的礼物。
- [贡献者提交表](https://page.ma.scrmtech.com/form/index?pf_uid=27715_2095&id=12100)
## 联系我们
如果您有什么问题需要解决，或者有什么问题需要解答，可以添加微信：TDengineECO
CONTRIBUTING.md
浏览文件 @ fece844f
# Contributing
We appreciate contributions from all developers. Feel free to follow us, fork the repository, report bugs and even submit your code on GitHub. However, we would like developers to follow our guides to contribute for better corporation.
We appreciate contributions from all developers. Feel free to follow us, fork the repository, report bugs, and even submit your code on GitHub. However, we would like developers to follow the guidelines in this document to ensure effective cooperation.
## Report bugs
## Reporting a bug
Any users can report bugs to us through the [github issue tracker](https://github.com/taosdata/TDengine/issues). We appreciate a detailed description of the problem you met. It is better to provide the detailed steps on reproducing the bug. Otherwise, an appendix with log files generated by the bug is welcome.
- Any users can report bugs to us through the **[GitHub issue tracker](https://github.com/taosdata/TDengine/issues)**. We would appreciate if you could provide **a detailed description** of the problem you encountered, including steps to reproduce it.
## Read the contributor license agreement
- Attaching log files caused by the bug is really appreciated.
It is required to agree the Contributor Licence Agreement(CLA) before a user submitting his/her code patch. Follow the [TaosData CLA](https://www.taosdata.com/en/contributor/) link to read through the agreement.
## Guidelines for committing code
## Submit your code
- You must agree to the **Contributor License Agreement(CLA) before submitting your code patch**. Follow the **[TAOSData CLA](https://cla-assistant.io/taosdata/TDengine)** link to read through and sign the agreement. If you do not accept the agreement, your contributions cannot be accepted.
Before submitting your code, make sure to [read the contributor license agreement](#read-the-contributor-license-agreement) beforehand. If you don't accept the aggreement, please stop submitting. Your submission means you have accepted the agreement. Your submission should solve an issue or add a feature registered in the [github issue tracker](https://github.com/taosdata/TDengine/issues). If no corresponding issue or feature is found in the issue tracker, please create one. When submitting your code to our repository, please create a pull request with the issue number included.
- Please solve an issue or add a feature registered in the **[GitHub issue tracker](https://github.com/taosdata/TDengine/issues)**.
- If no corresponding issue or feature is found in the issue tracker, please **create one**.
- When submitting your code to our repository, please create a pull request with the **issue number** included.
## Guidelines for communicating
1. Please be **nice and polite** in the description.
2. **Active voice is better than passive voice in general**. Sentences in the active voice will highlight who is performing the action rather than the recipient of the action highlighted by the passive voice.
3. Documentation writing advice
- Spell the product name "TDengine" correctly. "TD" is written in capital letters, and there is no space between "TD" and "engine" (**Correct spelling: TDengine**).
- Please **capitalize the first letter** of every sentence.
- Leave **only one space** after periods or other punctuation marks.
- Use **American spelling**.
- When possible, **use second person** rather than first person (e.g.“You are recommended to use a reverse proxy such as Nginx.” rather than “We recommend to use a reverse proxy such as Nginx.”).
5. Use **simple sentences**, rather than complex sentences.
## Gifts for the contributors
Developers, as long as you contribute to TDengine, whether it's code contributions to fix bugs or feature requests, or documentation changes, **you are eligible for a very special Contributor Souvenir Gift!**
**You can choose one of the following gifts:**
<p align="left">
<img
src="docs/assets/contributing-cup.jpg"
alt=""
width="200"
/>
<img
src="docs/assets/contributing-notebook.jpg"
alt=""
width="200"
/>
<img
src="docs/assets/contributing-shirt.jpg"
alt=""
width="200"
/>
The TDengine community is committed to making TDengine accepted and used by more developers.
Just fill out the **Contributor Submission Form** to choose your desired gift.
- [Contributor Submission Form](https://page.ma.scrmtech.com/form/index?pf_uid=27715_2095&id=12100)
## Contact us
If you have any problems or questions that need help from us, please feel free to add our WeChat account: TDengineECO.
Jenkinsfile2
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import hudson.model.Result
import hudson.model.*;
import jenkins.model.CauseOfInterruption
docs_only=0
node {
}
......@@ -29,6 +30,48 @@ def abort_previous(){
if (buildNumber > 1) milestone(buildNumber - 1)
milestone(buildNumber)
}
def check_docs() {
if (env.CHANGE_URL =~ /\/TDengine\//) {
sh '''
hostname
date
env
'''
sh '''
cd ${WKC}
git reset --hard
git clean -fxd
rm -rf examples/rust/
git remote prune origin
git fetch
'''
script {
sh '''
cd ${WKC}
git checkout ''' + env.CHANGE_TARGET + '''
'''
}
sh '''
cd ${WKC}
git pull >/dev/null
git fetch origin +refs/pull/${CHANGE_ID}/merge
git checkout -qf FETCH_HEAD
'''
def file_changed = sh (
script: '''
cd ${WKC}
git --no-pager diff --name-only FETCH_HEAD `git merge-base FETCH_HEAD ${CHANGE_TARGET}`|grep -v "^docs/en/"|grep -v "^docs/zh/" || :
''',
returnStdout: true
).trim()
if (file_changed == '') {
echo "docs PR"
docs_only=1
} else {
echo file_changed
}
}
}
def pre_test(){
sh '''
hostname
......@@ -307,10 +350,27 @@ pipeline {
WKPY = '/var/lib/jenkins/workspace/taos-connector-python'
}
stages {
stage('check') {
when {
allOf {
not { expression { env.CHANGE_BRANCH =~ /docs\// }}
not { expression { env.CHANGE_URL =~ /\/TDinternal\// }}
}
}
parallel {
stage('check docs') {
agent{label " worker03 || slave215 || slave217 || slave219 || Mac_catalina "}
steps {
check_docs()
}
}
}
}
stage('run test') {
when {
allOf {
not { expression { env.CHANGE_BRANCH =~ /docs\// }}
expression { docs_only == 0 }
}
}
parallel {
......
README-CN.md
浏览文件 @ fece844f
......@@ -210,14 +210,14 @@ cmake .. -G "NMake Makefiles"
nmake
```
### macOS 系统
<!-- ### macOS 系统
安装 Xcode 命令行工具和 cmake. 在 Catalina 和 Big Sur 操作系统上，需要安装 XCode 11.4+ 版本。
```bash
mkdir debug && cd debug
cmake .. && cmake --build .
```
``` -->
# 安装
......
README.md
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......@@ -15,7 +15,6 @@
[![Coverage Status](https://coveralls.io/repos/github/taosdata/TDengine/badge.svg?branch=develop)](https://coveralls.io/github/taosdata/TDengine?branch=develop)
[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/4201/badge)](https://bestpractices.coreinfrastructure.org/projects/4201)
English | [简体中文](README-CN.md) | We are hiring, check [here](https://tdengine.com/careers)
# What is TDengine？
......@@ -42,7 +41,7 @@ For user manual, system design and architecture, please refer to [TDengine Docum
At the moment, TDengine server supports running on Linux, Windows systems.Any OS application can also choose the RESTful interface of taosAdapter to connect the taosd service . TDengine supports X64/ARM64 CPU , and it will support MIPS64, Alpha64, ARM32, RISC-V and other CPU architectures in the future.
You can choose to install through source code according to your needs, [container](https://docs.taosdata.com/get-started/docker/), [installation package](https://docs.taosdata.com/get-started/package/) or [Kubenetes](https://docs.taosdata.com/deployment/k8s/) to install. This quick guide only applies to installing from source.
You can choose to install through source code according to your needs, [container](https://docs.taosdata.com/get-started/docker/), [installation package](https://docs.taosdata.com/get-started/package/) or [Kubernetes](https://docs.taosdata.com/deployment/k8s/) to install. This quick guide only applies to installing from source.
TDengine provide a few useful tools such as taosBenchmark (was named taosdemo) and taosdump. They were part of TDengine. By default, TDengine compiling does not include taosTools. You can use `cmake .. -DBUILD_TOOLS=true` to make them be compiled with TDengine.
......@@ -58,7 +57,6 @@ sudo apt-get install -y gcc cmake build-essential git libssl-dev
#### Install build dependencies for taosTools
To build the [taosTools](https://github.com/taosdata/taos-tools) on Ubuntu/Debian, the following packages need to be installed.
```bash
......@@ -82,14 +80,13 @@ sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel
#### Install build dependencies for taosTools on CentOS
#### CentOS 7.9
```
sudo yum install -y zlib-devel xz-devel snappy-devel jansson jansson-devel pkgconfig libatomic libstdc++-static openssl-devel
```
#### CentOS 8/Rocky Linux
#### CentOS 8/Rocky Linux
```
sudo yum install -y epel-release
......@@ -100,14 +97,14 @@ sudo yum install -y zlib-devel xz-devel snappy-devel jansson jansson-devel pkgco
Note: Since snappy lacks pkg-config support (refer to [link](https://github.com/google/snappy/pull/86)), it leads a cmake prompt libsnappy not found. But snappy still works well.
If the powertools installation fails, you can try to use:
If the PowerTools installation fails, you can try to use:
```
sudo yum config-manager --set-enabled Powertools
sudo yum config-manager --set-enabled powertools
```
### Setup golang environment
TDengine includes a few components like taosAdapter developed by Go language. Please refer to golang.org official documentation for golang environment setup.
Please use version 1.14+. For the user in China, we recommend using a proxy to accelerate package downloading.
......@@ -125,7 +122,7 @@ cmake .. -DBUILD_HTTP=false
### Setup rust environment
TDengine includes a few compoments developed by Rust language. Please refer to rust-lang.org official documentation for rust environment setup.
TDengine includes a few components developed by Rust language. Please refer to rust-lang.org official documentation for rust environment setup.
## Get the source codes
......@@ -136,7 +133,6 @@ git clone https://github.com/taosdata/TDengine.git
cd TDengine
```
You can modify the file ~/.gitconfig to use ssh protocol instead of https for better download speed. You will need to upload ssh public key to GitHub first. Please refer to GitHub official documentation for detail.
```
......@@ -146,14 +142,12 @@ You can modify the file ~/.gitconfig to use ssh protocol instead of https for be
## Special Note
[JDBC Connector](https://github.com/taosdata/taos-connector-jdbc)， [Go Connector](https://github.com/taosdata/driver-go)，[Python Connector](https://github.com/taosdata/taos-connector-python)，[Node.js Connector](https://github.com/taosdata/taos-connector-node)，[C# Connector](https://github.com/taosdata/taos-connector-dotnet) ，[Rust Connector](https://github.com/taosdata/taos-connector-rust) and [Grafana plugin](https://github.com/taosdata/grafanaplugin) has been moved to standalone repository.
## Build TDengine
### On Linux platform
You can run the bash script `build.sh` to build both TDengine and taosTools including taosBenchmark and taosdump as below:
```bash
......@@ -169,7 +163,6 @@ cmake .. -DBUILD_TOOLS=true
make
```
You can use Jemalloc as memory allocator instead of glibc:
```
......@@ -218,14 +211,14 @@ cmake .. -G "NMake Makefiles"
nmake
```
### On macOS platform
<!-- ### On macOS platform
Please install XCode command line tools and cmake. Verified with XCode 11.4+ on Catalina and Big Sur.
```shell
mkdir debug && cd debug
cmake .. && cmake --build .
```
``` -->
# Installing
......@@ -237,7 +230,7 @@ After building successfully, TDengine can be installed by
sudo make install
```
Users can find more information about directories installed on the system in the [directory and files](https://docs.taosdata.com/reference/directory/) section.
Users can find more information about directories installed on the system in the [directory and files](https://docs.taosdata.com/reference/directory/) section.
Installing from source code will also configure service management for TDengine.Users can also choose to [install from packages](https://docs.taosdata.com/get-started/package/) for it.
......@@ -309,7 +302,7 @@ Query OK, 2 row(s) in set (0.001700s)
## Official Connectors
TDengine provides abundant developing tools for users to develop on TDengine. include C/C++、Java、Python、Go、Node.js、C# 、RESTful ,Follow the links below to find your desired connectors and relevant documentation.
TDengine provides abundant developing tools for users to develop on TDengine. Follow the links below to find your desired connectors and relevant documentation.
- [Java](https://docs.taosdata.com/reference/connector/java/)
- [C/C++](https://docs.taosdata.com/reference/connector/cpp/)
......
cmake/cmake.version
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......@@ -2,7 +2,7 @@
IF (DEFINED VERNUMBER)
SET(TD_VER_NUMBER ${VERNUMBER})
ELSE ()
SET(TD_VER_NUMBER "3.0.0.0")
SET(TD_VER_NUMBER "3.0.0.1")
ENDIF ()
IF (DEFINED VERCOMPATIBLE)
......
cmake/libuv_CMakeLists.txt.in
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......@@ -2,7 +2,7 @@
# libuv
ExternalProject_Add(libuv
GIT_REPOSITORY https://github.com/libuv/libuv.git
GIT_TAG v1.42.0
GIT_TAG v1.44.2
SOURCE_DIR "${TD_CONTRIB_DIR}/libuv"
BINARY_DIR "${TD_CONTRIB_DIR}/libuv"
CONFIGURE_COMMAND ""
......
cmake/taostools_CMakeLists.txt.in
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......@@ -2,7 +2,7 @@
# taos-tools
ExternalProject_Add(taos-tools
GIT_REPOSITORY https://github.com/taosdata/taos-tools.git
GIT_TAG d237772
GIT_TAG 6bde102
SOURCE_DIR "${TD_SOURCE_DIR}/tools/taos-tools"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE
......
docs/en/01-index.md
浏览文件 @ fece844f
......@@ -13,7 +13,7 @@ TDengine greatly improves the efficiency of data ingestion, querying and storage
If you are a developer, please read the [“Developer Guide”](./develop) carefully. This section introduces the database connection, data modeling, data ingestion, query, continuous query, cache, data subscription, user-defined functions, and other functionality in detail. Sample code is provided for a variety of programming languages. In most cases, you can just copy and paste the sample code, make a few changes to accommodate your application, and it will work.
We live in the era of big data, and scale-up is unable to meet the growing needs of business. Any modern data system must have the ability to scale out, and clustering has become an indispensable feature of big data systems. Not only did the TDengine team develop the cluster feature, but also decided to open source this important feature. To learn how to deploy, manage and maintain a TDengine cluster please refer to ["cluster"](./cluster).
We live in the era of big data, and scale-up is unable to meet the growing needs of business. Any modern data system must have the ability to scale out, and clustering has become an indispensable feature of big data systems. Not only did the TDengine team develop the cluster feature, but also decided to open source this important feature. To learn how to deploy, manage and maintain a TDengine cluster please refer to ["cluster deployment"](../deployment).
TDengine uses ubiquitious SQL as its query language, which greatly reduces learning costs and migration costs. In addition to the standard SQL, TDengine has extensions to better support time series data analysis. These extensions include functions such as roll up, interpolation and time weighted average, among many others. The ["SQL Reference"](./taos-sql) chapter describes the SQL syntax in detail, and lists the various supported commands and functions.
......
docs/en/02-intro/index.md
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......@@ -3,7 +3,7 @@ title: Introduction
toc_max_heading_level: 2
---
TDengine is an open source, high-performance, cloud native time-series database optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. Its code, including its cluster feature is open source under GNU AGPL v3.0. Besides the database engine, it provides [caching](/develop/cache), [stream processing](/develop/continuous-query), [data subscription](/develop/subscribe) and other functionalities to reduce the system complexity and cost of development and operation.
TDengine is an open source, high-performance, cloud native time-series database optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. Its code, including its cluster feature is open source under GNU AGPL v3.0. Besides the database engine, it provides [caching](../develop/cache), [stream processing](../develop/stream), [data subscription](../develop/tmq) and other functionalities to reduce the system complexity and cost of development and operation.
This section introduces the major features, competitive advantages, typical use-cases and benchmarks to help you get a high level overview of TDengine.
......@@ -16,9 +16,9 @@ The major features are listed below:
3. Support for [all kinds of queries](/develop/query-data), including aggregation, nested query, downsampling, interpolation and others.
4. Support for [user defined functions](/develop/udf).
5. Support for [caching](/develop/cache). TDengine always saves the last data point in cache, so Redis is not needed in some scenarios.
6. Support for [continuous query](/develop/continuous-query).
7. Support for [data subscription](/develop/subscribe) with the capability to specify filter conditions.
8. Support for [cluster](/cluster/), with the capability of increasing processing power by adding more nodes. High availability is supported by replication.
6. Support for [continuous query](../develop/stream).
7. Support for [data subscription](../develop/tmq) with the capability to specify filter conditions.
8. Support for [cluster](../deployment/), with the capability of increasing processing power by adding more nodes. High availability is supported by replication.
9. Provides an interactive [command-line interface](/reference/taos-shell) for management, maintenance and ad-hoc queries.
10. Provides many ways to [import](/operation/import) and [export](/operation/export) data.
11. Provides [monitoring](/operation/monitor) on running instances of TDengine.
......@@ -43,7 +43,7 @@ By making full use of [characteristics of time series data](https://tdengine.com
- **Easy Data Analytics**: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way.
- **Open Source**: TDengine’s core modules, including cluster feature, are all available under open source licenses. It has gathered 18.8k stars on GitHub. There is an active developer community, and over 139k running instances worldwide.
- **Open Source**: TDengine’s core modules, including cluster feature, are all available under open source licenses. It has gathered over 19k stars on GitHub. There is an active developer community, and over 140k running instances worldwide.
With TDengine, the total cost of ownership of your time-series data platform can be greatly reduced. 1: With its superior performance, the computing and storage resources are reduced significantly；2: With SQL support, it can be seamlessly integrated with many third party tools, and learning costs/migration costs are reduced significantly；3: With its simplified solution and nearly zero management, the operation and maintenance costs are reduced significantly.
......
docs/en/05-get-started/01-docker.md
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......@@ -31,17 +31,6 @@ You can now access TDengine or run other Linux commands.
Note: For information about installing docker, see the [official documentation](https://docs.docker.com/get-docker/).
## Open the TDengine CLI
On the container, run the following command to open the TDengine CLI:
```
$ taos
taos>
```
## Insert Data into TDengine
You can use the `taosBenchmark` tool included with TDengine to write test data into your deployment.
......@@ -59,39 +48,51 @@ To do so, run the following command:
You can customize the test deployment that taosBenchmark creates by specifying command-line parameters. For information about command-line parameters, run the `taosBenchmark --help` command. For more information about taosBenchmark, see [taosBenchmark](/reference/taosbenchmark).
## Open the TDengine CLI
On the container, run the following command to open the TDengine CLI:
```
$ taos
taos>
```
## Query Data in TDengine
After using taosBenchmark to create your test deployment, you can run queries in the TDengine CLI to test its performance. For example:
Query the number of rows in the `meters` supertable:
From the TDengine CLI query the number of rows in the `meters` supertable:
```sql
taos> select count(*) from test.meters;
select count(*) from test.meters;
```
Query the average, maximum, and minimum values of all 100 million rows of data:
```sql
taos> select avg(current), max(voltage), min(phase) from test.meters;
select avg(current), max(voltage), min(phase) from test.meters;
```
Query the number of rows whose `location` tag is `California.SanFrancisco`:
Query the number of rows whose `location` tag is `San Francisco`:
```sql
taos> select count(*) from test.meters where location="San Francisco";
select count(*) from test.meters where location="San Francisco";
```
Query the average, maximum, and minimum values of all rows whose `groupId` tag is `10`:
```sql
taos> select avg(current), max(voltage), min(phase) from test.meters where groupId=10;
select avg(current), max(voltage), min(phase) from test.meters where groupId=10;
```
Query the average, maximum, and minimum values for table `d10` in 10 second intervals:
Query the average, maximum, and minimum values for table `d10` in 1 second intervals:
```sql
taos> select avg(current), max(voltage), min(phase) from test.d10 interval(10s);
select first(ts), avg(current), max(voltage), min(phase) from test.d10 interval(1s);
```
In the query above you are selecting the first timestamp (ts) in the interval, another way of selecting this would be _wstart which will give the start of the time window. For more information about windowed queries, see [Time-Series Extensions](../../taos-sql/distinguished/).
## Additional Information
......
docs/en/05-get-started/03-package.md
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......@@ -67,13 +67,6 @@ Users will be prompted to enter some configuration information when install.sh i
</TabItem>
<TabItem label="Windows" value="windows">
1. Download the Windows installation package.
<PkgListV3 type={3}/>
2. Run the downloaded package to install TDengine.
</TabItem>
<TabItem value="apt-get" label="apt-get">
You can use `apt-get` to install TDengine from the official package repository.
......@@ -102,6 +95,15 @@ sudo apt-get install tdengine
:::tip
This installation method is supported only for Debian and Ubuntu.
::::
</TabItem>
<TabItem label="Windows" value="windows">
Note: TDengine only supports Windows Server 2016/2019 and windows 10/11 system versions on the windows platform.
1. Download the Windows installation package.
<PkgListV3 type={3}/>
2. Run the downloaded package to install TDengine.
</TabItem>
</Tabs>
......@@ -172,6 +174,20 @@ After the installation is complete, run `C:\TDengine\taosd.exe` to start TDengin
</TabItem>
</Tabs>
## Test data insert performance
After your TDengine Server is running normally, you can run the taosBenchmark utility to test its performance:
```bash
taosBenchmark
```
This command creates the `meters` supertable in the `test` database. In the `meters` supertable, it then creates 10,000 subtables named `d0` to `d9999`. Each table has 10,000 rows and each row has four columns: `ts`, `current`, `voltage`, and `phase`. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a `groupId` tag from 1 to 10 and a `location` tag of either `Campbell`, `Cupertino`, `Los Angeles`, `Mountain View`, `Palo Alto`, `San Diego`, `San Francisco`, `San Jose`, `Santa Clara` or `Sunnyvale`.
The `taosBenchmark` command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in less than a minute.
You can customize the test deployment that taosBenchmark creates by specifying command-line parameters. For information about command-line parameters, run the `taosBenchmark --help` command. For more information about taosBenchmark, see [taosBenchmark](../../reference/taosbenchmark).
## Command Line Interface
You can use the TDengine CLI to monitor your TDengine deployment and execute ad hoc queries. To open the CLI, run the following command:
......@@ -203,51 +219,38 @@ Query OK, 2 row(s) in set (0.003128s)
```
You can also can monitor the deployment status, add and remove user accounts, and manage running instances. You can run the TDengine CLI on either Linux or Windows machines. For more information, see [TDengine CLI](../../reference/taos-shell/).
## Test data insert performance
After your TDengine Server is running normally, you can run the taosBenchmark utility to test its performance:
```bash
taosBenchmark
```
This command creates the `meters` supertable in the `test` database. In the `meters` supertable, it then creates 10,000 subtables named `d0` to `d9999`. Each table has 10,000 rows and each row has four columns: `ts`, `current`, `voltage`, and `phase`. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a `groupId` tag from 1 to ten and a `location` tag of either `California.SanFrancisco` or `California.LosAngeles`.
The `taosBenchmark` command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in less than a minute.
You can customize the test deployment that taosBenchmark creates by specifying command-line parameters. For information about command-line parameters, run the `taosBenchmark --help` command. For more information about taosBenchmark, see [taosBenchmark](../../reference/taosbenchmark).
## Test data query performance
After using taosBenchmark to create your test deployment, you can run queries in the TDengine CLI to test its performance:
Query the number of rows in the `meters` supertable:
From the TDengine CLI query the number of rows in the `meters` supertable:
```sql
taos> select count(*) from test.meters;
select count(*) from test.meters;
```
Query the average, maximum, and minimum values of all 100 million rows of data:
```sql
taos> select avg(current), max(voltage), min(phase) from test.meters;
select avg(current), max(voltage), min(phase) from test.meters;
```
Query the number of rows whose `location` tag is `California.SanFrancisco`:
Query the number of rows whose `location` tag is `San Francisco`:
```sql
taos> select count(*) from test.meters where location="California.SanFrancisco";
select count(*) from test.meters where location="San Francisco";
```
Query the average, maximum, and minimum values of all rows whose `groupId` tag is `10`:
```sql
taos> select avg(current), max(voltage), min(phase) from test.meters where groupId=10;
select avg(current), max(voltage), min(phase) from test.meters where groupId=10;
```
Query the average, maximum, and minimum values for table `d10` in 10 second intervals:
Query the average, maximum, and minimum values for table `d10` in 1 second intervals:
```sql
taos> select avg(current), max(voltage), min(phase) from test.d10 interval(10s);
select first(ts), avg(current), max(voltage), min(phase) from test.d10 interval(1s);
```
In the query above you are selecting the first timestamp (ts) in the interval, another way of selecting this would be _wstart which will give the start of the time window. For more information about windowed queries, see [Time-Series Extensions](../../taos-sql/distinguished/).
docs/en/07-develop/01-connect/index.md
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......@@ -223,7 +223,7 @@ phpize && ./configure && make -j && make install
**Specify TDengine Location：**
```shell
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/2.4.0.0 && make -j && make install
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/3.0.0.0 && make -j && make install
```
> `--with-tdengine-dir=` is followed by the TDengine installation location.
......
docs/en/07-develop/04-query-data/index.mdx
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......@@ -43,7 +43,7 @@ Query OK, 2 row(s) in set (0.001100s)
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).
For detailed query syntax, see [Select](../../taos-sql././select).
For detailed query syntax, see [Select](../../taos-sql/select).
## Aggregation among Tables
......@@ -74,7 +74,7 @@ taos> SELECT count(*), max(current) FROM meters where groupId = 2;
Query OK, 1 row(s) in set (0.002136s)
```
In [Select](../../taos-sql././select), all query operations are marked as to whether they support STables or not.
In [Select](../../taos-sql/select), all query operations are marked as to whether they support STables or not.
## Down Sampling and Interpolation
......@@ -122,7 +122,7 @@ In many use cases, it's hard to align the timestamp of the data collected by eac
Interpolation can be performed in TDengine if there is no data in a time range.
For more information, see [Aggregate by Window](../../taos-sql/interval).
For more information, see [Aggregate by Window](../../taos-sql/distinguished).
## Examples
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---
sidebar_label: Continuous Query
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"
---
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.
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：
- The computation is performed and the result is returned in real time in stream computing, but the computation in continuous query is only started when a time window closes. For example, if the time window is 1 day, then the result will only be generated at 23:59:59.
- If a historical data row is written in to a time window for which the computation has already finished, the computation will not be performed again and the result will not be pushed to client applications again. If the results have already been written into TDengine, they will not be updated.
- In continuous query, if the result is pushed to a client, the client status is not cached on the server side and Exactly-once is not guaranteed by the server. If the client program crashes, a new time window will be generated from the time where the continuous query is restarted. If the result is written into TDengine, the data written into TDengine can be guaranteed as valid and continuous.
## Syntax
```sql
[CREATE TABLE AS] SELECT select_expr [, select_expr ...]
FROM {tb_name_list}
[WHERE where_condition]
[INTERVAL(interval_val [, interval_offset]) [SLIDING sliding_val]]
```
INTERVAL: The time window for which continuous query is performed
SLIDING: The time step for which the time window moves forward each time
## How to Use
In this section the use case of meters will be used to introduce how to use continuous query. Assume the STable and subtables have been created using the SQL statements below.
```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);
```
The SQL statement below retrieves the average voltage for a one minute time window, with each time window moving forward by 30 seconds.
```sql
select avg(voltage) from meters interval(1m) sliding(30s);
```
Whenever the above SQL statement is executed, all the existing data will be computed again. If the computation needs to be performed every 30 seconds automatically to compute on the data in the past one minute, the above SQL statement needs to be revised as below, in which `{startTime}` stands for the beginning timestamp in the latest time window.
```sql
select avg(voltage) from meters where ts > {startTime} interval(1m) sliding(30s);
```
An easier way to achieve this is to prepend `create table {tableName} as` before the `select`.
```sql
create table avg_vol as select avg(voltage) from meters interval(1m) sliding(30s);
```
A table named as `avg_vol` will be created automatically, then every 30 seconds the `select` statement will be executed automatically on the data in the past 1 minute, i.e. the latest time window, and the result is written into table `avg_vol`. The client program just needs to query from table `avg_vol`. For example:
```sql
taos> select * from avg_vol;
ts | avg_voltage_ |
===================================================
2020-07-29 13:37:30.000 | 222.0000000 |
2020-07-29 13:38:00.000 | 221.3500000 |
2020-07-29 13:38:30.000 | 220.1700000 |
2020-07-29 13:39:00.000 | 223.0800000 |
```
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.
```sql
create table avg_vol as select avg(voltage) from meters where ts > now and ts <= now + 1h interval(1m) sliding(30s);
```
`now` in the above SQL statement stands for the time when the continuous query is created, not the time when the computation is actually performed. To avoid the trouble caused by a delay in receiving data as much as possible, the actual computation in a continuous query is started after a little delay. That means, once a time window closes, the computation is not started immediately. Normally, the result are available after a little time, normally within one minute, after the time window closes.
## How to Manage
`show streams` command can be used in the TDengine CLI `taos` to show all the continuous queries in the system, and `kill stream` can be used to terminate a continuous query.
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---
sidebar_label: Data Subscription
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
---
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
import Java from "./_sub_java.mdx";
import Python from "./_sub_python.mdx";
import Go from "./_sub_go.mdx";
import Rust from "./_sub_rust.mdx";
import Node from "./_sub_node.mdx";
import CSharp from "./_sub_cs.mdx";
import CDemo from "./_sub_c.mdx";
## Introduction
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 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.
```c
taos_subscribe
taos_consume
taos_unsubscribe
```
For more details about these APIs please refer to [C/C++ Connector](/reference/connector/cpp). Their usage will be introduced below using the use case of meters, in which the schema of STable and subtables from the previous section [Continuous Query](/develop/continuous-query) are used. Full sample code can be found [here](https://github.com/taosdata/TDengine/blob/master/examples/c/subscribe.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 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;
select * from D1002 where ts > {last_timestamp2} and current > 10;
...
```
The above way works, but the problem is that the number of `select` statements increases with the number of meters. Additionally, the performance of both client side and server side will be unacceptable once the number of meters grows to a big enough number.
A better way is to query on the STable, only one `select` is enough regardless of the number of meters, like below:
```sql
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 easily using the subscription functionality provided by TDengine.
The first step is to create subscription using `taos_subscribe`.
```c
TAOS_SUB* tsub = NULL;
if (async) {
　　// create an asynchronous subscription, the callback function will be called every 1s
　　tsub = taos_subscribe(taos, restart, topic, sql, subscribe_callback, &blockFetch, 1000);
} else {
　　// create an synchronous subscription, need to call 'taos_consume' manually
　　tsub = taos_subscribe(taos, restart, topic, sql, NULL, NULL, 0);
}
```
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. 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 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 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. 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), 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. Shown below is the sample code to consume data in sync mode, in the else condition of `if (async)`.
```c
if (async) {
　　getchar();
} else while(1) {
　　TAOS_RES* res = taos_consume(tsub);
　　if (res == NULL) {
　　　　printf("failed to consume data.");
　　　　break;
　　} else {
　　　　print_result(res, blockFetch);
　　　　getchar();
　　}
}
```
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. It is similar to `taos_use_result`. Below is the implementation of `print_result`.
```c
void print_result(TAOS_RES* res, int blockFetch) {
　　TAOS_ROW row = NULL;
　　int num_fields = taos_num_fields(res);
　　TAOS_FIELD* fields = taos_fetch_fields(res);
　　int nRows = 0;
　　if (blockFetch) {
　　　　nRows = taos_fetch_block(res, &row);
　　　　for (int i = 0; i < nRows; i++) {
　　　　　　char temp[256];
　　　　　　taos_print_row(temp, row + i, fields, num_fields);
　　　　　　puts(temp);
　　　　}
　　} else {
　　　　while ((row = taos_fetch_row(res))) {
　　　　　　char temp[256];
　　　　　　taos_print_row(temp, row, fields, num_fields);
　　　　　　puts(temp);
　　　　　　nRows++;
　　　　}
　　}
　　printf("%d rows consumed.\n", nRows);
}
```
In the above code `taos_print_row` is used to process the data consumed. All matching rows are printed.
In async mode, consuming data is simpler as shown below.
```c
void subscribe_callback(TAOS_SUB* tsub, TAOS_RES *res, void* param, int code) {
　　print_result(res, *(int*)param);
}
```
`taos_unsubscribe` can be invoked to terminate a subscription.
```c
taos_unsubscribe(tsub, keep);
```
The second parameter `keep` is used to specify whether to keep the subscription progress on the client sde. If it is **false**, i.e. **0**, then subscription will be restarted from beginning regardless of the `restart` parameter's value when `taos_subscribe` is invoked again. The subscription progress information is stored in _{DataDir}/subscribe/_ , under which there is a file with the same name as `topic` for each subscription(Note: The default value of `DataDir` in the `taos.cfg` file is **/var/lib/taos/**. However, **/var/lib/taos/** does not exist on the Windows server. So you need to change the `DataDir` value to the corresponding existing directory."), the subscription will be restarted from the beginning if the corresponding progress file is removed.
Now let's see the effect of the above sample code, assuming below prerequisites have been done.
- The sample code has been downloaded to local system
- TDengine has been installed and launched properly on same system
- The database, STable, and subtables required in the sample code are ready
Launch the command below in the directory where the sample code resides to compile and start the program.
```bash
make
./subscribe -sql='select * from meters where current > 10;'
```
After the program is started, open another terminal and launch TDengine CLI `taos`, then use the below SQL commands to insert a row whose current is 12A into table **D1001**.
```sql
use test;
insert into D1001 values(now, 12, 220, 1);
```
Then, this row of data will be shown by the example program on the first terminal because its current exceeds 10A. More data can be inserted for you to observe the output of the example program.
## Examples
The example program below demonstrates how to subscribe, using connectors, to data rows in which current exceeds 10A.
### Prepare Data
```bash
# create database "power"
taos> create database power;
# use "power" as the database in following operations
taos> use power;
# create super table "meters"
taos> create table meters(ts timestamp, current float, voltage int, phase int) tags(location binary(64), groupId int);
# create tabes using the schema defined by super table "meters"
taos> create table d1001 using meters tags ("California.SanFrancisco", 2);
taos> create table d1002 using meters tags ("California.LoSangeles", 2);
# insert some rows
taos> insert into d1001 values("2020-08-15 12:00:00.000", 12, 220, 1),("2020-08-15 12:10:00.000", 12.3, 220, 2),("2020-08-15 12:20:00.000", 12.2, 220, 1);
taos> insert into d1002 values("2020-08-15 12:00:00.000", 9.9, 220, 1),("2020-08-15 12:10:00.000", 10.3, 220, 1),("2020-08-15 12:20:00.000", 11.2, 220, 1);
# filter out the rows in which current is bigger than 10A
taos> select * from meters where current > 10;
ts | current | voltage | phase | location | groupid |
===========================================================================================================
2020-08-15 12:10:00.000 | 10.30000 | 220 | 1 | California.LoSangeles | 2 |
2020-08-15 12:20:00.000 | 11.20000 | 220 | 1 | California.LoSangeles | 2 |
2020-08-15 12:00:00.000 | 12.00000 | 220 | 1 | California.SanFrancisco | 2 |
2020-08-15 12:10:00.000 | 12.30000 | 220 | 2 | California.SanFrancisco | 2 |
2020-08-15 12:20:00.000 | 12.20000 | 220 | 1 | California.SanFrancisco | 2 |
Query OK, 5 row(s) in set (0.004896s)
```
### Example Programs
<Tabs defaultValue="java" groupId="lang">
<TabItem label="Java" value="java">
<Java />
</TabItem>
<TabItem label="Python" value="Python">
<Python />
</TabItem>
{/* <TabItem label="Go" value="go">
<Go/>
</TabItem> */}
<TabItem label="Rust" value="rust">
<Rust />
</TabItem>
{/* <TabItem label="Node.js" value="nodejs">
<Node/>
</TabItem>
<TabItem label="C#" value="csharp">
<CSharp/>
</TabItem> */}
<TabItem label="C" value="c">
<CDemo />
</TabItem>
</Tabs>
### Run the Examples
The example programs first consume all historical data matching the criteria.
```bash
ts: 1597464000000 current: 12.0 voltage: 220 phase: 1 location: California.SanFrancisco groupid : 2
ts: 1597464600000 current: 12.3 voltage: 220 phase: 2 location: California.SanFrancisco groupid : 2
ts: 1597465200000 current: 12.2 voltage: 220 phase: 1 location: California.SanFrancisco groupid : 2
ts: 1597464600000 current: 10.3 voltage: 220 phase: 1 location: California.LoSangeles groupid : 2
ts: 1597465200000 current: 11.2 voltage: 220 phase: 1 location: California.LoSangeles groupid : 2
```
Next, use TDengine CLI to insert a new row.
```
# taos
taos> use power;
taos> insert into d1001 values(now, 12.4, 220, 1);
```
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
```
docs/en/07-develop/09-udf.md
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......@@ -102,7 +102,7 @@ Replace `aggfn` with the name of your function.
## Interface Functions
There are strict naming conventions for interface functions. The names of the start, finish, init, and destroy interfaces must be <udf-name>_start, <udf-name>_finish, <udf-name>_init, and <udf-name>_destroy, respectively. Replace `scalarfn`, `aggfn`, and `udf` with the name of your user-defined function.
There are strict naming conventions for interface functions. The names of the start, finish, init, and destroy interfaces must be <udf-name\>_start, <udf-name\>_finish, <udf-name\>_init, and <udf-name\>_destroy, respectively. Replace `scalarfn`, `aggfn`, and `udf` with the name of your user-defined function.
Interface functions return a value that indicates whether the operation was successful. If an operation fails, the interface function returns an error code. Otherwise, it returns TSDB_CODE_SUCCESS. The error codes are defined in `taoserror.h` and in the common API error codes in `taos.h`. For example, TSDB_CODE_UDF_INVALID_INPUT indicates invalid input. TSDB_CODE_OUT_OF_MEMORY indicates insufficient memory.
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---
title: Deployment
---
## Prerequisites
### Step 1
The FQDN of all hosts must be setup properly. All FQDNs need to be configured in the /etc/hosts file on each host. You must confirm that each FQDN can be accessed from any other host, you can do this by using the `ping` command.
The command `hostname -f` can be executed to get the hostname on any host. `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.
- 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`.
:::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 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, 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
firstEp h1.taosdata.com:6030
// must be configured to the FQDN of the host where the dnode is launched
fqdn h1.taosdata.com
// the port used by the dnode, default is 6030
serverPort 6030
// only necessary when replica is configured to an even number
#arbitrator ha.taosdata.com:6042
```
`firstEp` and `fqdn` must be configured properly. In `taos.cfg` of all dnodes in TDengine cluster, `firstEp` must be configured to point to same address, i.e. the first dnode of the cluster. `fqdn` and `serverPort` compose the address of each node itself. If you want to start multiple TDengine dnodes on a single host, please make sure all other configurations like `dataDir`, `logDir`, and other resources related parameters are not conflicting.
For all the dnodes in a TDengine cluster, the below parameters must be configured exactly the same, any node whose configuration is different from dnodes already in the cluster can't join the cluster.
| **#** | **Parameter** | **Definition** |
| ----- | -------------- | ------------------------------------------------------------- |
| 1 | statusInterval | The time interval for which dnode reports its status to mnode |
| 2 | timezone | Time Zone where the server is located |
| 3 | locale | Location code of the system |
| 4 | charset | Character set of the system |
## 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
Start the first dnode following the instructions in [Get Started](/get-started/). Then launch TDengine CLI `taos` and execute command `show dnodes`, the output is as following for example:
```
Welcome to the TDengine shell from Linux, Client Version:3.0.0.0
Copyright (c) 2022 by TAOS Data, Inc. All rights reserved.
Server is Enterprise trial Edition, ver:3.0.0.0 and will never expire.
taos> show dnodes;
id | endpoint | vnodes | support_vnodes | status | create_time | note |
============================================================================================================================================
1 | h1.taosdata.com:6030 | 0 | 1024 | ready | 2022-07-16 10:50:42.673 | |
Query OK, 1 rows affected (0.007984s)
taos>
```
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.
Let's assume we are starting the second dnode with FQDN, h2.taosdata.com. Firstly we make sure the configuration is correct.
```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
```
Secondly, 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 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;
```
If the status of the newly added dnode is offline, please check:
- Whether the `taosd` process is running properly or not
- In the log file `taosdlog.0` to see whether the fqdn and port are correct
The above process can be repeated to add more dnodes in the cluster.
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---
sidebar_label: Operation
title: Manage DNODEs
---
The previous section, [Deployment],(/cluster/deploy) showed you how to deploy and start a cluster from scratch. Once a cluster is ready, the status of dnode(s) in the cluster can be shown at any time. Dnodes can be managed from the TDengine CLI. New dnode(s) can be added to scale out the cluster, an existing dnode can be removed and you can even perform load balancing manually, if necessary.
:::note
All the commands introduced in this chapter must be run in the TDengine CLI - `taos`. Note that sometimes it is necessary to use root privilege.
:::
## Show DNODEs
The below command can be executed in TDengine CLI `taos` to list all dnodes in the cluster, including ID, end point (fqdn:port), status (ready, offline), number of vnodes, number of free vnodes and so on. We recommend executing this command after adding or removing a dnode.
```sql
SHOW DNODES;
```
Below is the example output of this command.
```
taos> show dnodes;
id | end_point | vnodes | cores | status | role | create_time | offline reason |
======================================================================================================================================
1 | localhost:6030 | 9 | 8 | ready | any | 2022-04-15 08:27:09.359 | |
Query OK, 1 row(s) in set (0.008298s)
```
## Show VGROUPs
To utilize system resources efficiently and provide scalability, data sharding is required. The data of each database is divided into multiple shards and stored in multiple vnodes. These vnodes may be located on different dnodes. One way of scaling out is to add more vnodes on dnodes. Each vnode can only be used for a single DB, but one DB can have multiple vnodes. The allocation of vnode is scheduled automatically by mnode based on system resources of the dnodes.
Launch TDengine CLI `taos` and execute below command:
```sql
USE SOME_DATABASE;
SHOW VGROUPS;
```
The output is like below:
taos> use db;
Database changed.
taos> show vgroups;
vgId | tables | status | onlines | v1_dnode | v1_status | compacting |
==========================================================================================
14 | 38000 | ready | 1 | 1 | leader | 0 |
15 | 38000 | ready | 1 | 1 | leader | 0 |
16 | 38000 | ready | 1 | 1 | leader | 0 |
17 | 38000 | ready | 1 | 1 | leader | 0 |
18 | 37001 | ready | 1 | 1 | leader | 0 |
19 | 37000 | ready | 1 | 1 | leader | 0 |
20 | 37000 | ready | 1 | 1 | leader | 0 |
21 | 37000 | ready | 1 | 1 | leader | 0 |
Query OK, 8 row(s) in set (0.001154s)
````
## Add DNODE
Launch TDengine CLI `taos` and execute the command below to add the end point of a new dnode into the EPI (end point) list of the cluster. "fqdn:port" must be quoted using double quotes.
```sql
CREATE DNODE "fqdn:port";
````
The example output is as below:
```
taos> create dnode "localhost:7030";
Query OK, 0 of 0 row(s) in database (0.008203s)
taos> show dnodes;
id | end_point | vnodes | cores | status | role | create_time | offline reason |
======================================================================================================================================
1 | localhost:6030 | 9 | 8 | ready | any | 2022-04-15 08:27:09.359 | |
2 | localhost:7030 | 0 | 0 | offline | any | 2022-04-19 08:11:42.158 | status not received |
Query OK, 2 row(s) in set (0.001017s)
```
It can be seen that the status of the new dnode is "offline". Once the dnode is started and connects to the firstEp of the cluster, you can execute the command again and get the example output below. As can be seen, both dnodes are in "ready" status.
```
taos> show dnodes;
id | end_point | vnodes | cores | status | role | create_time | offline reason |
======================================================================================================================================
1 | localhost:6030 | 3 | 8 | ready | any | 2022-04-15 08:27:09.359 | |
2 | localhost:7030 | 6 | 8 | ready | any | 2022-04-19 08:14:59.165 | |
Query OK, 2 row(s) in set (0.001316s)
```
## Drop DNODE
Launch TDengine CLI `taos` and execute the command below to drop or remove a dnode from the cluster. In the command, you can get `dnodeId` from `show dnodes`.
```sql
DROP DNODE "fqdn:port";
```
or
```sql
DROP DNODE dnodeId;
```
The example output is below：
```
taos> show dnodes;
id | end_point | vnodes | cores | status | role | create_time | offline reason |
======================================================================================================================================
1 | localhost:6030 | 9 | 8 | ready | any | 2022-04-15 08:27:09.359 | |
2 | localhost:7030 | 0 | 0 | offline | any | 2022-04-19 08:11:42.158 | status not received |
Query OK, 2 row(s) in set (0.001017s)
taos> drop dnode 2;
Query OK, 0 of 0 row(s) in database (0.000518s)
taos> show dnodes;
id | end_point | vnodes | cores | status | role | create_time | offline reason |
======================================================================================================================================
1 | localhost:6030 | 9 | 8 | ready | any | 2022-04-15 08:27:09.359 | |
Query OK, 1 row(s) in set (0.001137s)
```
In the above example, when `show dnodes` is executed the first time, two dnodes are shown. After `drop dnode 2` is executed, you can execute `show dnodes` again and it can be seen that only the dnode with ID 1 is still in the cluster.
:::note
- Once a dnode is dropped, it can't rejoin the cluster. To rejoin, the dnode needs to deployed again after cleaning up the data directory. Before dropping a dnode, the data belonging to the dnode MUST be migrated/backed up according to your data retention, data security or other SOPs.
- Please note that `drop dnode` is different from stopping `taosd` process. `drop dnode` just removes the dnode out of TDengine cluster. Only after a dnode is dropped, can the corresponding `taosd` process be stopped.
- Once a dnode is dropped, other dnodes in the cluster will be notified of the drop and will not accept the request from the dropped dnode.
- dnodeID is allocated automatically and can't be manually modified. dnodeID is generated in ascending order without duplication.
:::
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---
title: Cluster
keywords: ["cluster", "high availability", "load balance", "scale out"]
---
TDengine has a native distributed design and provides the ability to scale out. A few nodes can form a TDengine cluster. If you need higher processing power, you just need to add more nodes into the cluster. TDengine uses virtual node technology to virtualize a node into multiple virtual nodes to achieve load balancing. At the same time, TDengine can group virtual nodes on different nodes into virtual node groups, and use the replication mechanism to ensure the high availability of the system. The cluster feature of TDengine is completely open source.
This chapter mainly introduces cluster deployment, maintenance, and how to achieve high availability and load balancing.
```mdx-code-block
import DocCardList from '@theme/DocCardList';
import {useCurrentSidebarCategory} from '@docusaurus/theme-common';
<DocCardList items={useCurrentSidebarCategory().items}/>
```
docs/en/12-taos-sql/06-select.md
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......@@ -171,8 +171,8 @@ The \_QSTART and \_QEND pseudocolumns contain the beginning and end of the time
The \_QSTART and \_QEND pseudocolumns cannot be used in a WHERE clause.
**\_WSTART, \_WEND, and \_DURATION**
\_WSTART, \_WEND, and \_WDURATION pseudocolumns
**\_WSTART, \_WEND, and \_WDURATION**
The \_WSTART, \_WEND, and \_WDURATION pseudocolumns indicate the beginning, end, and duration of a window.
These pseudocolumns can be used only in time window-based aggregations and must occur after the aggregation clause.
......
docs/en/12-taos-sql/10-function.md
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......@@ -846,7 +846,7 @@ SELECT FIRST(field_name) FROM { tb_name | stb_name } [WHERE clause];
### INTERP
```sql
SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [ RANGE(timestamp1,timestamp2) ] [EVERY(interval)] [FILL ({ VALUE | PREV | NULL | LINEAR | NEXT})];
SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] RANGE(timestamp1,timestamp2) EVERY(interval) FILL({ VALUE | PREV | NULL | LINEAR | NEXT});
```
**Description**: The value that matches the specified timestamp range is returned, if existing; or an interpolation value is returned.
......@@ -861,11 +861,10 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [
- `INTERP` is used to get the value that matches the specified time slice from a column. If no such value exists an interpolation value will be returned based on `FILL` parameter.
- The input data of `INTERP` is the value of the specified column and a `where` clause can be used to filter the original data. If no `where` condition is specified then all original data is the input.
- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1<=timestamp2. timestamp1 is the starting point of the output time range and must be specified. timestamp2 is the ending point of the output time range and must be specified. If `RANGE` is not specified, then the timestamp of the first row that matches the filter condition is treated as timestamp1, the timestamp of the last row that matches the filter condition is treated as timestamp2.
- The number of rows in the result set of `INTERP` is determined by the parameter `EVERY`. Starting from timestamp1, one interpolation is performed for every time interval specified `EVERY` parameter. If `EVERY` parameter is not used, the time windows will be considered as no ending timestamp, i.e. there is only one time window from timestamp1.
- Interpolation is performed based on `FILL` parameter. No interpolation is performed if `FILL` is not used, that means either the original data that matches is returned or nothing is returned.
- `INTERP` can only be used to interpolate in single timeline. So it must be used with `group by tbname` when it's used on a STable. It can't be used with `GROUP BY` when it's used in the inner query of a nested query.
- The result of `INTERP` is not influenced by `ORDER BY TIMESTAMP`, which impacts the output order only..
- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1<=timestamp2. timestamp1 is the starting point of the output time range and must be specified. timestamp2 is the ending point of the output time range and must be specified.
- The number of rows in the result set of `INTERP` is determined by the parameter `EVERY`. Starting from timestamp1, one interpolation is performed for every time interval specified `EVERY` parameter.
- Interpolation is performed based on `FILL` parameter.
- `INTERP` can only be used to interpolate in single timeline. So it must be used with `partition by tbname` when it's used on a STable.
### LAST
......@@ -1232,7 +1231,7 @@ SELECT SERVER_VERSION();
### SERVER_STATUS
```sql
SELECT SERVER_VERSION();
SELECT SERVER_STATUS();
```
**Description**: The server status.
docs/en/12-taos-sql/12-distinguished.md
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......@@ -58,6 +58,15 @@ The following restrictions apply:
- The window clause cannot be used with a GROUP BY clause.
- `WHERE` clause can be used to specify the starting and ending time and other filter conditions
### Window Pseudocolumns
**\_WSTART, \_WEND, and \_WDURATION**
The \_WSTART, \_WEND, and \_WDURATION pseudocolumns indicate the beginning, end, and duration of a window.
These pseudocolumns occur after the aggregation clause.
### FILL Clause
`FILL` clause is used to specify how to fill when there is data missing in any window, including:
......
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......@@ -15,11 +15,6 @@ title: Escape Characters
| `\%` | % see below for details |
| `\_` | \_ see below for details |
:::note
Escape characters are available from version 2.4.0.4 .
:::
## Restrictions
1. If there are escape characters in identifiers (database name, table name, column name)
......
docs/en/12-taos-sql/index.md
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......@@ -3,7 +3,7 @@ title: TDengine SQL
description: "The syntax supported by TDengine SQL "
---
This section explains the syntax of SQL to perform operations on databases, tables and STables, insert data, select data and use functions. We also provide some tips that can be used in TDengine SQL. If you have previous experience with SQL this section will be fairly easy to understand. If you do not have previous experience with SQL, you'll come to appreciate the simplicity and power of SQL. TDengine SQL has been enhanced in version 3.0, and the query engine has been rearchitected. For information about how TDengine SQL has changed, see [Changes in TDengine 3.0](/taos-sql/changes).
This section explains the syntax of SQL to perform operations on databases, tables and STables, insert data, select data and use functions. We also provide some tips that can be used in TDengine SQL. If you have previous experience with SQL this section will be fairly easy to understand. If you do not have previous experience with SQL, you'll come to appreciate the simplicity and power of SQL. TDengine SQL has been enhanced in version 3.0, and the query engine has been rearchitected. For information about how TDengine SQL has changed, see [Changes in TDengine 3.0](../taos-sql/changes).
TDengine SQL is the major interface for users to write data into or query from TDengine. It uses standard SQL syntax and includes extensions and optimizations for time-series data and services. The maximum length of a TDengine SQL statement is 1 MB. Note that keyword abbreviations are not supported. For example, DELETE cannot be entered as DEL.
......
docs/en/13-operation/01-pkg-install.md
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......@@ -10,131 +10,7 @@ TDengine community version provides deb and rpm packages for users to choose fro
## Install
<Tabs>
<TabItem label="Install Deb" value="debinst">
1. Download deb package from official website, for example TDengine-server-2.4.0.7-Linux-x64.deb
2. In the directory where the package is located, execute the command below
```bash
$ sudo dpkg -i TDengine-server-2.4.0.7-Linux-x64.deb
(Reading database ... 137504 files and directories currently installed.)
Preparing to unpack TDengine-server-2.4.0.7-Linux-x64.deb ...
TDengine is removed successfully!
Unpacking tdengine (2.4.0.7) over (2.4.0.7) ...
Setting up tdengine (2.4.0.7) ...
Start to install TDengine...
System hostname is: ubuntu-1804
Enter FQDN:port (like h1.taosdata.com:6030) of an existing TDengine cluster node to join
OR leave it blank to build one:
Enter your email address for priority support or enter empty to skip:
Created symlink /etc/systemd/system/multi-user.target.wants/taosd.service → /etc/systemd/system/taosd.service.
To configure TDengine : edit /etc/taos/taos.cfg
To start TDengine : sudo systemctl start taosd
To access TDengine : taos -h ubuntu-1804 to login into TDengine server
TDengine is installed successfully!
```
</TabItem>
<TabItem label="Install RPM" value="rpminst">
1. Download rpm package from official website, for example TDengine-server-2.4.0.7-Linux-x64.rpm；
2. In the directory where the package is located, execute the command below
```
$ sudo rpm -ivh TDengine-server-2.4.0.7-Linux-x64.rpm
Preparing... ################################# [100%]
Updating / installing...
1:tdengine-2.4.0.7-3 ################################# [100%]
Start to install TDengine...
System hostname is: centos7
Enter FQDN:port (like h1.taosdata.com:6030) of an existing TDengine cluster node to join
OR leave it blank to build one:
Enter your email address for priority support or enter empty to skip:
Created symlink from /etc/systemd/system/multi-user.target.wants/taosd.service to /etc/systemd/system/taosd.service.
To configure TDengine : edit /etc/taos/taos.cfg
To start TDengine : sudo systemctl start taosd
To access TDengine : taos -h centos7 to login into TDengine server
TDengine is installed successfully!
```
</TabItem>
<TabItem label="Install tar.gz" value="tarinst">
1. Download the tar.gz package, for example TDengine-server-2.4.0.7-Linux-x64.tar.gz；
2. In the directory where the package is located, first decompress the file, then switch to the sub-directory generated in decompressing, i.e. "TDengine-enterprise-server-2.4.0.7/" in this example, and execute the `install.sh` script.
```bash
$ tar xvzf TDengine-enterprise-server-2.4.0.7-Linux-x64.tar.gz
TDengine-enterprise-server-2.4.0.7/
TDengine-enterprise-server-2.4.0.7/driver/
TDengine-enterprise-server-2.4.0.7/driver/vercomp.txt
TDengine-enterprise-server-2.4.0.7/driver/libtaos.so.2.4.0.7
TDengine-enterprise-server-2.4.0.7/install.sh
TDengine-enterprise-server-2.4.0.7/examples/
...
$ ll
total 43816
drwxrwxr-x 3 ubuntu ubuntu 4096 Feb 22 09:31 ./
drwxr-xr-x 20 ubuntu ubuntu 4096 Feb 22 09:30 ../
drwxrwxr-x 4 ubuntu ubuntu 4096 Feb 22 09:30 TDengine-enterprise-server-2.4.0.7/
-rw-rw-r-- 1 ubuntu ubuntu 44852544 Feb 22 09:31 TDengine-enterprise-server-2.4.0.7-Linux-x64.tar.gz
$ cd TDengine-enterprise-server-2.4.0.7/
$ ll
total 40784
drwxrwxr-x 4 ubuntu ubuntu 4096 Feb 22 09:30 ./
drwxrwxr-x 3 ubuntu ubuntu 4096 Feb 22 09:31 ../
drwxrwxr-x 2 ubuntu ubuntu 4096 Feb 22 09:30 driver/
drwxrwxr-x 10 ubuntu ubuntu 4096 Feb 22 09:30 examples/
-rwxrwxr-x 1 ubuntu ubuntu 33294 Feb 22 09:30 install.sh*
-rw-rw-r-- 1 ubuntu ubuntu 41704288 Feb 22 09:30 taos.tar.gz
$ sudo ./install.sh
Start to update TDengine...
Created symlink /etc/systemd/system/multi-user.target.wants/taosd.service → /etc/systemd/system/taosd.service.
Nginx for TDengine is updated successfully!
To configure TDengine : edit /etc/taos/taos.cfg
To configure Taos Adapter (if has) : edit /etc/taos/taosadapter.toml
To start TDengine : sudo systemctl start taosd
To access TDengine : use taos -h ubuntu-1804 in shell OR from http://127.0.0.1:6060
TDengine is updated successfully!
Install taoskeeper as a standalone service
taoskeeper is installed, enable it by `systemctl enable taoskeeper`
```
:::info
Users will be prompted to enter some configuration information when install.sh is executing. The interactive mode can be disabled by executing `./install.sh -e no`. `./install.sh -h` can show all parameters with detailed explanation.
:::
</TabItem>
</Tabs>
:::note
When installing on the first node in the cluster, at the "Enter FQDN:" prompt, nothing needs to be provided. When installing on subsequent nodes, at the "Enter FQDN:" prompt, you must enter the end point of the first dnode in the cluster if it is already up. You can also just ignore it and configure it later after installation is finished.
:::
About details of installing TDenine, please refer to [Installation Guide](../../get-started/package/).
## Uninstall
......@@ -146,7 +22,7 @@ Deb package of TDengine can be uninstalled as below:
```bash
$ sudo dpkg -r tdengine
(Reading database ... 137504 files and directories currently installed.)
Removing tdengine (2.4.0.7) ...
Removing tdengine (3.0.0.0) ...
TDengine is removed successfully!
```
......@@ -245,7 +121,7 @@ For example, if using `systemctl` , the commands to start, stop, restart and che
- Check server status：`systemctl status taosd`
From version 2.4.0.0, a new independent component named as `taosAdapter` has been included in TDengine. `taosAdapter` should be started and stopped using `systemctl`.
Another component named as `taosAdapter` is to provide HTTP service for TDengine, it should be started and stopped using `systemctl`.
If the server process is OK, the output of `systemctl status` is like below:
......
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---
title: User Management
---
A system operator can use TDengine CLI `taos` to create or remove users or change passwords. The SQL commands are documented below:
## Create User
```sql
CREATE USER <user_name> PASS <'password'>;
```
When creating a user and specifying the user name and password, the password needs to be quoted using single quotes.
## Drop User
```sql
DROP USER <user_name>;
```
Dropping a user can only be performed by root.
## Change Password
```sql
ALTER USER <user_name> PASS <'password'>;
```
To keep the case of the password when changing password, the password needs to be quoted using single quotes.
## Change Privilege
```sql
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 is not allowed to be authorized to any user.
## Show Users
```sql
SHOW USERS;
```
:::note
In SQL syntax, `< >` means the part that needs to be input by the user, excluding the `< >` itself.
:::
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---
sidebar_label: Connections & Tasks
title: Manage Connections and Query Tasks
---
A system operator can use the TDengine CLI to show connections, ongoing queries, stream computing, and can close connections or stop ongoing query tasks or stream computing.
## Show Connections
```sql
SHOW CONNECTIONS;
```
One column of the output of the above SQL command is "ip:port", which is the end point of the client.
## Force Close Connections
```sql
KILL CONNECTION <connection-id>;
```
In the above SQL command, `connection-id` is from the first column of the output of `SHOW CONNECTIONS`.
## Show Ongoing Queries
```sql
SHOW QUERIES;
```
The first column of the output is query ID, which is composed of the corresponding connection ID and the sequence number of the current query task started on this connection. The format is "connection-id:query-no".
## Force Close Queries
```sql
KILL QUERY <query-id>;
```
In the above SQL command, `query-id` is from the first column of the output of `SHOW QUERIES `.
## Show Continuous Query
```sql
SHOW STREAMS;
```
The first column of the output is stream ID, which is composed of the connection ID and the sequence number of the current stream started on this connection. The format is "connection-id:stream-no".
## Force Close Continuous Query
```sql
KILL STREAM <stream-id>;
```
The above SQL command, `stream-id` is from the first column of the output of `SHOW STREAMS`.
docs/en/14-reference/03-connector/php.mdx
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---
sidebar_position: 1
sidebar_label: PHP
sidebar_label: PHP (community contribution)
title: PHP Connector
---
......@@ -61,7 +61,7 @@ phpize && ./configure && make -j && make install
**Specify TDengine location：**
```shell
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/2.4.0.0 && make -j && make install
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/3.0.0.0 && make -j && make install
```
> `--with-tdengine-dir=` is followed by TDengine location.
......
docs/en/14-reference/03-connector/python.mdx
浏览文件 @ fece844f
......@@ -150,10 +150,19 @@ If the test is successful, it will output the server version information, e.g.
```json
{
"status": "succ",
"head": ["server_version()"],
"column_meta": [["server_version()", 8, 8]],
"data": [["2.4.0.16"]],
"code": 0,
"column_meta": [
[
"server_version()",
"VARCHAR",
7
]
],
"data": [
[
"3.0.0.0"
]
],
"rows": 1
}
```
......
docs/en/14-reference/04-taosadapter.md
浏览文件 @ fece844f
......@@ -30,7 +30,7 @@ taosAdapter provides the following features.
### Install taosAdapter
taosAdapter has been part of TDengine server software since TDengine v2.4.0.0. If you use the TDengine server, you don't need additional steps to install taosAdapter. You can download taosAdapter from [TDengine official website](https://tdengine.com/all-downloads/) to download the TDengine server installation package (taosAdapter is included in v2.4.0.0 and later version). If you need to deploy taosAdapter separately on another server other than the TDengine server, you should install the full TDengine server package on that server to install taosAdapter. If you need to build taosAdapter from source code, you can refer to the [Building taosAdapter]( https://github.com/taosdata/taosadapter/blob/3.0/BUILD.md) documentation.
If you use the TDengine server, you don't need additional steps to install taosAdapter. You can download taosAdapter from [TDengine 3.0 released versions](../../releases) to download the TDengine server installation package. If you need to deploy taosAdapter separately on another server other than the TDengine server, you should install the full TDengine server package on that server to install taosAdapter. If you need to build taosAdapter from source code, you can refer to the [Building taosAdapter]( https://github.com/taosdata/taosadapter/blob/3.0/BUILD.md) documentation.
### Start/Stop taosAdapter
......@@ -329,4 +329,4 @@ In TDengine server 2.2.x.x or earlier, the TDengine server process (taosd) conta
| 3 | telegrafUseFieldNum | See the taosAdapter telegraf configuration method | |
| 4 | restfulRowLimit | restfulRowLimit | Embedded httpd outputs 10240 rows of data by default, the maximum allowed is 102400. taosAdapter also provides restfulRowLimit but it is not limited by default. You can configure it according to the actual scenario.
| 5 | httpDebugFlag | Not applicable | httpdDebugFlag does not work for taosAdapter |
| 6 | httpDBNameMandatory | N/A | taosAdapter requires the database name to be specified in the URL |
\ No newline at end of file
| 6 | httpDBNameMandatory | N/A | taosAdapter requires the database name to be specified in the URL |
docs/en/14-reference/11-docker/index.md
浏览文件 @ fece844f
......@@ -115,7 +115,7 @@ If you want to start your application in a container, you need to add the corres
```docker
FROM ubuntu:20.04
RUN apt-get update && apt-get install -y wget
ENV TDENGINE_VERSION=2.4.0.0
ENV TDENGINE_VERSION=3.0.0.0
RUN wget -c https://www.taosdata.com/assets-download/TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \
&& tar xvf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \
&& cd TDengine-client-${TDENGINE_VERSION} \
......@@ -216,7 +216,7 @@ Here is the full Dockerfile:
```docker
FROM golang:1.17.6-buster as builder
ENV TDENGINE_VERSION=2.4.0.0
ENV TDENGINE_VERSION=3.0.0.0
RUN wget -c https://www.taosdata.com/assets-download/TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \
&& tar xvf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \
&& cd TDengine-client-${TDENGINE_VERSION} \
......@@ -232,7 +232,7 @@ RUN go build
FROM ubuntu:20.04
RUN apt-get update && apt-get install -y wget
ENV TDENGINE_VERSION=2.4.0.0
ENV TDENGINE_VERSION=3.0.0.0
RUN wget -c https://www.taosdata.com/assets-download/TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \
&& tar xvf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \
&& cd TDengine-client-${TDENGINE_VERSION} \
......@@ -320,7 +320,7 @@ password: taosdata
2. Start the cluster
```shell
$ VERSION=2.4.0.0 docker-compose up -d
$ VERSION=3.0.0.0 docker-compose up -d
Creating network "test_default" with the default driver
Creating volume "test_taosdata-td1" with default driver
Creating volume "test_taoslog-td1" with default driver
......@@ -457,7 +457,7 @@ If you want to deploy a container-based TDengine cluster on multiple hosts, you
The docker-compose file can refer to the previous section. Here is the command to start TDengine with docker swarm:
```shell
$ VERSION=2.4.0 docker stack deploy -c docker-compose.yml taos
$ VERSION=3.0.0.0 docker stack deploy -c docker-compose.yml taos
Creating network taos_inter
Creating network taos_api
Creating service taos_arbitrator
......@@ -473,20 +473,20 @@ Checking status:
$ docker stack ps taos
ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS
79ni8temw59n taos_nginx.1 nginx:latest TM1701 Running Running about a minute ago
3e94u72msiyg taos_adapter.1 tdengine/tdengine:2.4.0 TM1702 Running Running 56 seconds ago
100amjkwzsc6 taos_td-2.1 tdengine/tdengine:2.4.0 TM1703 Running Running about a minute ago
pkjehr2vvaaa taos_td-1.1 tdengine/tdengine:2.4.0 TM1704 Running Running 2 minutes ago
tpzvgpsr1qkt taos_arbitrator.1 tdengine/tdengine:2.4.0 TM1705 Running Running 2 minutes ago
rvss3g5yg6fa taos_adapter.2 tdengine/tdengine:2.4.0 TM1706 Running Running 56 seconds ago
i2augxamfllf taos_adapter.3 tdengine/tdengine:2.4.0 TM1707 Running Running 56 seconds ago
lmjyhzccpvpg taos_adapter.4 tdengine/tdengine:2.4.0 TM1708 Running Running 56 seconds ago
3e94u72msiyg taos_adapter.1 tdengine/tdengine:3.0.0.0 TM1702 Running Running 56 seconds ago
100amjkwzsc6 taos_td-2.1 tdengine/tdengine:3.0.0.0 TM1703 Running Running about a minute ago
pkjehr2vvaaa taos_td-1.1 tdengine/tdengine:3.0.0.0 TM1704 Running Running 2 minutes ago
tpzvgpsr1qkt taos_arbitrator.1 tdengine/tdengine:3.0.0.0 TM1705 Running Running 2 minutes ago
rvss3g5yg6fa taos_adapter.2 tdengine/tdengine:3.0.0.0 TM1706 Running Running 56 seconds ago
i2augxamfllf taos_adapter.3 tdengine/tdengine:3.0.0.0 TM1707 Running Running 56 seconds ago
lmjyhzccpvpg taos_adapter.4 tdengine/tdengine:3.0.0.0 TM1708 Running Running 56 seconds ago
$ docker service ls
ID NAME MODE REPLICAS IMAGE PORTS
561t4lu6nfw6 taos_adapter replicated 4/4 tdengine/tdengine:2.4.0
3hk5ct3q90sm taos_arbitrator replicated 1/1 tdengine/tdengine:2.4.0
561t4lu6nfw6 taos_adapter replicated 4/4 tdengine/tdengine:3.0.0.0
3hk5ct3q90sm taos_arbitrator replicated 1/1 tdengine/tdengine:3.0.0.0
d8qr52envqzu taos_nginx replicated 1/1 nginx:latest *:6041->6041/tcp, *:6044->6044/udp
2isssfvjk747 taos_td-1 replicated 1/1 tdengine/tdengine:2.4.0
9pzw7u02ichv taos_td-2 replicated 1/1 tdengine/tdengine:2.4.0
2isssfvjk747 taos_td-1 replicated 1/1 tdengine/tdengine:3.0.0.0
9pzw7u02ichv taos_td-2 replicated 1/1 tdengine/tdengine:3.0.0.0
```
From the above output, you can see two dnodes, two taosAdapters, and one Nginx reverse proxy service.
......@@ -502,5 +502,5 @@ verify: Service converged
$ docker service ls -f name=taos_adapter
ID NAME MODE REPLICAS IMAGE PORTS
561t4lu6nfw6 taos_adapter replicated 1/1 tdengine/tdengine:2.4.0
561t4lu6nfw6 taos_adapter replicated 1/1 tdengine/tdengine:3.0.0.0
```
docs/en/14-reference/12-config/index.md
浏览文件 @ fece844f
......@@ -75,7 +75,6 @@ taos --dump-config
| Applicable | Server Only |
| Meaning | The port for external access after `taosd` is started |
| Default Value | 6030 |
| Note | REST service is provided by `taosd` before 2.4.0.0 but by `taosAdapter` after 2.4.0.0, the default port of REST service is 6041 |
:::note
TDengine uses 13 continuous ports, both TCP and UDP, starting with the port specified by `serverPort`. You should ensure, in your firewall rules, that these ports are kept open. Below table describes the ports used by TDengine in details.
......@@ -87,11 +86,11 @@ TDengine uses 13 continuous ports, both TCP and UDP, starting with the port spec
| TCP | 6030 | Communication between client and server | serverPort |
| TCP | 6035 | Communication among server nodes in cluster | serverPort+5 |
| TCP | 6040 | Data syncup among server nodes in cluster | serverPort+10 |
| TCP | 6041 | REST connection between client and server | Prior to 2.4.0.0: serverPort+11; After 2.4.0.0 refer to [taosAdapter](/reference/taosadapter/) |
| TCP | 6041 | REST connection between client and server | Please refer to [taosAdapter](../taosadapter/) |
| TCP | 6042 | Service Port of Arbitrator | The parameter of Arbitrator |
| TCP | 6043 | Service Port of TaosKeeper | The parameter of TaosKeeper |
| TCP | 6044 | Data access port for StatsD | refer to [taosAdapter](/reference/taosadapter/) |
| UDP | 6045 | Data access for statsd | refer to [taosAdapter](/reference/taosadapter/) |
| TCP | 6044 | Data access port for StatsD | refer to [taosAdapter](../taosadapter/) |
| UDP | 6045 | Data access for statsd | refer to [taosAdapter](../taosadapter/) |
| TCP | 6060 | Port of Monitoring Service in Enterprise version | |
| UDP | 6030-6034 | Communication between client and server | serverPort |
| UDP | 6035-6039 | Communication among server nodes in cluster | serverPort |
......@@ -777,12 +776,6 @@ To prevent system resource from being exhausted by multiple concurrent streams,
## HTTP Parameters
:::note
HTTP service was provided by `taosd` prior to version 2.4.0.0 and is provided by `taosAdapter` after version 2.4.0.0.
The parameters described in this section are only application in versions prior to 2.4.0.0. If you are using any version from 2.4.0.0, please refer to [taosAdapter](/reference/taosadapter/).
:::
### http
| Attribute | Description |
......@@ -980,16 +973,7 @@ The parameters described in this section are only application in versions prior
| Applicable | Server and Client |
| Meaning | Log level of common module |
| Value Range | Same as debugFlag |
| Default Value | |
### httpDebugFlag
| Attribute | Description |
| ------------- | ------------------------------------------- |
| Applicable | Server Only |
| Meaning | Log level of http module (prior to 2.4.0.0) |
| Value Range | Same as debugFlag |
| Default Value | |
| Default Value | | |
### mqttDebugFlag
......
docs/en/14-reference/12-directory.md
浏览文件 @ fece844f
......@@ -29,11 +29,6 @@ All executable files of TDengine are in the _/usr/local/taos/bin_ directory by d
- _set_core.sh_: script for setting up the system to generate core dump files for easy debugging
- _taosd-dump-cfg.gdb_: script to facilitate debugging of taosd's gdb execution.
:::note
taosdump after version 2.4.0.0 require taosTools as a standalone installation. A new version of taosBenchmark is include in taosTools too.
:::
:::tip
You can configure different data directories and log directories by modifying the system configuration file `taos.cfg`.
......
docs/en/20-third-party/06-statsd.md
浏览文件 @ fece844f
......@@ -39,15 +39,8 @@ $ echo "foo:1|c" | nc -u -w0 127.0.0.1 8125
Use the TDengine CLI to verify that StatsD data is written to TDengine and can read out correctly.
```
Welcome to the TDengine shell from Linux, Client Version:2.4.0.0
Copyright (c) 2020 by TAOS Data, Inc. All rights reserved.
taos> show databases;
name | created_time | ntables | vgroups | replica | quorum | days | keep | cache(MB) | blocks | minrows | maxrows | wallevel | fsync | comp | cachelast | precision | update | status |
====================================================================================================================================================================================================================================================================================
log | 2022-04-20 07:19:50.260 | 11 | 1 | 1 | 1 | 10 | 3650 | 16 | 6 | 100 | 4096 | 1 | 3000 | 2 | 0 | ms | 0 | ready |
statsd | 2022-04-20 09:54:51.220 | 1 | 1 | 1 | 1 | 10 | 3650 | 16 | 6 | 100 | 4096 | 1 | 3000 | 2 | 0 | ns | 2 | ready |
Query OK, 2 row(s) in set (0.003142s)
Welcome to the TDengine shell from Linux, Client Version:3.0.0.0
Copyright (c) 2022 by TAOS Data, Inc. All rights reserved.
taos> use statsd;
Database changed.
......
docs/en/25-application/01-telegraf.md
浏览文件 @ fece844f
......@@ -34,7 +34,7 @@ Please refer to the [official documentation](https://grafana.com/grafana/downloa
### TDengine
Download the latest TDengine-server 2.4.0.x or above from the [Downloads](http://taosdata.com/cn/all-downloads/) page on the TAOSData website and install it.
Download the latest TDengine-server from the [Downloads](http://tdengine.com/en/all-downloads/) page on the TAOSData website and install it.
## Data Connection Setup
......@@ -79,5 +79,5 @@ Click on the plus icon on the left and select `Import` to get the data from `htt
## Wrap-up
The above demonstrates how to quickly build a IT DevOps visualization system. Thanks to the new schemaless protocol parsing feature in TDengine version 2.4.0.0 and ability to integrate easily with a large software ecosystem, users can build an efficient and easy-to-use IT DevOps visualization system in just a few minutes.
The above demonstrates how to quickly build a IT DevOps visualization system. Thanks to the schemaless protocol parsing feature in TDengine and ability to integrate easily with a large software ecosystem, users can build an efficient and easy-to-use IT DevOps visualization system in just a few minutes.
Please refer to the official documentation and product implementation cases for other features.
docs/en/25-application/02-collectd.md
浏览文件 @ fece844f
......@@ -37,7 +37,7 @@ Please refer to the [official documentation](https://grafana.com/grafana/downloa
### Install TDengine
Download the latest TDengine-server 2.4.0.x or above from the [Downloads](http://taosdata.com/cn/all-downloads/) page on the TAOSData website and install it.
Download the latest TDengine-server from the [Downloads](http://tdengine.com/en/all-downloads/) page on the TAOSData website and install it.
## Data Connection Setup
......@@ -99,6 +99,6 @@ Download the dashboard json from `https://github.com/taosdata/grafanaplugin/blob
## Wrap-up
TDengine, as an emerging time-series big data platform, has the advantages of high performance, high reliability, easy management and easy maintenance. Thanks to the new schemaless protocol parsing feature in TDengine version 2.4.0.0 and ability to integrate easily with a large software ecosystem, users can build an efficient and easy-to-use IT DevOps visualization system, or adapt an existing system, in just a few minutes.
TDengine, as an emerging time-series big data platform, has the advantages of high performance, high reliability, easy management and easy maintenance. Thanks to the new schemaless protocol parsing feature in TDengine and ability to integrate easily with a large software ecosystem, users can build an efficient and easy-to-use IT DevOps visualization system, or adapt an existing system, in just a few minutes.
For TDengine's powerful data writing and querying performance and other features, please refer to the official documentation and successful product implementation cases.
docs/en/25-application/03-immigrate.md
浏览文件 @ fece844f
......@@ -419,11 +419,11 @@ Note that once the installation is complete, do not immediately start the `taosd
To ensure that the system can obtain the necessary information for regular operation. Please set the following vital parameters correctly on the server:
FQDN, firstEp, secondEP, dataDir, logDir, tmpDir, serverPort. For the specific meaning and setting requirements of each parameter, please refer to the document "[TDengine Cluster Installation and Management](/cluster/)"
FQDN, firstEp, secondEP, dataDir, logDir, tmpDir, serverPort. For the specific meaning and setting requirements of each parameter, please refer to the document "[TDengine Cluster Deployment](../../deployment)"
Follow the same steps to set parameters on the other nodes, start the taosd service, and then add Dnodes to the cluster.
Finally, start `taos` and execute the `show dnodes` command. If you can see all the nodes that have joined the cluster, the cluster building process was successfully completed. For specific operation procedures and precautions, please refer to the document "[TDengine Cluster Installation and Management](/cluster/)".
Finally, start `taos` and execute the `show dnodes` command. If you can see all the nodes that have joined the cluster, the cluster building process was successfully completed. For specific operation procedures and precautions, please refer to the document "[TDengine Cluster Deployment](../../deployment)".
## Appendix 4: Super Table Names
......@@ -431,5 +431,5 @@ Since OpenTSDB's metric name has a dot (".") in it, for example, a metric with a
## Appendix 5: Reference Articles
1. [Using TDengine + collectd/StatsD + Grafana to quickly build an IT operation and maintenance monitoring system](/application/collectd/)
2. [Write collected data directly to TDengine through collectd](/third-party/collectd/)
1. [Using TDengine + collectd/StatsD + Grafana to quickly build an IT operation and maintenance monitoring system](../collectd/)
2. [Write collected data directly to TDengine through collectd](../collectd/)
docs/en/27-train-faq/03-docker.md 已删除 100644 → 0
浏览文件 @ b0263a4b
---
sidebar_label: TDengine in Docker
title: Deploy TDengine in Docker
---
We do not recommend deploying TDengine using Docker in a production system. However, Docker is still very useful in a development environment, especially when your host is not Linux. From version 2.0.14.0, the official image of TDengine can support X86-64, X86, arm64, and rm32 .
In this chapter we introduce a simple step by step guide to use TDengine in Docker.
## Install Docker
To install Docker please refer to [Get Docker](https://docs.docker.com/get-docker/).
After Docker is installed, you can check whether Docker is installed properly by displaying Docker version.
```bash
$ docker -v
Docker version 20.10.3, build 48d30b5
```
## Launch TDengine in Docker
### Launch TDengine Server
```bash
$ docker run -d -p 6030-6049:6030-6049 -p 6030-6049:6030-6049/udp tdengine/tdengine
526aa188da767ae94b244226a2b2eec2b5f17dd8eff592893d9ec0cd0f3a1ccd
```
In the above command, a docker container is started to run TDengine server, the port range 6030-6049 of the container is mapped to host port range 6030-6049. If port range 6030-6049 has been occupied on the host, please change to an available host port range. For port requirements on the host, please refer to [Port Configuration](/reference/config/#serverport).
- **docker run**: Launch a docker container
- **-d**: the container will run in background mode
- **-p**: port mapping
- **tdengine/tdengine**: The image from which to launch the container
- **526aa188da767ae94b244226a2b2eec2b5f17dd8eff592893d9ec0cd0f3a1ccd**: the container ID if successfully launched.
Furthermore, `--name` can be used with `docker run` to specify name for the container, `--hostname` can be used to specify hostname for the container, `-v` can be used to mount local volumes to the container so that the data generated inside the container can be persisted to disk on the host.
```bash
docker run -d --name tdengine --hostname="tdengine-server" -v ~/work/taos/log:/var/log/taos -v ~/work/taos/data:/var/lib/taos -p 6030-6049:6030-6049 -p 6030-6049:6030-6049/udp tdengine/tdengine
```
- **--name tdengine**: specify the name of the container, the name can be used to specify the container later
- **--hostname=tdengine-server**: specify the hostname inside the container, the hostname can be used inside the container without worrying the container IP may vary
- **-v**: volume mapping between host and container
### Check the container
```bash
docker ps
```
The output is like below:
```
CONTAINER ID IMAGE COMMAND CREATED STATUS ···
c452519b0f9b tdengine/tdengine "taosd" 14 minutes ago Up 14 minutes ···
```
- **docker ps**: List all the containers
- **CONTAINER ID**: Container ID
- **IMAGE**: The image used for the container
- **COMMAND**: The command used when launching the container
- **CREATED**: When the container was created
- **STATUS**: Status of the container
### Access TDengine inside container
```bash
$ docker exec -it tdengine /bin/bash
root@tdengine-server:~/TDengine-server-2.4.0.4#
```
- **docker exec**: Attach to the container
- **-i**: Interactive mode
- **-t**: Use terminal
- **tdengine**: Container name, up to the output of `docker ps`
- **/bin/bash**: The command to execute once the container is attached
Inside the container, start TDengine CLI `taos`
```bash
root@tdengine-server:~/TDengine-server-2.4.0.4# taos
Welcome to the TDengine shell from Linux, Client Version:2.4.0.4
Copyright (c) 2020 by TAOS Data, Inc. All rights reserved.
taos>
```
The above example is for a successful connection. If `taos` fails to connect to the server side, error information would be shown.
In TDengine CLI, SQL commands can be executed to create/drop databases, tables, STables, and insert or query data. For details please refer to [TAOS SQL](/taos-sql/).
### Access TDengine from host
If option `-p` used to map ports properly between host and container, it's also able to access TDengine in container from the host as long as `firstEp` is configured correctly for the client on host.
```
$ taos
Welcome to the TDengine shell from Linux, Client Version:2.4.0.4
Copyright (c) 2020 by TAOS Data, Inc. All rights reserved.
taos>
```
It's also able to access the REST interface provided by TDengine in container from the host.
```
curl -L -u root:taosdata -d "show databases" 127.0.0.1:6041/rest/sql
```
Output is like below:
```
{"status":"succ","head":["name","created_time","ntables","vgroups","replica","quorum","days","keep0,keep1,keep(D)","cache(MB)","blocks","minrows","maxrows","wallevel","fsync","comp","cachelast","precision","update","status"],"column_meta":[["name",8,32],["created_time",9,8],["ntables",4,4],["vgroups",4,4],["replica",3,2],["quorum",3,2],["days",3,2],["keep0,keep1,keep(D)",8,24],["cache(MB)",4,4],["blocks",4,4],["minrows",4,4],["maxrows",4,4],["wallevel",2,1],["fsync",4,4],["comp",2,1],["cachelast",2,1],["precision",8,3],["update",2,1],["status",8,10]],"data":[["test","2021-08-18 06:01:11.021",10000,4,1,1,10,"3650,3650,3650",16,6,100,4096,1,3000,2,0,"ms",0,"ready"],["log","2021-08-18 05:51:51.065",4,1,1,1,10,"30,30,30",1,3,100,4096,1,3000,2,0,"us",0,"ready"]],"rows":2}
```
For details of REST API please refer to [REST API](/reference/rest-api/).
### Run TDengine server and taosAdapter inside container
From version 2.4.0.0, in the TDengine Docker image, `taosAdapter` is enabled by default, but can be disabled using environment variable `TAOS_DISABLE_ADAPTER=true` . `taosAdapter` can also be run alone without `taosd` when launching a container.
For the port mapping of `taosAdapter`, please refer to [taosAdapter](/reference/taosadapter/).
- Run both `taosd` and `taosAdapter` (by default) in docker container:
```bash
docker run -d --name tdengine-all -p 6030-6049:6030-6049 -p 6030-6049:6030-6049/udp tdengine/tdengine:2.4.0.4
```
- Run `taosAdapter` only in docker container, `TAOS_FIRST_EP` environment variable needs to be used to specify the container name in which `taosd` is running:
```bash
docker run -d --name tdengine-taosa -p 6041-6049:6041-6049 -p 6041-6049:6041-6049/udp -e TAOS_FIRST_EP=tdengine-all tdengine/tdengine:2.4.0.4 taosadapter
```
- Run `taosd` only in docker container:
```bash
docker run -d --name tdengine-taosd -p 6030-6042:6030-6042 -p 6030-6042:6030-6042/udp -e TAOS_DISABLE_ADAPTER=true tdengine/tdengine:2.4.0.4
```
- Verify the REST interface:
```bash
curl -L -H "Authorization: Basic cm9vdDp0YW9zZGF0YQ==" -d "show databases;" 127.0.0.1:6041/rest/sql
```
Below is an example output:
```
{"status":"succ","head":["name","created_time","ntables","vgroups","replica","quorum","days","keep","cache(MB)","blocks","minrows","maxrows","wallevel","fsync","comp","cachelast","precision","update","status"],"column_meta":[["name",8,32],["created_time",9,8],["ntables",4,4],["vgroups",4,4],["replica",3,2],["quorum",3,2],["days",3,2],["keep",8,24],["cache(MB)",4,4],["blocks",4,4],["minrows",4,4],["maxrows",4,4],["wallevel",2,1],["fsync",4,4],["comp",2,1],["cachelast",2,1],["precision",8,3],["update",2,1],["status",8,10]],"data":[["log","2021-12-28 09:18:55.765",10,1,1,1,10,"30",1,3,100,4096,1,3000,2,0,"us",0,"ready"]],"rows":1}
```
### Use taosBenchmark on host to access TDengine server in container
1. Run `taosBenchmark`, named as `taosdemo` previously, on the host:
```bash
$ taosBenchmark
taosBenchmark is simulating data generated by power equipments monitoring...
host: 127.0.0.1:6030
user: root
password: taosdata
configDir:
resultFile: ./output.txt
thread num of insert data: 10
thread num of create table: 10
top insert interval: 0
number of records per req: 30000
max sql length: 1048576
database count: 1
database[0]:
database[0] name: test
drop: yes
replica: 1
precision: ms
super table count: 1
super table[0]:
stbName: meters
autoCreateTable: no
childTblExists: no
childTblCount: 10000
childTblPrefix: d
dataSource: rand
iface: taosc
insertRows: 10000
interlaceRows: 0
disorderRange: 1000
disorderRatio: 0
maxSqlLen: 1048576
timeStampStep: 1
startTimestamp: 2017-07-14 10:40:00.000
sampleFormat:
sampleFile:
tagsFile:
columnCount: 3
column[0]:FLOAT column[1]:INT column[2]:FLOAT
tagCount: 2
tag[0]:INT tag[1]:BINARY(16)
Press enter key to continue or Ctrl-C to stop
```
Once the execution is finished, a database `test` is created, a STable `meters` is created in database `test`, 10,000 sub tables are created using `meters` as template, named as "d0" to "d9999", while 10,000 rows are inserted into each table, so totally 100,000,000 rows are inserted.
2. Check the data
- **Check database**
```bash
$ taos> show databases;
name | created_time | ntables | vgroups | ···
test | 2021-08-18 06:01:11.021 | 10000 | 6 | ···
log | 2021-08-18 05:51:51.065 | 4 | 1 | ···
```
- **Check STable**
```bash
$ taos> use test;
Database changed.
$ taos> show stables;
name | created_time | columns | tags | tables |
============================================================================================
meters | 2021-08-18 06:01:11.116 | 4 | 2 | 10000 |
Query OK, 1 row(s) in set (0.003259s)
```
- **Check Tables**
```bash
$ taos> select * from test.t0 limit 10;
DB error: Table does not exist (0.002857s)
taos> select * from test.d0 limit 10;
ts | current | voltage | phase |
======================================================================================
2017-07-14 10:40:00.000 | 10.12072 | 223 | 0.34167 |
2017-07-14 10:40:00.001 | 10.16103 | 224 | 0.34445 |
2017-07-14 10:40:00.002 | 10.00204 | 220 | 0.33334 |
2017-07-14 10:40:00.003 | 10.00030 | 220 | 0.33333 |
2017-07-14 10:40:00.004 | 9.84029 | 216 | 0.32222 |
2017-07-14 10:40:00.005 | 9.88028 | 217 | 0.32500 |
2017-07-14 10:40:00.006 | 9.88110 | 217 | 0.32500 |
2017-07-14 10:40:00.007 | 10.08137 | 222 | 0.33889 |
2017-07-14 10:40:00.008 | 10.12063 | 223 | 0.34167 |
2017-07-14 10:40:00.009 | 10.16086 | 224 | 0.34445 |
Query OK, 10 row(s) in set (0.016791s)
```
- **Check tag values of table d0**
```bash
$ taos> select groupid, location from test.d0;
groupid | location |
=================================
0 | California.SanDiego |
Query OK, 1 row(s) in set (0.003490s)
```
### Access TDengine from 3rd party tools
A lot of 3rd party tools can be used to write data into TDengine through `taosAdapter`, for details please refer to [3rd party tools](/third-party/).
There is nothing different from the 3rd party side to access TDengine server inside a container, as long as the end point is specified correctly, the end point should be the FQDN and the mapped port of the host.
## Stop TDengine inside container
```bash
docker stop tdengine
```
- **docker stop**: stop a container
- **tdengine**: container name
docs/en/28-releases.md 0 → 100644
浏览文件 @ fece844f
---
sidebar_label: Releases
title: Released Versions
---
import Release from "/components/ReleaseV3";
<Release versionPrefix="3.0" />
docs/examples/python/connect_native_reference.py
浏览文件 @ fece844f
......@@ -11,10 +11,10 @@ conn: taos.TaosConnection = taos.connect(host="localhost",
server_version = conn.server_info
print("server_version", server_version)
client_version = conn.client_info
print("client_version", client_version) # 2.4.0.16
print("client_version", client_version) # 3.0.0.0
conn.close()
# possible output:
# 2.4.0.16
# 2.4.0.16
# 3.0.0.0
# 3.0.0.0
docs/examples/python/subscribe_demo.py 已删除 100644 → 0
浏览文件 @ b0263a4b
"""
Python asynchronous subscribe demo.
run on Linux system with: python3 subscribe_demo.py
"""
from ctypes import c_void_p
import taos
import time
def query_callback(p_sub, p_result, p_param, code):
"""
:param p_sub: pointer returned by native API -- taos_subscribe
:param p_result: pointer to native TAOS_RES
:param p_param: None
:param code: error code
:return: None
"""
print("in callback")
result = taos.TaosResult(c_void_p(p_result))
# raise exception if error occur
result.check_error(code)
for row in result.rows_iter():
print(row)
print(f"{result.row_count} rows consumed.")
if __name__ == '__main__':
conn = taos.connect()
restart = True
topic = "topic-meter-current-bg"
sql = "select * from power.meters where current > 10" # Error sql
interval = 2000 # consumption interval in microseconds.
_ = conn.subscribe(restart, topic, sql, interval, query_callback)
# Note: we received the return value as _ above, to avoid the TaosSubscription object to be deleted by gc.
while True:
time.sleep(10) # use Ctrl + C to interrupt
docs/zh/05-get-started/03-package.md
浏览文件 @ fece844f
......@@ -67,13 +67,6 @@ install.sh 安装脚本在执行过程中，会通过命令行交互界面询问
</TabItem>
<TabItem label="Windows 安装" value="windows">
1. 从列表中下载获得 exe 安装程序；
<PkgListV3 type={3}/>
2. 运行可执行程序来安装 TDengine。
</TabItem>
<TabItem value="apt-get" label="apt-get">
可以使用 apt-get 工具从官方仓库安装。
......@@ -102,6 +95,15 @@ sudo apt-get install tdengine
:::tip
apt-get 方式只适用于 Debian 或 Ubuntu 系统
::::
</TabItem>
<TabItem label="Windows 安装" value="windows">
注意：目前 TDengine 在 Windows 平台上只支持 Windows server 2016/2019 和 Windows 10/11 系统版本。
1. 从列表中下载获得 exe 安装程序；
<PkgListV3 type={3}/>
2. 运行可执行程序来安装 TDengine。
</TabItem>
</Tabs>
......
docs/zh/05-get-started/_pkg_install.mdx
浏览文件 @ fece844f
......@@ -2,7 +2,7 @@ import PkgList from "/components/PkgList";
TDengine 的安装非常简单，从下载到安装成功仅仅只要几秒钟。
为方便使用，从 2.4.0.10 开始，标准的服务端安装包包含了 taos、taosd、taosAdapter、taosdump、taosBenchmark、TDinsight 安装脚本和示例代码；如果您只需要用到服务端程序和客户端连接的 C/C++ 语言支持，也可以仅下载 lite 版本的安装包。
标准的服务端安装包包含了 taos、taosd、taosAdapter、taosdump、taosBenchmark、TDinsight 安装脚本和示例代码；如果您只需要用到服务端程序和客户端连接的 C/C++ 语言支持，也可以仅下载 lite 版本的安装包。
在安装包格式上，我们提供 tar.gz, rpm 和 deb 格式，为企业客户提供 tar.gz 格式安装包，以方便在特定操作系统上使用。需要注意的是，rpm 和 deb 包不含 taosdump、taosBenchmark 和 TDinsight 安装脚本，这些工具需要通过安装 taosTool 包获得。
......
docs/zh/07-develop/01-connect/index.md
浏览文件 @ fece844f
......@@ -223,7 +223,7 @@ phpize && ./configure && make -j && make install
**手动指定 TDengine 目录：**
```shell
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/2.4.0.0 && make -j && make install
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/3.0.0.0 && make -j && make install
```
> `--with-tdengine-dir=` 后跟上 TDengine 目录。
......
docs/zh/12-taos-sql/10-function.md
浏览文件 @ fece844f
......@@ -846,7 +846,7 @@ SELECT FIRST(field_name) FROM { tb_name | stb_name } [WHERE clause];
### INTERP
```sql
SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [ RANGE(timestamp1,timestamp2) ] [EVERY(interval)] [FILL ({ VALUE | PREV | NULL | LINEAR | NEXT})];
SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] RANGE(timestamp1,timestamp2) EVERY(interval) FILL({ VALUE | PREV | NULL | LINEAR | NEXT});
```
**功能说明**：返回指定时间截面指定列的记录值或插值。
......@@ -855,17 +855,16 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [
**适用数据类型**：数值类型。
**适用于**：表、超级表。
**适用于**：表和超级表。
**使用说明**
- INTERP 用于在指定时间断面获取指定列的记录值，如果该时间断面不存在符合条件的行数据，那么会根据 FILL 参数的设定进行插值。
- INTERP 的输入数据为指定列的数据，可以通过条件语句（where 子句）来对原始列数据进行过滤，如果没有指定过滤条件则输入为全部数据。
- INTERP 的输出时间范围根据 RANGE(timestamp1,timestamp2)字段来指定，需满足 timestamp1<=timestamp2。其中 timestamp1（必选值）为输出时间范围的起始值，即如果 timestamp1 时刻符合插值条件则 timestamp1 为输出的第一条记录，timestamp2（必选值）为输出时间范围的结束值，即输出的最后一条记录的 timestamp 不能大于 timestamp2。如果没有指定 RANGE，那么满足过滤条件的输入数据中第一条记录的 timestamp 即为 timestamp1，最后一条记录的 timestamp 即为 timestamp2，同样也满足 timestamp1 <= timestamp2。
- INTERP 的输出时间范围根据 RANGE(timestamp1,timestamp2)字段来指定，需满足 timestamp1<=timestamp2。其中 timestamp1（必选值）为输出时间范围的起始值，即如果 timestamp1 时刻符合插值条件则 timestamp1 为输出的第一条记录，timestamp2（必选值）为输出时间范围的结束值，即输出的最后一条记录的 timestamp 不能大于 timestamp2。
- INTERP 根据 EVERY 字段来确定输出时间范围内的结果条数，即从 timestamp1 开始每隔固定长度的时间（EVERY 值）进行插值。如果没有指定 EVERY，则默认窗口大小为无穷大，即从 timestamp1 开始只有一个窗口。
- INTERP 根据 FILL 字段来决定在每个符合输出条件的时刻如何进行插值，如果没有 FILL 字段则默认不插值，即输出为原始记录值或不输出（原始记录不存在）。
- INTERP 只能在一个时间序列内进行插值，因此当作用于超级表时必须跟 group by tbname 一起使用，当作用嵌套查询外层时内层子查询不能含 GROUP BY 信息。
- INTERP 的插值结果不受 ORDER BY timestamp 的影响，ORDER BY timestamp 只影响输出结果的排序。
- INTERP 根据 FILL 字段来决定在每个符合输出条件的时刻如何进行插值。
- INTERP 只能在一个时间序列内进行插值，因此当作用于超级表时必须跟 partition by tbname 一起使用。
### LAST
......
docs/zh/12-taos-sql/18-escape.md
浏览文件 @ fece844f
......@@ -15,9 +15,6 @@ title: 转义字符说明
| `\%` | % 规则见下 |
| `\_` | \_ 规则见下 |
:::note
转义符的功能从 2.4.0.4 版本开始
:::
## 转义字符使用规则
......
docs/zh/14-reference/03-connector/php.mdx
浏览文件 @ fece844f
---
sidebar_position: 1
sidebar_label: PHP
sidebar_label: PHP（社区贡献）
title: PHP Connector
---
......@@ -61,7 +61,7 @@ phpize && ./configure && make -j && make install
**手动指定 tdengine 目录：**
```shell
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/2.4.0.0 && make -j && make install
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/3.0.0.0 && make -j && make install
```
> `--with-tdengine-dir=` 后跟上 tdengine 目录。
......
docs/zh/14-reference/03-connector/python.mdx
浏览文件 @ fece844f
......@@ -150,10 +150,19 @@ curl -u root:taosdata http://<FQDN>:<PORT>/rest/sql -d "select server_version()"
```json
{
"status": "succ",
"head": ["server_version()"],
"column_meta": [["server_version()", 8, 8]],
"data": [["2.4.0.16"]],
"code": 0,
"column_meta": [
[
"server_version()",
"VARCHAR",
7
]
],
"data": [
[
"3.0.0.0"
]
],
"rows": 1
}
```
......
docs/zh/14-reference/04-taosadapter.md
浏览文件 @ fece844f
......@@ -30,7 +30,7 @@ taosAdapter 提供以下功能：
### 安装 taosAdapter
taosAdapter 从 TDengine v2.4.0.0 版本开始成为 TDengine 服务端软件 的一部分，如果您使用 TDengine server 您不需要任何额外的步骤来安装 taosAdapter。您可以从[涛思数据官方网站](https://taosdata.com/cn/all-downloads/)下载 TDengine server（taosAdapter 包含在 v2.4.0.0 及以上版本）安装包。如果需要将 taosAdapter 分离部署在 TDengine server 之外的服务器上，则应该在该服务器上安装完整的 TDengine 来安装 taosAdapter。如果您需要使用源代码编译生成 taosAdapter，您可以参考[构建 taosAdapter](https://github.com/taosdata/taosadapter/blob/3.0/BUILD-CN.md)文档。
taosAdapter 是 TDengine 服务端软件 的一部分，如果您使用 TDengine server 您不需要任何额外的步骤来安装 taosAdapter。您可以从[涛思数据官方网站](https://taosdata.com/cn/all-downloads/)下载 TDengine server 安装包。如果需要将 taosAdapter 分离部署在 TDengine server 之外的服务器上，则应该在该服务器上安装完整的 TDengine 来安装 taosAdapter。如果您需要使用源代码编译生成 taosAdapter，您可以参考[构建 taosAdapter](https://github.com/taosdata/taosadapter/blob/3.0/BUILD-CN.md)文档。
### start/stop taosAdapter
......@@ -329,4 +329,4 @@ taosAdapter 通过参数 `restfulRowLimit` 来控制结果的返回条数，-1
| 3 | telegrafUseFieldNum | 请参考 taosAdapter telegraf 配置方法 |
| 4 | restfulRowLimit | restfulRowLimit | 内嵌 httpd 默认输出 10240 行数据，最大允许值为 102400。taosAdapter 也提供 restfulRowLimit 但是默认不做限制。您可以根据实际场景需求进行配置 |
| 5 | httpDebugFlag | 不适用 | httpdDebugFlag 对 taosAdapter 不起作用 |
| 6 | httpDBNameMandatory | 不适用 | taosAdapter 要求 URL 中必须指定数据库名 |
\ No newline at end of file
| 6 | httpDBNameMandatory | 不适用 | taosAdapter 要求 URL 中必须指定数据库名 |
docs/zh/14-reference/07-tdinsight/index.md → docs/zh/14-reference/07-tdinsight/index.mdx
浏览文件 @ fece844f
......@@ -3,19 +3,28 @@ title: TDinsight - 基于Grafana的TDengine零依赖监控解决方案
sidebar_label: TDinsight
---
TDinsight 是使用内置监控数据库和 [Grafana] 对 TDengine 进行监控的解决方案。
TDinsight 是使用监控数据库和 [Grafana] 对 TDengine 进行监控的解决方案。
TDengine 启动后，会自动创建一个监测数据库 `log`，并自动将服务器的 CPU、内存、硬盘空间、带宽、请求数、磁盘读写速度、慢查询等信息定时写入该数据库，并对重要的系统操作（比如登录、创建、删除数据库等）以及各种错误报警信息进行记录。通过 [Grafana] 和 [TDengine 数据源插件](https://github.com/taosdata/grafanaplugin/releases)，TDinsight 将集群状态、节点信息、插入及查询请求、资源使用情况等进行可视化展示，同时还支持 vnode、dnode、mnode 节点状态异常告警，为开发者实时监控 TDengine 集群运行状态提供了便利。本文将指导用户安装 Grafana 服务器并通过 `TDinsight.sh` 安装脚本自动安装 TDengine 数据源插件及部署 TDinsight 可视化面板。
TDengine 通过 [taosKeeper](../taosKeeper) 将服务器的 CPU、内存、硬盘空间、带宽、请求数、磁盘读写速度、慢查询等信息定时写入指定数据库，并对重要的系统操作（比如登录、创建、删除数据库等）以及各种错误报警信息进行记录。通过 [Grafana] 和 [TDengine 数据源插件](https://github.com/taosdata/grafanaplugin/releases)，TDinsight 将集群状态、节点信息、插入及查询请求、资源使用情况等进行可视化展示，同时还支持 vnode、dnode、mnode 节点状态异常告警，为开发者实时监控 TDengine 集群运行状态提供了便利。本文将指导用户安装 Grafana 服务器并通过 `TDinsight.sh` 安装脚本自动安装 TDengine 数据源插件及部署 TDinsight 可视化面板。
## 系统要求
要部署 TDinsight，需要一个单节点的 TDengine 服务器或一个多节点的 [TDengine] 集群，以及一个[Grafana]服务器。此仪表盘需要 TDengine 2.3.3.0 及以上，并启用 `log` 数据库（`monitor = 1`）。
- 单节点的 TDengine 服务器或多节点的 [TDengine] 集群，以及一个[Grafana]服务器。此仪表盘需要 TDengine 3.0.0.0 及以上，并开启监控服务，具体配置请参考：[TDengine 监控配置](../config/#监控相关)。
- taosAdapter 已经安装并正常运行。具体细节请参考：[taosAdapter 使用手册](../taosadapter)
- taosKeeper 已安装并正常运行。具体细节请参考：[taosKeeper 使用手册](../taosKeeper)
记录以下信息：
- taosAdapter 集群 REST API 地址，如：`http://tdengine.local:6041`。
- taosAdapter 集群认证信息，可使用用户名及密码。
- taosKeeper 记录监控指标的数据库名称。
## 安装 Grafana
我们建议在此处使用最新的[Grafana] 7 或 8 版本。您可以在任何[支持的操作系统](https://grafana.com/docs/grafana/latest/installation/requirements/#supported-operating-systems)中，按照 [Grafana 官方文档安装说明](https://grafana.com/docs/grafana/latest/installation/) 安装 [Grafana]。
我们建议在此处使用最新的[Grafana] 8 或 9 版本。您可以在任何[支持的操作系统](https://grafana.com/docs/grafana/latest/installation/requirements/#supported-operating-systems)中，按照 [Grafana 官方文档安装说明](https://grafana.com/docs/grafana/latest/installation/) 安装 [Grafana]。
### 在 Debian 或 Ubuntu 上安装 Grafana
<Tabs defaultValue="debian" groupId="install">
<TabItem value="debian" label="基于 Debian 或 Ubuntu 系统">
对于 Debian 或 Ubuntu 操作系统，建议使用 Grafana 镜像仓库。使用如下命令从零开始安装：
......@@ -31,6 +40,8 @@ sudo apt-get install grafana
```
### 在 CentOS / RHEL 上安装 Grafana
</TabItem>
<TabItem label="redhat" value="基于 CentOS / RHEL 系统">
您可以从官方 YUM 镜像仓库安装。
......@@ -59,7 +70,12 @@ sudo yum install \
https://dl.grafana.com/oss/release/grafana-7.5.11-1.x86_64.rpm
```
## 自动部署 TDinsight
</TabItem>
</Tabs>
<Tabs defaultValue="auto" groupId="deploy">
<TabItem value="auto" label="自动部署 TDinsight">
我们提供了一个自动化安装脚本 [`TDinsight.sh`](https://github.com/taosdata/grafanaplugin/releases/latest/download/TDinsight.sh) 脚本以便用户快速进行安装配置。
......@@ -71,7 +87,7 @@ chmod +x TDinsight.sh
./TDinsight.sh
```
这个脚本会自动下载最新的[Grafana TDengine 数据源插件](https://github.com/taosdata/grafanaplugin/releases/latest) 和 [TDinsight 仪表盘](https://grafana.com/grafana/dashboards/15167) ，将命令行选项中的可配置参数转为 [Grafana Provisioning](https://grafana.com/docs/grafana/latest/administration/provisioning/) 配置文件，以进行自动化部署及更新等操作。利用该脚本提供的告警设置选项，你还可以获得内置的阿里云短信告警通知支持。
这个脚本会自动下载最新的[Grafana TDengine 数据源插件](https://github.com/taosdata/grafanaplugin/releases/latest) 和 [TDinsight 仪表盘](https://github.com/taosdata/grafanaplugin/blob/master/dashboards/TDinsightV3.json) ，将命令行选项中的可配置参数转为 [Grafana Provisioning](https://grafana.com/docs/grafana/latest/administration/provisioning/) 配置文件，以进行自动化部署及更新等操作。利用该脚本提供的告警设置选项，你还可以获得内置的阿里云短信告警通知支持。
假设您在同一台主机上使用 TDengine 和 Grafana 的默认服务。运行 `./TDinsight.sh` 并打开 Grafana 浏览器窗口就可以看到 TDinsight 仪表盘了。
......@@ -106,18 +122,6 @@ Install and configure TDinsight dashboard in Grafana on Ubuntu 18.04/20.04 syste
-E, --external-notifier <string> Apply external notifier uid to TDinsight dashboard.
Aliyun SMS as Notifier:
-s, --sms-enabled To enable tdengine-datasource plugin builtin Aliyun SMS webhook.
-N, --sms-notifier-name <string> Provisioning notifier name.[default: TDinsight Builtin SMS]
-U, --sms-notifier-uid <string> Provisioning notifier uid, use lowercase notifier name by default.
-D, --sms-notifier-is-default Set notifier as default.
-I, --sms-access-key-id <string> Aliyun SMS access key id
-K, --sms-access-key-secret <string> Aliyun SMS access key secret
-S, --sms-sign-name <string> Sign name
-C, --sms-template-code <string> Template code
-T, --sms-template-param <string> Template param, a escaped JSON string like '{"alarm_level":"%s","time":"%s","name":"%s","content":"%s"}'
-B, --sms-phone-numbers <string> Comma-separated numbers list, eg "189xxxxxxxx,132xxxxxxxx"
-L, --sms-listen-addr <string> [default: 127.0.0.1:9100]
```
大多数命令行选项都可以通过环境变量获得同样的效果。
......@@ -136,17 +140,6 @@ Aliyun SMS as Notifier:
| -t | --tdinsight-title | TDINSIGHT_DASHBOARD_TITLE | TDinsight 仪表盘标题。 [默认：TDinsight] |
| -e | --tdinsight-可编辑 | TDINSIGHT_DASHBOARD_EDITABLE | 如果配置仪表盘可以编辑。 [默认值：false] |
| -E | --external-notifier | EXTERNAL_NOTIFIER | 将外部通知程序 uid 应用于 TDinsight 仪表盘。 |
| -s | --sms-enabled | SMS_ENABLED | 启用阿里云短信 webhook 内置的 tdengine-datasource 插件。 |
| -N | --sms-notifier-name | SMS_NOTIFIER_NAME | 供应通知程序名称。[默认：`TDinsight Builtin SMS`] |
| -U | --sms-notifier-uid | SMS_NOTIFIER_UID | "Notification Channel" `uid`，默认使用程序名称的小写，其他字符用 “-” 代替。 |
| -D | --sms-notifier-is-default | SMS_NOTIFIER_IS_DEFAULT | 将内置短信通知设置为默认值。 |
| -I | --sms-access-key-id | SMS_ACCESS_KEY_ID | 阿里云短信访问密钥 id |
| -K | --sms-access-key-secret | SMS_ACCESS_KEY_SECRET | 阿里云短信访问秘钥 |
| -S | --sms-sign-name | SMS_SIGN_NAME | 签名 |
| -C | --sms-template-code | SMS_TEMPLATE_CODE | 模板代码 |
| -T | --sms-template-param | SMS_TEMPLATE_PARAM | 模板参数的 JSON 模板 |
| -B | --sms-phone-numbers | SMS_PHONE_NUMBERS | 逗号分隔的手机号列表，例如`"189xxxxxxxx,132xxxxxxxx"` |
| -L | --sms-listen-addr | SMS_LISTEN_ADDR | 内置 SMS webhook 监听地址，默认为`127.0.0.1:9100` |
假设您在主机 `tdengine` 上启动 TDengine 数据库，HTTP API 端口为 `6041`，用户为 `root1`，密码为 `pass5ord`。执行脚本：
......@@ -166,31 +159,18 @@ curl --no-progress-meter -u admin:admin http://localhost:3000/api/alert-notifica
sudo ./TDinsight.sh -a http://tdengine:6041 -u root1 -p pass5ord -E existing-notifier
```
如果你想使用[阿里云短信](https://www.aliyun.com/product/sms)服务作为通知渠道，你应该使用`-s`标志启用并添加以下参数：
- `-N`：Notification Channel 名，默认为`TDinsight Builtin SMS`。
- `-U`：Channel uid，默认是 `name` 的小写，任何其他字符都替换为 - ，对于默认的 `-N`，其 uid 为 `tdinsight-builtin-sms`。
- `-I`：阿里云短信访问密钥 id。
- `-K`：阿里云短信访问秘钥。
- `-S`：阿里云短信签名。
- `-C`：阿里云短信模板 ID。
- `-T`：阿里云短信模板参数，为 JSON 格式模板，示例如下 `'{"alarm_level":"%s","time":"%s","name":"%s","content":"%s "}'`。有四个参数：告警级别、时间、名称和告警内容。
- `-B`：电话号码列表，以逗号`,`分隔。
如果要监控多个 TDengine 集群，则需要设置多个 TDinsight 仪表盘。设置非默认 TDinsight 需要进行一些更改： `-n` `-i` `-t` 选项需要更改为非默认名称，如果使用 内置短信告警功能，`-N` 和 `-L` 也应该改变。
```bash
sudo ./TDengine.sh -n TDengine-Env1 -a http://another:6041 -u root -p taosdata -i tdinsight-env1 -t 'TDinsight Env1'
# 如果使用内置短信通知
sudo ./TDengine.sh -n TDengine-Env1 -a http://another:6041 -u root -p taosdata -i tdinsight-env1 -t 'TDinsight Env1' \
-s -N 'Env1 SMS' -I xx -K xx -S xx -C SMS_XX -T '' -B 00000000000 -L 127.0.0.01:10611
```
请注意，配置数据源、通知 Channel 和仪表盘在前端是不可更改的。您应该再次通过此脚本更新配置或手动更改 `/etc/grafana/provisioning` 目录（这是 Grafana 的默认目录，根据需要使用`-P`选项更改）中的配置文件。
特别地，当您使用 Grafana Cloud 或其他组织时，`-O` 可用于设置组织 ID。 `-G` 可指定 Grafana 插件安装目录。 `-e` 参数将仪表盘设置为可编辑。
## 手动设置 TDinsight
</TabItem>
<TabItem label="manual" value="手动设置 TDinsight">
### 安装 TDengine 数据源插件
......@@ -247,23 +227,30 @@ sudo systemctl enable grafana-server
![TDengine Database TDinsight 数据源测试](./assets/howto-add-datasource-test.webp)
</TabItem>
</Tabs>
### 导入仪表盘
指向 **+** / **Create** - **import**（或 `/dashboard/import` url）。
在配置 TDengine 数据源界面，点击 **Dashboards** tab。
![TDengine Database TDinsight 导入仪表盘和配置](./assets/import_dashboard.webp)
在 **Import via grafana.com** 位置键入仪表盘 ID `15167` 并 **Load**。
选择 `TDengine for 3.x`，并点击 `import`。
导入完成后，在搜索界面已经出现了 **TDinsight for 3.x** dashboard。
![TDengine Database TDinsight 查看导入结果](./assets/import_dashboard_view.webp)
![通过 grafana.com 导入](./assets/import-dashboard-15167.webp)
进入 TDinsight for 3.x dashboard 后，选择 taosKeeper 中设置的记录监控指标的数据库。
导入完成后，TDinsight 的完整页面视图如下所示。
![TDengine Database TDinsight 选择数据库](./assets/select_dashboard_db.webp)
![TDengine Database TDinsight 显示](./assets/TDinsight-full.webp)
然后可以看到监控结果。
## TDinsight 仪表盘详细信息
TDinsight 仪表盘旨在提供 TDengine 相关资源使用情况[dnodes, mnodes, vnodes](https://www.taosdata.com/cn/documentation/architecture#cluster)或数据库的使用情况和状态。
TDinsight 仪表盘旨在提供 TDengine 相关资源的使用情况和状态，比如 dnodes、 mnodes、 vnodes 和数据库等。
指标详情如下：
......@@ -285,7 +272,6 @@ TDinsight 仪表盘旨在提供 TDengine 相关资源使用情况[dnodes, mnodes
- **Measuring Points Used**：启用告警规则的测点数用量（社区版无数据，默认情况下是健康的）。
- **Grants Expire Time**：启用告警规则的企业版过期时间（社区版无数据，默认情况是健康的）。
- **Error Rate**：启用警报的集群总合错误率（每秒平均错误数）。
- **Variables**：`show variables` 表格展示。
### DNodes 状态
......@@ -294,7 +280,6 @@ TDinsight 仪表盘旨在提供 TDengine 相关资源使用情况[dnodes, mnodes
- **DNodes Status**：`show dnodes` 的简单表格视图。
- **DNodes Lifetime**：从创建 dnode 开始经过的时间。
- **DNodes Number**：DNodes 数量变化。
- **Offline Reason**：如果有任何 dnode 状态为离线，则以饼图形式展示离线原因。
### MNode 概述
......@@ -309,7 +294,6 @@ TDinsight 仪表盘旨在提供 TDengine 相关资源使用情况[dnodes, mnodes
1. **Requests Rate(Inserts per Second)**：平均每秒插入次数。
2. **Requests (Selects)**：查询请求数及变化率（count of second）。
3. **Requests (HTTP)**：HTTP 请求数和请求速率（count of second）。
### 数据库
......@@ -319,9 +303,8 @@ TDinsight 仪表盘旨在提供 TDengine 相关资源使用情况[dnodes, mnodes
1. **STables**：超级表数量。
2. **Total Tables**：所有表数量。
3. **Sub Tables**：所有超级表子表的数量。
4. **Tables**：所有普通表数量随时间变化图。
5. **Tables Number Foreach VGroups**：每个 VGroups 包含的表数量。
3. **Tables**：所有普通表数量随时间变化图。
4. **Tables Number Foreach VGroups**：每个 VGroups 包含的表数量。
### DNode 资源使用情况
......@@ -356,12 +339,11 @@ TDinsight 仪表盘旨在提供 TDengine 相关资源使用情况[dnodes, mnodes
支持监控 taosAdapter 请求统计和状态详情。包括：
1. **http_request**: 包含总请求数，请求失败数以及正在处理的请求数
2. **top 3 request endpoint**: 按终端分组，请求排名前三的数据
3. **Memory Used**: taosAdapter 内存使用情况
4. **latency_quantile(ms)**: (1, 2, 5, 9, 99)阶段的分位数
5. **top 3 failed request endpoint**: 按终端分组，请求失败排名前三的数据
6. **CPU Used**: taosAdapter CPU 使用情况
1. **http_request_inflight**: 即时处理请求数
2. **http_request_total**: 请求总数。
3. **http_request_fail**: 请求总数。
4. **CPU Used**: taosAdapter CPU 使用情况。
5. **Memory Used**: taosAdapter 内存使用情况。
## 升级
......@@ -403,13 +385,6 @@ services:
TDENGINE_API: ${TDENGINE_API}
TDENGINE_USER: ${TDENGINE_USER}
TDENGINE_PASS: ${TDENGINE_PASS}
SMS_ACCESS_KEY_ID: ${SMS_ACCESS_KEY_ID}
SMS_ACCESS_KEY_SECRET: ${SMS_ACCESS_KEY_SECRET}
SMS_SIGN_NAME: ${SMS_SIGN_NAME}
SMS_TEMPLATE_CODE: ${SMS_TEMPLATE_CODE}
SMS_TEMPLATE_PARAM: '${SMS_TEMPLATE_PARAM}'
SMS_PHONE_NUMBERS: $SMS_PHONE_NUMBERS
SMS_LISTEN_ADDR: ${SMS_LISTEN_ADDR}
ports:
- 3000:3000
volumes:
......
docs/zh/14-reference/12-directory.md
浏览文件 @ fece844f
......@@ -30,7 +30,7 @@ TDengine 的所有可执行文件默认存放在 _/usr/local/taos/bin_ 目录下
- _taosd-dump-cfg.gdb_：用于方便调试 taosd 的 gdb 执行脚本。
:::note
2.4.0.0 版本之后的 taosBenchmark 和 taosdump 需要安装独立安装包 taosTools。
taosdump 需要安装独立安装包 taosTools。
:::
......
docs/zh/17-operation/10-monitor.md
浏览文件 @ fece844f
......@@ -2,13 +2,13 @@
title: 系统监控
---
TDengine 启动后，会自动创建一个监测数据库 log，并自动将服务器的 CPU、内存、硬盘空间、带宽、请求数、磁盘读写速度、慢查询等信息定时写入该数据库。TDengine 还将重要的系统操作（比如登录、创建、删除数据库等）日志以及各种错误报警信息记录下来存放在 log 库里。系统管理员可以从 CLI 直接查看这个数据库，也可以在 WEB 通过图形化界面查看这些监测信息。
TDengine 通过 [taosKeeper](/reference/taosKeeper/) 将服务器的 CPU、内存、硬盘空间、带宽、请求数、磁盘读写速度等信息定时写入指定数据库。TDengine 还将重要的系统操作（比如登录、创建、删除数据库等）日志以及各种错误报警信息进行记录。系统管理员可以从 CLI 直接查看这个数据库，也可以在 WEB 通过图形化界面查看这些监测信息。
这些监测信息的采集缺省是打开的，但可以修改配置文件里的选项 monitor 将其关闭或打开。
## TDinsight - 使用监控数据库 + Grafana 对 TDengine 进行监控的解决方案
从 2.3.3.0 开始，监控数据库将提供更多的监控项，您可以从 [TDinsight Grafana Dashboard](https://grafana.com/grafana/dashboards/15167) 了解如何使用 TDinsight 方案对 TDengine 进行监控。
监控数据库将提供更多的监控项，您可以从 [TDinsight Grafana Dashboard](/reference/tdinsight/) 了解如何使用 TDinsight 方案对 TDengine 进行监控。
我们提供了一个自动化脚本 `TDinsight.sh` 对 TDinsight 进行部署。
......@@ -34,21 +34,6 @@ chmod +x TDinsight.sh
sudo ./TDinsight.sh -a http://localhost:6041 -u root -p taosdata -E <notifier uid>
```
- 使用 TDengine 数据源插件内置的阿里云短信告警通知，使用 `-s` 启用之，并设置如下参数：
1. 阿里云短信服务 Key ID，参数 `-I`
2. 阿里云短信服务 Key Secret，参数 `K`
3. 阿里云短信服务签名，参数 `-S`
4. 短信通知模板号，参数 `-C`
5. 短信通知模板输入参数，JSON 格式，参数 `-T`，如 `{"alarm_level":"%s","time":"%s","name":"%s","content":"%s"}`
6. 逗号分隔的通知手机列表，参数 `-B`
```bash
sudo ./TDinsight.sh -a http://localhost:6041 -u root -p taosdata -s \
-I XXXXXXX -K XXXXXXXX -S taosdata -C SMS_1111111 -B 18900000000 \
-T '{"alarm_level":"%s","time":"%s","name":"%s","content":"%s"}'
```
运行程序并重启 Grafana 服务，打开面板：`http://localhost:3000/d/tdinsight`。
更多使用场景和限制请参考[TDinsight](/reference/tdinsight/) 文档。
docs/zh/25-application/01-telegraf.md
浏览文件 @ fece844f
......@@ -34,7 +34,7 @@ IT 运维监测数据通常都是对时间特性比较敏感的数据，例如
### TDengine
从涛思数据官网[下载](http://taosdata.com/cn/all-downloads/)页面下载最新 TDengine-server 2.4.0.x 或以上版本安装。
从涛思数据官网[下载](http://taosdata.com/cn/all-downloads/)页面下载最新 TDengine-server 版本安装。
## 数据链路设置
......@@ -79,4 +79,4 @@ sudo systemctl start telegraf
## 总结
以上演示如何快速搭建一个完整的 IT 运维展示系统。得力于 TDengine 2.4.0.0 版本中新增的 schemaless 协议解析功能，以及强大的生态软件适配能力，用户可以短短数分钟就可以搭建一个高效易用的 IT 运维系统。TDengine 强大的数据写入查询性能和其他丰富功能请参考官方文档和产品落地案例。
以上演示如何快速搭建一个完整的 IT 运维展示系统。得力于 TDengine 的 schemaless 协议解析功能，以及强大的生态软件适配能力，用户可以短短数分钟就可以搭建一个高效易用的 IT 运维系统。TDengine 强大的数据写入查询性能和其他丰富功能请参考官方文档和产品落地案例。
docs/zh/25-application/02-collectd.md
浏览文件 @ fece844f
......@@ -36,7 +36,7 @@ IT 运维监测数据通常都是对时间特性比较敏感的数据，例如
### 安装 TDengine
从涛思数据官网[下载](http://taosdata.com/cn/all-downloads/)页面下载最新 TDengine-server 2.4.0.x 或以上版本安装。
从涛思数据官网[下载](http://taosdata.com/cn/all-downloads/)页面下载最新 TDengine-server 版本安装。
## 数据链路设置
......@@ -90,6 +90,6 @@ repeater 部分添加 { host:'<TDengine server/cluster host>', port: <port for S
## 总结
TDengine 作为新兴的时序大数据平台，具备极强的高性能、高可靠、易管理、易维护的优势。得力于 TDengine 2.4.0.0 版本中新增的 schemaless 协议解析功能，以及强大的生态软件适配能力，用户可以短短数分钟就可以搭建一个高效易用的 IT 运维系统或者适配一个已存在的系统。
TDengine 作为新兴的时序大数据平台，具备极强的高性能、高可靠、易管理、易维护的优势。得力于 TDengine 的 schemaless 协议解析功能，以及强大的生态软件适配能力，用户可以短短数分钟就可以搭建一个高效易用的 IT 运维系统或者适配一个已存在的系统。
TDengine 强大的数据写入查询性能和其他丰富功能请参考官方文档和产品成功落地案例。
docs/zh/27-train-faq/01-faq.md
浏览文件 @ fece844f
......@@ -187,7 +187,7 @@ TDengine 中时间戳的时区总是由客户端进行处理，而与服务端
### 17. 为什么 RESTful 接口无响应、Grafana 无法添加 TDengine 为数据源、TDengineGUI 选了 6041 端口还是无法连接成功？
taosAdapter 从 TDengine 2.4.0.0 版本开始成为 TDengine 服务端软件的组成部分，是 TDengine 集群和应用程序之间的桥梁和适配器。在此之前 RESTful 接口等功能是由 taosd 内置的 HTTP 服务提供的，而如今要实现上述功能需要执行：```systemctl start taosadapter``` 命令来启动 taosAdapter 服务。
这个现象可能是因为 taosAdapter 没有被正确启动引起的，需要执行：```systemctl start taosadapter``` 命令来启动 taosAdapter 服务。
需要说明的是，taosAdapter 的日志路径 path 需要单独配置，默认路径是 /var/log/taos ；日志等级 logLevel 有 8 个等级，默认等级是 info ，配置成 panic 可关闭日志输出。请注意操作系统 / 目录的空间大小，可通过命令行参数、环境变量或配置文件来修改配置，默认配置文件是 /etc/taos/taosadapter.toml 。
......
examples/JDBC/JDBCDemo/pom.xml
浏览文件 @ fece844f
......@@ -17,7 +17,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>2.0.34</version>
<version>3.0.0</version>
</dependency>
</dependencies>
......
examples/JDBC/SpringJdbcTemplate/pom.xml
浏览文件 @ fece844f
......@@ -47,7 +47,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>2.0.18</version>
<version>3.0.0</version>
</dependency>
</dependencies>
......
examples/JDBC/SpringJdbcTemplate/readme.md
浏览文件 @ fece844f
......@@ -10,7 +10,7 @@
```xml
<bean id="dataSource" class="org.springframework.jdbc.datasource.DriverManagerDataSource">
<property name="driverClassName" value="com.taosdata.jdbc.TSDBDriver"></property>
<property name="url" value="jdbc:TAOS://127.0.0.1:6030/log"></property>
<property name="url" value="jdbc:TAOS://127.0.0.1:6030/test"></property>
<property name="username" value="root"></property>
<property name="password" value="taosdata"></property>
</bean>
......@@ -28,5 +28,5 @@ mvn clean package
```
打包成功之后，进入 `target/` 目录下，执行以下命令就可运行测试：
```shell
java -jar SpringJdbcTemplate-1.0-SNAPSHOT-jar-with-dependencies.jar
java -jar target/SpringJdbcTemplate-1.0-SNAPSHOT-jar-with-dependencies.jar
```
\ No newline at end of file
examples/JDBC/SpringJdbcTemplate/src/main/java/com/taosdata/example/jdbcTemplate/App.java
浏览文件 @ fece844f
......@@ -28,7 +28,7 @@ public class App {
//use database
executor.doExecute("use test");
// create table
executor.doExecute("create table if not exists test.weather (ts timestamp, temperature int, humidity float)");
executor.doExecute("create table if not exists test.weather (ts timestamp, temperature float, humidity int)");
WeatherDao weatherDao = ctx.getBean(WeatherDao.class);
Weather weather = new Weather(new Timestamp(new Date().getTime()), random.nextFloat() * 50.0f, random.nextInt(100));
......
examples/JDBC/SpringJdbcTemplate/src/test/java/com/taosdata/example/jdbcTemplate/BatcherInsertTest.java
浏览文件 @ fece844f
......@@ -41,7 +41,7 @@ public class BatcherInsertTest {
//use database
executor.doExecute("use test");
// create table
executor.doExecute("create table if not exists test.weather (ts timestamp, temperature int, humidity float)");
executor.doExecute("create table if not exists test.weather (ts timestamp, temperature float, humidity int)");
}
@Test
......
examples/JDBC/connectionPools/README-cn.md
浏览文件 @ fece844f
......@@ -13,13 +13,13 @@ ConnectionPoolDemo的程序逻辑：
### 如何运行这个例子：
```shell script
mvn clean package assembly:single
java -jar target/connectionPools-1.0-SNAPSHOT-jar-with-dependencies.jar -host 127.0.0.1
mvn clean package
java -jar target/ConnectionPoolDemo-jar-with-dependencies.jar -host 127.0.0.1
```
使用mvn运行ConnectionPoolDemo的main方法，可以指定参数
```shell script
Usage:
java -jar target/connectionPools-1.0-SNAPSHOT-jar-with-dependencies.jar
java -jar target/ConnectionPoolDemo-jar-with-dependencies.jar
-host : hostname
-poolType <c3p0| dbcp| druid| hikari>
-poolSize <poolSize>
......
examples/JDBC/connectionPools/pom.xml
浏览文件 @ fece844f
......@@ -18,7 +18,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>2.0.18</version>
<version>3.0.0</version>
</dependency>
<!-- druid -->
<dependency>
......
examples/JDBC/mybatisplus-demo/pom.xml
浏览文件 @ fece844f
......@@ -47,7 +47,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>2.0.18</version>
<version>3.0.0</version>
</dependency>
<dependency>
......
examples/JDBC/mybatisplus-demo/readme 0 → 100644
浏览文件 @ fece844f
# 使用说明
## 创建使用db
```shell
$ taos
> create database mp_test
```
## 执行测试用例
```shell
$ mvn clean test
```
\ No newline at end of file
examples/JDBC/mybatisplus-demo/src/main/java/com/taosdata/example/mybatisplusdemo/mapper/WeatherMapper.java
浏览文件 @ fece844f
......@@ -2,7 +2,17 @@ package com.taosdata.example.mybatisplusdemo.mapper;
import com.baomidou.mybatisplus.core.mapper.BaseMapper;
import com.taosdata.example.mybatisplusdemo.domain.Weather;
import org.apache.ibatis.annotations.Insert;
import org.apache.ibatis.annotations.Update;
public interface WeatherMapper extends BaseMapper<Weather> {
@Update("CREATE TABLE if not exists weather(ts timestamp, temperature float, humidity int, location nchar(100))")
int createTable();
@Insert("insert into weather (ts, temperature, humidity, location) values(#{ts}, #{temperature}, #{humidity}, #{location})")
int insertOne(Weather one);
@Update("drop table if exists weather")
void dropTable();
}
examples/JDBC/mybatisplus-demo/src/main/resources/application.yml
浏览文件 @ fece844f
......@@ -2,7 +2,7 @@ spring:
datasource:
driver-class-name: com.taosdata.jdbc.TSDBDriver
url: jdbc:TAOS://localhost:6030/mp_test?charset=UTF-8&locale=en_US.UTF-8&timezone=UTC-8
user: root
username: root
password: taosdata
druid:
......
examples/JDBC/mybatisplus-demo/src/test/java/com/taosdata/example/mybatisplusdemo/mapper/TemperatureMapperTest.java
浏览文件 @ fece844f
......@@ -82,27 +82,15 @@ public class TemperatureMapperTest {
Assert.assertEquals(1, affectRows);
}
/***
* test SelectOne
* **/
@Test
public void testSelectOne() {
QueryWrapper<Temperature> wrapper = new QueryWrapper<>();
wrapper.eq("location", "beijing");
Temperature one = mapper.selectOne(wrapper);
System.out.println(one);
Assert.assertNotNull(one);
}
/***
* test select By map
* ***/
@Test
public void testSelectByMap() {
Map<String, Object> map = new HashMap<>();
map.put("location", "beijing");
map.put("location", "北京");
List<Temperature> temperatures = mapper.selectByMap(map);
Assert.assertEquals(1, temperatures.size());
Assert.assertTrue(temperatures.size() > 1);
}
/***
......@@ -120,7 +108,7 @@ public class TemperatureMapperTest {
@Test
public void testSelectCount() {
int count = mapper.selectCount(null);
Assert.assertEquals(5, count);
Assert.assertEquals(10, count);
}
/****
......
examples/JDBC/mybatisplus-demo/src/test/java/com/taosdata/example/mybatisplusdemo/mapper/WeatherMapperTest.java
浏览文件 @ fece844f
......@@ -6,6 +6,7 @@ import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
import com.taosdata.example.mybatisplusdemo.domain.Weather;
import org.junit.Assert;
import org.junit.Test;
import org.junit.Before;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
......@@ -26,6 +27,18 @@ public class WeatherMapperTest {
@Autowired
private WeatherMapper mapper;
@Before
public void createTable(){
mapper.dropTable();
mapper.createTable();
Weather one = new Weather();
one.setTs(new Timestamp(1605024000000l));
one.setTemperature(12.22f);
one.setLocation("望京");
one.setHumidity(100);
mapper.insertOne(one);
}
@Test
public void testSelectList() {
List<Weather> weathers = mapper.selectList(null);
......@@ -46,20 +59,20 @@ public class WeatherMapperTest {
@Test
public void testSelectOne() {
QueryWrapper<Weather> wrapper = new QueryWrapper<>();
wrapper.eq("location", "beijing");
wrapper.eq("location", "望京");
Weather one = mapper.selectOne(wrapper);
System.out.println(one);
Assert.assertEquals(12.22f, one.getTemperature(), 0.00f);
Assert.assertEquals("beijing", one.getLocation());
Assert.assertEquals("望京", one.getLocation());
}
@Test
public void testSelectByMap() {
Map<String, Object> map = new HashMap<>();
map.put("location", "beijing");
List<Weather> weathers = mapper.selectByMap(map);
Assert.assertEquals(1, weathers.size());
}
// @Test
// public void testSelectByMap() {
// Map<String, Object> map = new HashMap<>();
// map.put("location", "beijing");
// List<Weather> weathers = mapper.selectByMap(map);
// Assert.assertEquals(1, weathers.size());
// }
@Test
public void testSelectObjs() {
......
examples/JDBC/readme.md
浏览文件 @ fece844f
......@@ -10,4 +10,4 @@
| 6 | taosdemo | This is an internal tool for testing Our JDBC-JNI, JDBC-RESTful, RESTful interfaces |
more detail: https://www.taosdata.com/cn//documentation20/connector-java/
\ No newline at end of file
more detail: https://docs.taosdata.com/reference/connector/java/
\ No newline at end of file
examples/JDBC/springbootdemo/pom.xml
浏览文件 @ fece844f
......@@ -68,7 +68,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>2.0.34</version>
<version>3.0.0</version>
</dependency>
<dependency>
......
examples/JDBC/springbootdemo/readme.md
浏览文件 @ fece844f
## TDengine SpringBoot + Mybatis Demo
## 需要提前创建 test 数据库
### 配置 application.properties
```properties
# datasource config
spring.datasource.driver-class-name=com.taosdata.jdbc.TSDBDriver
spring.datasource.url=jdbc:TAOS://127.0.0.1:6030/log
spring.datasource.url=jdbc:TAOS://127.0.0.1:6030/test
spring.datasource.username=root
spring.datasource.password=taosdata
......
examples/JDBC/springbootdemo/src/main/java/com/taosdata/example/springbootdemo/controller/WeatherController.java
浏览文件 @ fece844f
......@@ -6,7 +6,6 @@ import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;
import java.util.List;
import java.util.Map;
@RequestMapping("/weather")
@RestController
......
examples/JDBC/springbootdemo/src/main/java/com/taosdata/example/springbootdemo/dao/WeatherMapper.xml
浏览文件 @ fece844f
......@@ -10,8 +10,7 @@
</resultMap>
<select id="lastOne" resultType="java.util.Map">
select last_row(*), location, groupid
from test.weather
select last_row(ts) as ts, last_row(temperature) as temperature, last_row(humidity) as humidity, last_row(note) as note,last_row(location) as location , last_row(groupid) as groupid from test.weather;
</select>
<update id="dropDB">
......
examples/JDBC/springbootdemo/src/main/resources/application.properties
浏览文件 @ fece844f
......@@ -5,7 +5,7 @@
#spring.datasource.password=taosdata
# datasource config - JDBC-RESTful
spring.datasource.driver-class-name=com.taosdata.jdbc.rs.RestfulDriver
spring.datasource.url=jdbc:TAOS-RS://localhsot:6041/test?timezone=UTC-8&charset=UTF-8&locale=en_US.UTF-8
spring.datasource.url=jdbc:TAOS-RS://localhost:6041/test?timezone=UTC-8&charset=UTF-8&locale=en_US.UTF-8
spring.datasource.username=root
spring.datasource.password=taosdata
spring.datasource.druid.initial-size=5
......
examples/JDBC/taosdemo/pom.xml
浏览文件 @ fece844f
......@@ -67,7 +67,7 @@
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>2.0.20</version>
<version>3.0.0</version>
<!-- <scope>system</scope>-->
<!-- <systemPath>${project.basedir}/src/main/resources/lib/taos-jdbcdriver-2.0.15-dist.jar</systemPath>-->
</dependency>
......
examples/JDBC/taosdemo/readme.md
浏览文件 @ fece844f
......@@ -2,9 +2,9 @@
cd tests/examples/JDBC/taosdemo
mvn clean package -Dmaven.test.skip=true
# 先建表，再插入的
java -jar target/taosdemo-2.0-jar-with-dependencies.jar -host [hostname] -database [database] -doCreateTable true -superTableSQL "create table weather(ts timestamp, f1 int) tags(t1 nchar(4))" -numOfTables 1000 -numOfRowsPerTable 100000000 -numOfThreadsForInsert 10 -numOfTablesPerSQL 10 -numOfValuesPerSQL 100
java -jar target/taosdemo-2.0.1-jar-with-dependencies.jar -host [hostname] -database [database] -doCreateTable true -superTableSQL "create table weather(ts timestamp, f1 int) tags(t1 nchar(4))" -numOfTables 1000 -numOfRowsPerTable 100000000 -numOfThreadsForInsert 10 -numOfTablesPerSQL 10 -numOfValuesPerSQL 100
# 不建表，直接插入的
java -jar target/taosdemo-2.0-jar-with-dependencies.jar -host [hostname] -database [database] -doCreateTable false -superTableSQL "create table weather(ts timestamp, f1 int) tags(t1 nchar(4))" -numOfTables 1000 -numOfRowsPerTable 100000000 -numOfThreadsForInsert 10 -numOfTablesPerSQL 10 -numOfValuesPerSQL 100
java -jar target/taosdemo-2.0.1-jar-with-dependencies.jar -host [hostname] -database [database] -doCreateTable false -superTableSQL "create table weather(ts timestamp, f1 int) tags(t1 nchar(4))" -numOfTables 1000 -numOfRowsPerTable 100000000 -numOfThreadsForInsert 10 -numOfTablesPerSQL 10 -numOfValuesPerSQL 100
```
需求：
......
examples/JDBC/taosdemo/src/main/java/com/taosdata/taosdemo/TaosDemoApplication.java
浏览文件 @ fece844f
......@@ -32,8 +32,10 @@ public class TaosDemoApplication {
System.exit(0);
}
// 初始化
final DataSource dataSource = DataSourceFactory.getInstance(config.host, config.port, config.user, config.password);
if (config.executeSql != null && !config.executeSql.isEmpty() && !config.executeSql.replaceAll("\\s", "").isEmpty()) {
final DataSource dataSource = DataSourceFactory.getInstance(config.host, config.port, config.user,
config.password);
if (config.executeSql != null && !config.executeSql.isEmpty()
&& !config.executeSql.replaceAll("\\s", "").isEmpty()) {
Thread task = new Thread(new SqlExecuteTask(dataSource, config.executeSql));
task.start();
try {
......@@ -55,7 +57,7 @@ public class TaosDemoApplication {
databaseParam.put("keep", Integer.toString(config.keep));
databaseParam.put("days", Integer.toString(config.days));
databaseParam.put("replica", Integer.toString(config.replica));
//TODO: other database parameters
// TODO: other database parameters
databaseService.createDatabase(databaseParam);
databaseService.useDatabase(config.database);
long end = System.currentTimeMillis();
......@@ -70,11 +72,13 @@ public class TaosDemoApplication {
if (config.database != null && !config.database.isEmpty())
superTableMeta.setDatabase(config.database);
} else if (config.numOfFields == 0) {
String sql = "create table " + config.database + "." + config.superTable + " (ts timestamp, temperature float, humidity int) tags(location nchar(64), groupId int)";
String sql = "create table " + config.database + "." + config.superTable
+ " (ts timestamp, temperature float, humidity int) tags(location nchar(64), groupId int)";
superTableMeta = SuperTableMetaGenerator.generate(sql);
} else {
// create super table with specified field size and tag size
superTableMeta = SuperTableMetaGenerator.generate(config.database, config.superTable, config.numOfFields, config.prefixOfFields, config.numOfTags, config.prefixOfTags);
superTableMeta = SuperTableMetaGenerator.generate(config.database, config.superTable, config.numOfFields,
config.prefixOfFields, config.numOfTags, config.prefixOfTags);
}
/**********************************************************************************/
// 建表
......@@ -84,7 +88,8 @@ public class TaosDemoApplication {
superTableService.create(superTableMeta);
if (!config.autoCreateTable) {
// 批量建子表
subTableService.createSubTable(superTableMeta, config.numOfTables, config.prefixOfTable, config.numOfThreadsForCreate);
subTableService.createSubTable(superTableMeta, config.numOfTables, config.prefixOfTable,
config.numOfThreadsForCreate);
}
}
end = System.currentTimeMillis();
......@@ -93,7 +98,7 @@ public class TaosDemoApplication {
// 插入
long tableSize = config.numOfTables;
int threadSize = config.numOfThreadsForInsert;
long startTime = getProperStartTime(config.startTime, config.keep);
long startTime = getProperStartTime(config.startTime, config.days);
if (tableSize < threadSize)
threadSize = (int) tableSize;
......@@ -101,13 +106,13 @@ public class TaosDemoApplication {
start = System.currentTimeMillis();
// multi threads to insert
int affectedRows = subTableService.insertMultiThreads(superTableMeta, threadSize, tableSize, startTime, gap, config);
int affectedRows = subTableService.insertMultiThreads(superTableMeta, threadSize, tableSize, startTime, gap,
config);
end = System.currentTimeMillis();
logger.info("insert " + affectedRows + " rows, time cost: " + (end - start) + " ms");
/**********************************************************************************/
// 查询
/**********************************************************************************/
// 删除表
if (config.dropTable) {
......
examples/JDBC/taosdemo/src/main/java/com/taosdata/taosdemo/service/QueryService.java
浏览文件 @ fece844f
package com.taosdata.taosdemo.service;
import com.taosdata.jdbc.utils.SqlSyntaxValidator;
import javax.sql.DataSource;
import java.sql.*;
import java.util.ArrayList;
......@@ -23,10 +21,6 @@ public class QueryService {
Boolean[] ret = new Boolean[sqls.length];
for (int i = 0; i < sqls.length; i++) {
ret[i] = true;
if (!SqlSyntaxValidator.isValidForExecuteQuery(sqls[i])) {
ret[i] = false;
continue;
}
try (Connection conn = dataSource.getConnection(); Statement stmt = conn.createStatement()) {
stmt.executeQuery(sqls[i]);
} catch (SQLException e) {
......
examples/JDBC/taosdemo/src/main/java/com/taosdata/taosdemo/utils/SqlSpeller.java
浏览文件 @ fece844f
......@@ -15,9 +15,12 @@ public class SqlSpeller {
StringBuilder sb = new StringBuilder();
sb.append("create database if not exists ").append(map.get("database")).append(" ");
if (map.containsKey("keep"))
sb.append("keep ").append(map.get("keep")).append(" ");
if (map.containsKey("days"))
sb.append("days ").append(map.get("days")).append(" ");
sb.append("keep ");
if (map.containsKey("days")) {
sb.append(map.get("days")).append("d ");
} else {
sb.append(" ");
}
if (map.containsKey("replica"))
sb.append("replica ").append(map.get("replica")).append(" ");
if (map.containsKey("cache"))
......@@ -29,7 +32,7 @@ public class SqlSpeller {
if (map.containsKey("maxrows"))
sb.append("maxrows ").append(map.get("maxrows")).append(" ");
if (map.containsKey("precision"))
sb.append("precision ").append(map.get("precision")).append(" ");
sb.append("precision '").append(map.get("precision")).append("' ");
if (map.containsKey("comp"))
sb.append("comp ").append(map.get("comp")).append(" ");
if (map.containsKey("walLevel"))
......@@ -46,11 +49,13 @@ public class SqlSpeller {
// create table if not exists xx.xx using xx.xx tags(x,x,x)
public static String createTableUsingSuperTable(SubTableMeta subTableMeta) {
StringBuilder sb = new StringBuilder();
sb.append("create table if not exists ").append(subTableMeta.getDatabase()).append(".").append(subTableMeta.getName()).append(" ");
sb.append("using ").append(subTableMeta.getDatabase()).append(".").append(subTableMeta.getSupertable()).append(" ");
// String tagStr = subTableMeta.getTags().stream().filter(Objects::nonNull)
// .map(tagValue -> tagValue.getName() + " '" + tagValue.getValue() + "' ")
// .collect(Collectors.joining(",", "(", ")"));
sb.append("create table if not exists ").append(subTableMeta.getDatabase()).append(".")
.append(subTableMeta.getName()).append(" ");
sb.append("using ").append(subTableMeta.getDatabase()).append(".").append(subTableMeta.getSupertable())
.append(" ");
// String tagStr = subTableMeta.getTags().stream().filter(Objects::nonNull)
// .map(tagValue -> tagValue.getName() + " '" + tagValue.getValue() + "' ")
// .collect(Collectors.joining(",", "(", ")"));
sb.append("tags ").append(tagValues(subTableMeta.getTags()));
return sb.toString();
}
......@@ -63,7 +68,7 @@ public class SqlSpeller {
return sb.toString();
}
//f1, f2, f3
// f1, f2, f3
private static String fieldValues(List<FieldValue> fields) {
return IntStream.range(0, fields.size()).mapToObj(i -> {
if (i == 0) {
......@@ -73,13 +78,13 @@ public class SqlSpeller {
}
}).collect(Collectors.joining(",", "(", ")"));
// return fields.stream()
// .filter(Objects::nonNull)
// .map(fieldValue -> "'" + fieldValue.getValue() + "'")
// .collect(Collectors.joining(",", "(", ")"));
// return fields.stream()
// .filter(Objects::nonNull)
// .map(fieldValue -> "'" + fieldValue.getValue() + "'")
// .collect(Collectors.joining(",", "(", ")"));
}
//(f1, f2, f3),(f1, f2, f3)
// (f1, f2, f3),(f1, f2, f3)
private static String rowValues(List<RowValue> rowValues) {
return rowValues.stream().filter(Objects::nonNull)
.map(rowValue -> fieldValues(rowValue.getFields()))
......@@ -89,8 +94,10 @@ public class SqlSpeller {
// insert into xx.xxx using xx.xx tags(x,x,x) values(x,x,x),(x,x,x)...
public static String insertOneTableMultiValuesUsingSuperTable(SubTableValue subTableValue) {
StringBuilder sb = new StringBuilder();
sb.append("insert into ").append(subTableValue.getDatabase()).append(".").append(subTableValue.getName()).append(" ");
sb.append("using ").append(subTableValue.getDatabase()).append(".").append(subTableValue.getSupertable()).append(" ");
sb.append("insert into ").append(subTableValue.getDatabase()).append(".").append(subTableValue.getName())
.append(" ");
sb.append("using ").append(subTableValue.getDatabase()).append(".").append(subTableValue.getSupertable())
.append(" ");
sb.append("tags ").append(tagValues(subTableValue.getTags()) + " ");
sb.append("values ").append(rowValues(subTableValue.getValues()));
return sb.toString();
......@@ -126,7 +133,8 @@ public class SqlSpeller {
// create table if not exists xx.xx (f1 xx,f2 xx...) tags(t1 xx, t2 xx...)
public static String createSuperTable(SuperTableMeta tableMetadata) {
StringBuilder sb = new StringBuilder();
sb.append("create table if not exists ").append(tableMetadata.getDatabase()).append(".").append(tableMetadata.getName());
sb.append("create table if not exists ").append(tableMetadata.getDatabase()).append(".")
.append(tableMetadata.getName());
String fields = tableMetadata.getFields().stream()
.filter(Objects::nonNull).map(field -> field.getName() + " " + field.getType() + " ")
.collect(Collectors.joining(",", "(", ")"));
......@@ -139,10 +147,10 @@ public class SqlSpeller {
return sb.toString();
}
public static String createTable(TableMeta tableMeta) {
StringBuilder sb = new StringBuilder();
sb.append("create table if not exists ").append(tableMeta.getDatabase()).append(".").append(tableMeta.getName()).append(" ");
sb.append("create table if not exists ").append(tableMeta.getDatabase()).append(".").append(tableMeta.getName())
.append(" ");
String fields = tableMeta.getFields().stream()
.filter(Objects::nonNull).map(field -> field.getName() + " " + field.getType() + " ")
.collect(Collectors.joining(",", "(", ")"));
......@@ -179,16 +187,17 @@ public class SqlSpeller {
public static String insertMultiTableMultiValuesWithColumns(List<TableValue> tables) {
StringBuilder sb = new StringBuilder();
sb.append("insert into ").append(tables.stream().filter(Objects::nonNull)
.map(table -> table.getDatabase() + "." + table.getName() + " " + columnNames(table.getColumns()) + " values " + rowValues(table.getValues()))
.map(table -> table.getDatabase() + "." + table.getName() + " " + columnNames(table.getColumns())
+ " values " + rowValues(table.getValues()))
.collect(Collectors.joining(" ")));
return sb.toString();
}
public static String insertMultiTableMultiValues(List<TableValue> tables) {
StringBuilder sb = new StringBuilder();
sb.append("insert into ").append(tables.stream().filter(Objects::nonNull).map(table ->
table.getDatabase() + "." + table.getName() + " values " + rowValues(table.getValues())
).collect(Collectors.joining(" ")));
sb.append("insert into ").append(tables.stream().filter(Objects::nonNull)
.map(table -> table.getDatabase() + "." + table.getName() + " values " + rowValues(table.getValues()))
.collect(Collectors.joining(" ")));
return sb.toString();
}
}
examples/JDBC/taosdemo/src/main/resources/application.properties
浏览文件 @ fece844f
jdbc.driver=com.taosdata.jdbc.rs.RestfulDriver
#jdbc.driver=com.taosdata.jdbc.TSDBDriver
# jdbc.driver=com.taosdata.jdbc.rs.RestfulDriver
jdbc.driver=com.taosdata.jdbc.TSDBDriver
hikari.maximum-pool-size=20
hikari.minimum-idle=20
hikari.max-lifetime=0
\ No newline at end of file
examples/JDBC/taosdemo/src/test/java/com/taosdata/taosdemo/service/TableServiceTest.java 已删除 100644 → 0
浏览文件 @ b0263a4b
package com.taosdata.taosdemo.service;
import com.taosdata.taosdemo.domain.TableMeta;
import org.junit.Before;
import org.junit.Test;
import java.util.ArrayList;
import java.util.List;
public class TableServiceTest {
private TableService tableService;
private List<TableMeta> tables;
@Before
public void before() {
tables = new ArrayList<>();
for (int i = 0; i < 1; i++) {
TableMeta tableMeta = new TableMeta();
tableMeta.setDatabase("test");
tableMeta.setName("weather" + (i + 1));
tables.add(tableMeta);
}
}
@Test
public void testCreate() {
tableService.create(tables);
}
}
\ No newline at end of file
include/libs/function/function.h
浏览文件 @ fece844f
......@@ -142,6 +142,7 @@ typedef struct SqlFunctionCtx {
struct SSDataBlock *pDstBlock; // used by indifinite rows function to set selectivity
int32_t curBufPage;
bool increase;
bool isStream;
char udfName[TSDB_FUNC_NAME_LEN];
} SqlFunctionCtx;
......
include/libs/nodes/querynodes.h
浏览文件 @ fece844f
......@@ -276,6 +276,7 @@ typedef struct SSelectStmt {
bool hasLastRowFunc;
bool hasTimeLineFunc;
bool hasUdaf;
bool hasStateKey;
bool onlyHasKeepOrderFunc;
bool groupSort;
} SSelectStmt;
......
include/util/taoserror.h
浏览文件 @ fece844f
此差异已折叠。
include/util/tdef.h
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source/client/src/clientImpl.c
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此差异已折叠。
source/client/src/clientMain.c
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source/libs/catalog/src/catalog.c
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source/libs/command/src/explain.c
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source/libs/executor/inc/executil.h
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此差异已折叠。
source/libs/executor/src/executil.c
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source/libs/executor/src/executor.c
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此差异已折叠。
source/libs/executor/src/tfill.c
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source/libs/parser/src/parInsert.c
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此差异已折叠。
source/libs/parser/src/parUtil.c
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source/libs/qworker/src/qworker.c
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source/libs/scheduler/inc/schInt.h
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source/libs/scheduler/src/schTask.c
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source/libs/sync/inc/syncSnapshot.h
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source/libs/sync/src/syncMain.c
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source/libs/sync/src/syncRaftCfg.c
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source/libs/sync/src/syncSnapshot.c
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