@@ -277,7 +277,7 @@ If TDengine shell connects the server successfully, welcome messages and version
...
@@ -277,7 +277,7 @@ If TDengine shell connects the server successfully, welcome messages and version
## Install TDengine by apt-get
## Install TDengine by apt-get
If you use Debian or Ubuntu system, you can use 'apt-get' command to intall TDengine from official repository. Please use following commands to setup:
If you use Debian or Ubuntu system, you can use 'apt-get' command to install TDengine from official repository. Please use following commands to setup:
Enter FQDN:port (like h1.taosdata.com:6030) of an existing TDengine cluster node to join OR leave it blank to build one :hostname.taosdata.com:7030
To configure TDengine : edit /etc/taos/taos.cfg
To start TDengine : sudo systemctl start taosd
To access TDengine : use taos in shell
Please run: taos -h hostname.taosdata.com:7030 to login into cluster, then execute : create dnode 'newDnodeFQDN:port'; in TAOS shell to add this new node into the clsuter
TDengine is installed successfully!
```
说明：install.sh 安装脚本在执行过程中，会通过命令行交互界面询问一些配置信息。如果希望采取无交互安装方式，那么可以用 -e no 参数来执行 install.sh 脚本。运行 ./install.sh -h 指令可以查看所有参数的详细说明信息。
如果客户端和服务端运行在不同的电脑上，可以单独安装客户端。下载时请注意，所选择的客户端版本号应该和在上面下载的服务端版本号精确匹配。Linux 和 Windows 安装包如下（其中 lite 版本的安装包仅带有 C/C++ 语言的连接支持，而标准版本的安装包还包含 Java、Python、Go、Node.js 等编程语言的连接器支持和示例代码）：
TDengine is a highly efficient platform to store, query, and analyze time-series data. It is specially designed and optimized for IoT, Internet of Vehicles, Industrial IoT, IT Infrastructure and Application Monitoring, etc. It works like a relational database, such as MySQL, but you are strongly encouraged to read through the following documentation before you experience it, especially the Data Modeling sections. In addition to this document, you should also download and read the technology white paper.
TDengine is a highly efficient platform to store, query, and analyze time-series data. It is specially designed and optimized for IoT, Internet of Vehicles, Industrial IoT, IT Infrastructure and Application Monitoring, etc. It works like a relational database, such as MySQL, but you are strongly encouraged to read through the following documentation before you experience it, especially the Data Modeling sections. In addition to this document, you should also download and read the technology white paper.
## [TDengine Introduction](/evaluation)
## [TDengine Introduction](/evaluation)
*[TDengine Introduction and Features](/evaluation#intro)
*[TDengine Introduction and Features](/evaluation#intro)
...
@@ -84,7 +85,7 @@ TDengine is a highly efficient platform to store, query, and analyze time-series
...
@@ -84,7 +85,7 @@ TDengine is a highly efficient platform to store, query, and analyze time-series
*[taosAdapter](/tools/adapter): a bridge/adapter between TDengine cluster and applications.
*[taosAdapter](/tools/adapter): a bridge/adapter between TDengine cluster and applications.
*[TDinsight](/tools/insight): monitoring TDengine cluster with Grafana.
*[TDinsight](/tools/insight): monitoring TDengine cluster with Grafana.
*[taosdump](/tools/taosdump): backup tool for TDengine. Please install `taosTools` package for it.
*[taosdump](/tools/taosdump): backup tool for TDengine. Please install `taosTools` package for it.
*[taosBenchmark](/tools/taosbenchmark): stress test tool for TDengine. Please install `taosTools` package for it.
*[taosBenchmark](/tools/taosbenchmark): stress test tool for TDengine.
## [Connections with Other Tools](/connections)
## [Connections with Other Tools](/connections)
...
@@ -92,6 +93,8 @@ TDengine is a highly efficient platform to store, query, and analyze time-series
...
@@ -92,6 +93,8 @@ TDengine is a highly efficient platform to store, query, and analyze time-series
-[MATLAB](/connections#matlab): access data stored in TDengine server via JDBC configured within MATLAB
-[MATLAB](/connections#matlab): access data stored in TDengine server via JDBC configured within MATLAB
-[R](/connections#r): access data stored in TDengine server via JDBC configured within R
-[R](/connections#r): access data stored in TDengine server via JDBC configured within R
-[IDEA Database](https://www.taosdata.com/blog/2020/08/27/1767.html): use TDengine visually through IDEA Database Management Tool
-[IDEA Database](https://www.taosdata.com/blog/2020/08/27/1767.html): use TDengine visually through IDEA Database Management Tool
-[TDengineGUI](https://github.com/skye0207/TDengineGUI): a TDengine management tool with Graphical User Interface
-[DataX](https://github.com/taosdata/datax): a data immigaration tool with TDeninge supported
## [Installation and Management of TDengine Cluster](/cluster)
## [Installation and Management of TDengine Cluster](/cluster)
...
@@ -118,6 +121,12 @@ TDengine is a highly efficient platform to store, query, and analyze time-series
...
@@ -118,6 +121,12 @@ TDengine is a highly efficient platform to store, query, and analyze time-series
-[File Directory Structure](/administrator#directories): directories where TDengine data files and configuration files located
-[File Directory Structure](/administrator#directories): directories where TDengine data files and configuration files located
-[Parameter Limits and Reserved Keywords](/administrator#keywords): TDengine’s list of parameter limits and reserved keywords
-[Parameter Limits and Reserved Keywords](/administrator#keywords): TDengine’s list of parameter limits and reserved keywords
## Rapidly build an IT DevOps system with TDengine
*[devops](/devops/telegraf): Rapidly build an IT DevOps system with TDengine + Telegraf + Grafana
*[devops](/devops/collectd): Rapidly build a IT DevOps system with TDengine + collectd/StatsD + Grafana
*[immigration](/devops/immigrate): Best practice of immigration from OpenTSDB to TDengine
## Performance: TDengine vs Others
## Performance: TDengine vs Others
-[Performance: TDengine vs OpenTSDB](https://www.taosdata.com/blog/2019/09/12/710.html)
-[Performance: TDengine vs OpenTSDB](https://www.taosdata.com/blog/2019/09/12/710.html)
While it is not recommended to deploy TDengine services via Docker in a production environment, Docker tools do a good job of shielding the environmental differences in the underlying operating system and are well suited for use in development testing or first-time experience with the toolset for installing and running TDengine. In particular, Docker makes it relatively easy to try TDengine on Mac OSX and Windows systems without having to install a virtual machine or rent an additional Linux server. In addition, starting from version 2.0.14.0, TDengine provides images that support both X86-64, X86, arm64, and arm32 platforms, so non-mainstream computers that can run docker, such as NAS, Raspberry Pi, and embedded development boards, can also easily experience TDengine based on this document.
While it is not recommended to deploy TDengine services via Docker in a production environment, Docker tools do a good job of shielding the environmental differences in the underlying operating system and are well suited for use in development testing or first-time taste with the toolset for installing and running TDengine. In particular, Docker makes it relatively easy to try TDengine on Mac OSX and Windows systems without having to install a virtual machine or rent an additional Linux server. In addition, starting from version 2.0.14.0, TDengine provides images that support both X86-64, X86, arm64, and arm32 platforms, so non-mainstream computers that can run docker, such as NAS, Raspberry Pi, and embedded development boards, can also easily taste TDengine based on this document.
The following article explains how to quickly build a single-node TDengine runtime environment via Docker to support development and testing through a Step by Step style introduction.
The following article explains how to quickly build a single-node TDengine runtime environment via Docker to support development and testing through a Step by Step style introduction.
Since TDengine was open sourced in July 2019, it has gained a lot of popularity among time-series database developers with its innovative data modeling design, simple installation method, easy programming interface, and powerful data insertion and query performance. The insertion and querying performance is often astonishing to users who are new to TDengine. In order to help users to experience the high performance and functions of TDengine in the shortest time, we developed an application called `taosBenchmark` (was named `taosdemo`) for insertion and querying performance testing of TDengine. Then user can easily simulate the scenario of a large number of devices generating a very large amount of data. User can easily manipulate the number of columns, data types, disorder ratio, and number of concurrent threads with taosBenchmark customized parameters.
Since TDengine was open sourced in July 2019, it has gained a lot of popularity among time-series database developers with its innovative data modeling design, simple installation method, easy programming interface, and powerful data insertion and query performance. The insertion and querying performance is often astonishing to users who are new to TDengine. In order to help users to experience the high performance and functions of TDengine in the shortest time, we developed an application called `taosBenchmark` (was named `taosdemo`) for insertion and querying performance testing of TDengine. Then user can easily simulate the scenario of a large number of devices generating a very large amount of data. User can easily manipulate the number of columns, data types, disorder ratio, and number of concurrent threads with taosBenchmark customized parameters.
Running taosBenchmark is very simple. Just download the [TDengine installation package](https://www.taosdata.com/cn/all-downloads/) or compiling the [TDengine code](https://github.com/taosdata/TDengine). It can be found and run in the installation directory or in the compiled results directory.
Running taosBenchmark is very simple. Just download the TDengine installation package (https://www.taosdata.com/cn/all-downloads/) or compiling the TDengine code yourself (https://github.com/taosdata/TDengine). It can be found and run in the installation directory or in the compiled results directory.
# To run an insertion test with taosBenchmark
To run an insertion test with taosBenchmark
--
Executing taosBenchmark without any parameters results in the following output.
Executing taosBenchmark without any parameters results in the following output.
```
```
$ taosBenchmark
$ taosBenchmark
...
@@ -70,6 +70,7 @@ Query OK, 6 row(s) in set (0.002972s)
...
@@ -70,6 +70,7 @@ Query OK, 6 row(s) in set (0.002972s)
```
```
After pressing any key taosBenchmark will create the database test and super table meters and generate 10,000 sub-tables representing 10,000 individule meter devices that report data. That means they independently using the super table meters as a template according to TDengine data modeling best practices.
After pressing any key taosBenchmark will create the database test and super table meters and generate 10,000 sub-tables representing 10,000 individule meter devices that report data. That means they independently using the super table meters as a template according to TDengine data modeling best practices.
The above information is the result of a real test on a normal PC server with 8 CPUs and 64G RAM. It shows that taosBenchmark inserted 100,000,000 (no need to count, 100 million) records in 18 seconds, or an average of 552,909,049 records per second.
The above information is the result of a real test on a normal PC server with 8 CPUs and 64G RAM. It shows that taosBenchmark inserted 100,000,000 (no need to count, 100 million) records in 18 seconds, or an average of 552,909,049 records per second.
TDengine also offers a parameter-bind interface for better performance, and using the parameter-bind interface (taosBenchmark -I stmt) on the same hardware for the same amount of data writes, the results are as follows.
TDengine also offers a parameter-bind interface for better performance, and using the parameter-bind interface (taosBenchmark -I stmt) on the same hardware for the same amount of data writes, the results are as follows.
```
```
...
...
...
@@ -145,12 +150,13 @@ Spent 6.0257 seconds to insert rows: 100000000, affected rows: 100000000 with 16
...
@@ -145,12 +150,13 @@ Spent 6.0257 seconds to insert rows: 100000000, affected rows: 100000000 with 16
It shows that taosBenchmark inserted 100 million records in 6 seconds, with a much more higher insertion performance, 1,659,590 records wer inserted per second.
It shows that taosBenchmark inserted 100 million records in 6 seconds, with a much more higher insertion performance, 1,659,590 records wer inserted per second.
Because taosBenchmark is so easy to use, so we have extended it with more features to support more complex parameter settings for sample data preparation and validation for rapid prototyping.
Because taosBenchmark is so easy to use, so we have extended it with more features to support more complex parameter settings for sample data preparation and validation for rapid prototyping.
The complete list of taosBenchmark command-line arguments can be displayed via taosBenchmark --help as follows.
The complete list of taosBenchmark command-line arguments can be displayed via taosBenchmark --help as follows.
```
```
$ taosBenchmark --help
$ taosBenchmark --help
...
@@ -197,15 +203,19 @@ Report bugs to <support@taosdata.com>.
...
@@ -197,15 +203,19 @@ Report bugs to <support@taosdata.com>.
```
```
taosBenchmark's parameters are designed to meet the needs of data simulation. A few commonly used parameters are described below.
taosBenchmark's parameters are designed to meet the needs of data simulation. A few commonly used parameters are described below.
```
```
-I, --interface=INTERFACE The interface (taosc, rest, and stmt) taosBenchmark uses. Default is 'taosc'.
-I, --interface=INTERFACE The interface (taosc, rest, and stmt) taosBenchmark uses. Default is 'taosc'.
```
```
The performance difference between different interfaces of taosBenchmark has been mentioned earlier, the -I parameter is used to select different interfaces, currently taosc, stmt and rest are supported. The -I parameter is used to select different interfaces, currently taosc, stmt and rest are supported. taosc uses SQL statements to write data, stmt uses parameter binding interface to write data, and rest uses RESTful protocol to write data.
The performance difference between different interfaces of taosBenchmark has been mentioned earlier, the -I parameter is used to select different interfaces, currently taosc, stmt and rest are supported. The -I parameter is used to select different interfaces, currently taosc, stmt and rest are supported. taosc uses SQL statements to write data, stmt uses parameter binding interface to write data, and rest uses RESTful protocol to write data.
```
```
-T, --threads=NUMBER The number of threads. Default is 8.
-T, --threads=NUMBER The number of threads. Default is 8.
```
```
The -T parameter sets how many threads taosBenchmark uses to synchronize data writes, so that multiple threads can squeeze as much processing power out of the hardware as possible.
The -T parameter sets how many threads taosBenchmark uses to synchronize data writes, so that multiple threads can squeeze as much processing power out of the hardware as possible.
```
```
-b, --data-type=DATATYPE The data_type of columns, default: FLOAT, INT, FLOAT.
-b, --data-type=DATATYPE The data_type of columns, default: FLOAT, INT, FLOAT.
...
@@ -213,36 +223,50 @@ The -T parameter sets how many threads taosBenchmark uses to synchronize data wr
...
@@ -213,36 +223,50 @@ The -T parameter sets how many threads taosBenchmark uses to synchronize data wr
-l, --columns=COLUMNS The number of columns per record. Demo mode by default is 3 (float, int, float). Max values is 4095
-l, --columns=COLUMNS The number of columns per record. Demo mode by default is 3 (float, int, float). Max values is 4095
```
```
As mentioned earlier, tadosdemo creates a typical meter data reporting scenario by default, with each device containing three columns. They are current, voltage and phases. TDengine supports BOOL, TINYINT, SMALLINT, INT, BIGINT, FLOAT, DOUBLE, BINARY, NCHAR, TIMESTAMP data types. By using -b with a list of types allows you to specify the column list with customized data type. Using -w to specify the width of the columns of the BINARY and NCHAR data types (default is 64). The -l parameter can be added to the columns of the data type specified by the -b parameter with the total number of columns of the INT type, which reduces the manual input process in case of a particularly large number of columns, up to 4095 columns.
As mentioned earlier, tadosdemo creates a typical meter data reporting scenario by default, with each device containing three columns. They are current, voltage and phases. TDengine supports BOOL, TINYINT, SMALLINT, INT, BIGINT, FLOAT, DOUBLE, BINARY, NCHAR, TIMESTAMP data types. By using -b with a list of types allows you to specify the column list with customized data type. Using -w to specify the width of the columns of the BINARY and NCHAR data types (default is 64). The -l parameter can be added to the columns of the data type specified by the -b parameter with the total number of columns of the INT type, which reduces the manual input process in case of a particularly large number of columns, up to 4095 columns.
```
```
-r, --rec-per-req=NUMBER The number of records per request. Default is 30000.
-r, --rec-per-req=NUMBER The number of records per request. Default is 30000.
```
```
To reach TDengine performance limits, data insertion can be executed by using multiple clients, multiple threads, and batch data insertions at once. The -r parameter sets the number of records batch that can be stitched together in a single write request, the default is 30,000. The effective number of spliced records is also related to the client buffer size, which is currently 1M Bytes. If the record column width is large, the maximum number of spliced records can be calculated by dividing 1M by the column width (in bytes).
To reach TDengine performance limits, data insertion can be executed by using multiple clients, multiple threads, and batch data insertions at once. The -r parameter sets the number of records batch that can be stitched together in a single write request, the default is 30,000. The effective number of spliced records is also related to the client buffer size, which is currently 1M Bytes. If the record column width is large, the maximum number of spliced records can be calculated by dividing 1M by the column width (in bytes).
```
```
-t, --tables=NUMBER The number of tables. Default is 10000.
-t, --tables=NUMBER The number of tables. Default is 10000.
-n, --records=NUMBER The number of records per table. Default is 10000.
-n, --records=NUMBER The number of records per table. Default is 10000.
-M, --random The value of records generated are totally random. The default is to simulate power equipment scenario.
-M, --random The value of records generated are totally random. The default is to simulate power equipment scenario.
```
```
As mentioned earlier, taosBenchmark creates 10,000 tables by default, and each table writes 10,000 records. taosBenchmark can set the number of tables and the number of records in each table by -t and -n. The data generated by default without parameters are simulated real scenarios, and the simulated data are current and voltage phase values with certain jitter, which can more realistically show TDengine's efficient data compression ability. If you need to simulate the generation of completely random data, you can pass the -M parameter.
As mentioned earlier, taosBenchmark creates 10,000 tables by default, and each table writes 10,000 records. taosBenchmark can set the number of tables and the number of records in each table by -t and -n. The data generated by default without parameters are simulated real scenarios, and the simulated data are current and voltage phase values with certain jitter, which can more realistically show TDengine's efficient data compression ability. If you need to simulate the generation of completely random data, you can pass the -M parameter.
```
```
-y, --answer-yes Default input yes for prompt.
-y, --answer-yes Default input yes for prompt.
```
```
As we can see above, taosBenchmark outputs a list of parameters for the upcoming operation by default before creating a database or inserting data, so that the user can know what data is about to be written before inserting. To facilitate automatic testing, the -y parameter allows taosBenchmark to write data immediately after outputting the parameters.
As we can see above, taosBenchmark outputs a list of parameters for the upcoming operation by default before creating a database or inserting data, so that the user can know what data is about to be written before inserting. To facilitate automatic testing, the -y parameter allows taosBenchmark to write data immediately after outputting the parameters.
```
```
-O, --disorder=NUMBER Insert order mode--0: In order, 1 ~ 50: disorder ratio. Default is in order.
-O, --disorder=NUMBER Insert order mode--0: In order, 1 ~ 50: disorder ratio. Default is in order.
-R, --disorder-range=NUMBER Out of order data's range, ms, default is 1000.
-R, --disorder-range=NUMBER Out of order data's range, ms, default is 1000.
```
```
In some scenarios, the received data does not arrive in exact order, but contains a certain percentage of out-of-order data, which TDengine can also handle very well. In order to simulate the writing of out-of-order data, tadosdemo provides -O and -R parameters to be set. The -O parameter is the same as the -O parameter for fully ordered data writes. 1 to 50 is the percentage of data that contains out-of-order data. The -R parameter is the range of the timestamp offset of the out-of-order data, default is 1000 milliseconds. Also note that temporal data is uniquely identified by a timestamp, so garbled data may generate the exact same timestamp as previously written data, and such data may either be discarded (update 0) or overwrite existing data (update 1 or 2) depending on the update value created by the database, and the total number of data entries may not match the expected number of entries.
In some scenarios, the received data does not arrive in exact order, but contains a certain percentage of out-of-order data, which TDengine can also handle very well. In order to simulate the writing of out-of-order data, tadosdemo provides -O and -R parameters to be set. The -O parameter is the same as the -O parameter for fully ordered data writes. 1 to 50 is the percentage of data that contains out-of-order data. The -R parameter is the range of the timestamp offset of the out-of-order data, default is 1000 milliseconds. Also note that temporal data is uniquely identified by a timestamp, so garbled data may generate the exact same timestamp as previously written data, and such data may either be discarded (update 0) or overwrite existing data (update 1 or 2) depending on the update value created by the database, and the total number of data entries may not match the expected number of entries.
```
```
-g, --debug Print debug info.
-g, --debug Print debug info.
```
```
If you are interested in the taosBenchmark insertion process or if the data insertion result is not as expected, you can use the -g parameter to make taosBenchmark print the debugging information in the process of the execution to the screen or import it to another file with the Linux redirect command to easily find the cause of the problem. In addition, taosBenchmark will also output the corresponding executed statements and debugging reasons to the screen after the execution fails. You can search the word "reason" to find the error reason information returned by the TDengine server.
If you are interested in the taosBenchmark insertion process or if the data insertion result is not as expected, you can use the -g parameter to make taosBenchmark print the debugging information in the process of the execution to the screen or import it to another file with the Linux redirect command to easily find the cause of the problem. In addition, taosBenchmark will also output the corresponding executed statements and debugging reasons to the screen after the execution fails. You can search the word "reason" to find the error reason information returned by the TDengine server.
```
```
-x, --aggr-func Test aggregation funtions after insertion.
-x, --aggr-func Test aggregation funtions after insertion.
```
```
TDengine is not only very powerful in insertion performance, but also in query performance due to its advanced database engine design. tadosdemo provides a -x function that performs the usual query operations and outputs the query consumption time after the insertion of data. The following is the result of a common query after inserting 100 million rows on the aforementioned server.
TDengine is not only very powerful in insertion performance, but also in query performance due to its advanced database engine design. tadosdemo provides a -x function that performs the usual query operations and outputs the query consumption time after the insertion of data. The following is the result of a common query after inserting 100 million rows on the aforementioned server.
You can see that the select * fetch 100 million rows (not output to the screen) operation consumes only 1.26 seconds. The most of normal aggregation function for 100 million records usually takes only about 20 milliseconds, and even the longest count function takes less than 40 milliseconds.
You can see that the select * fetch 100 million rows (not output to the screen) operation consumes only 1.26 seconds. The most of normal aggregation function for 100 million records usually takes only about 20 milliseconds, and even the longest count function takes less than 40 milliseconds.
```
```
taosBenchmark -I stmt -T 48 -y -x
taosBenchmark -I stmt -T 48 -y -x
...
...
...
@@ -264,7 +288,9 @@ select min(current) took 0.025812 second(s)
...
@@ -264,7 +288,9 @@ select min(current) took 0.025812 second(s)
select first(current) took 0.024105 second(s)
select first(current) took 0.024105 second(s)
...
...
```
```
In addition to the command line approach, taosBenchmark also supports take a JSON file as an incoming parameter to provide a richer set of settings. A typical JSON file would look like this.
In addition to the command line approach, taosBenchmark also supports take a JSON file as an incoming parameter to provide a richer set of settings. A typical JSON file would look like this.
```
```
{
{
"filetype": "insert",
"filetype": "insert",
...
@@ -327,13 +353,15 @@ In addition to the command line approach, taosBenchmark also supports take a JSO
...
@@ -327,13 +353,15 @@ In addition to the command line approach, taosBenchmark also supports take a JSO
}]
}]
}
}
```
```
For example, we can specify different number of threads for table creation and data insertion with "thread_count" and "thread_count_create_tbl". You can use a combination of "child_table_exists", "childtable_limit" and "childtable_offset" to use multiple taosBenchmark processes (even on different computers) to write to different ranges of child tables of the same super table at the same time. You can also import existing data by specifying the data source as a csv file with "data_source" and "sample_file".
For example, we can specify different number of threads for table creation and data insertion with "thread_count" and "thread_count_create_tbl". You can use a combination of "child_table_exists", "childtable_limit" and "childtable_offset" to use multiple taosBenchmark processes (even on different computers) to write to different ranges of child tables of the same super table at the same time. You can also import existing data by specifying the data source as a csv file with "data_source" and "sample_file".
Use taosBenchmark for query and subscription testing
# Use taosBenchmark for query and subscription testing
--
taosBenchmark can not only write data, but also perform query and subscription functions. However, a taosBenchmark instance can only support one of these functions, not all three, and the configuration file is used to specify which function to test.
taosBenchmark can not only write data, but also perform query and subscription functions. However, a taosBenchmark instance can only support one of these functions, not all three, and the configuration file is used to specify which function to test.
The following is the content of a typical query JSON example file.
The following is the content of a typical query JSON example file.
```
```
{
{
"filetype": "query",
"filetype": "query",
...
@@ -373,7 +401,9 @@ The following is the content of a typical query JSON example file.
...
@@ -373,7 +401,9 @@ The following is the content of a typical query JSON example file.
}
}
}
}
```
```
The following parameters are specific to the query in the JSON file.
The following parameters are specific to the query in the JSON file.
```
```
"query_times": the number of queries per query type
"query_times": the number of queries per query type
"query_mode": query data interface, "tosc": call TDengine's c interface; "resetful": use restfule interface. Options are available. Default is "taosc".
"query_mode": query data interface, "tosc": call TDengine's c interface; "resetful": use restfule interface. Options are available. Default is "taosc".
...
@@ -392,6 +422,7 @@ The following parameters are specific to the query in the JSON file.
...
@@ -392,6 +422,7 @@ The following parameters are specific to the query in the JSON file.
```
```
The following is a typical subscription JSON example file content.
The following is a typical subscription JSON example file content.
```
```
{
{
"filetype":"subscribe",
"filetype":"subscribe",
...
@@ -431,7 +462,9 @@ The following is a typical subscription JSON example file content.
...
@@ -431,7 +462,9 @@ The following is a typical subscription JSON example file content.
}
}
}
}
```
```
The following are the meanings of the parameters specific to the subscription function.
The following are the meanings of the parameters specific to the subscription function.
```
```
"interval": interval for executing subscriptions, in seconds. Optional, default is 0.
"interval": interval for executing subscriptions, in seconds. Optional, default is 0.
"restart": subscription restart." yes": restart the subscription if it already exists, "no": continue the previous subscription. (Please note that the executing user needs to have read/write access to the dataDir directory)
"restart": subscription restart." yes": restart the subscription if it already exists, "no": continue the previous subscription. (Please note that the executing user needs to have read/write access to the dataDir directory)
...
@@ -439,8 +472,9 @@ The following are the meanings of the parameters specific to the subscription fu
...
@@ -439,8 +472,9 @@ The following are the meanings of the parameters specific to the subscription fu
"resubAfterConsume": Used in conjunction with keepProgress to call unsubscribe after the subscription has been consumed the appropriate number of times and to subscribe again.
"resubAfterConsume": Used in conjunction with keepProgress to call unsubscribe after the subscription has been consumed the appropriate number of times and to subscribe again.
"result": the name of the file to which the query result is written. Optional, default is null, means the query result will not be written to the file. Note: The file to save the result after each sql statement cannot be renamed, and the file name will be appended with the thread number when generating the result file.
"result": the name of the file to which the query result is written. Optional, default is null, means the query result will not be written to the file. Note: The file to save the result after each sql statement cannot be renamed, and the file name will be appended with the thread number when generating the result file.
```
```
Conclusion
--
# Conclusion
TDengine is a big data platform designed and optimized for IoT, Telematics, Industrial Internet, DevOps, etc. TDengine shows a high performance that far exceeds similar products due to the innovative data storage and query engine design in the database kernel. And withSQL syntax support and connectors for multiple programming languages (currently Java, Python, Go, C#, NodeJS, Rust, etc. are supported), it is extremely easy to use and has zero learning cost. To facilitate the operation and maintenance needs, we also provide data migration and monitoring functions and other related ecological tools and software.
TDengine is a big data platform designed and optimized for IoT, Telematics, Industrial Internet, DevOps, etc. TDengine shows a high performance that far exceeds similar products due to the innovative data storage and query engine design in the database kernel. And withSQL syntax support and connectors for multiple programming languages (currently Java, Python, Go, C#, NodeJS, Rust, etc. are supported), it is extremely easy to use and has zero learning cost. To facilitate the operation and maintenance needs, we also provide data migration and monitoring functions and other related ecological tools and software.
For users who are new to TDengine, we have developed rich features for taosBenchmark to facilitate technical evaluation and stress testing. This article is a brief introduction to taosBenchmark, which will continue to evolve and improve as new features are added to TDengine.
For users who are new to TDengine, we have developed rich features for taosBenchmark to facilitate technical evaluation and stress testing. This article is a brief introduction to taosBenchmark, which will continue to evolve and improve as new features are added to TDengine.
# How to install/uninstall TDengine with installtion package
TDengine open source version provides `deb` and `rpm` format installation packages. Our users can choose the appropriate installation package according to their own running environment. The `deb` supports Debian/Ubuntu etc. and the `rpm` supports CentOS/RHEL/SUSE etc. We also provide `tar.gz` format installers for enterprise users.
## Install and uninstall deb package
### Install deb package
- Download and obtain the deb installation package from the official website, such as TDengine-server-2.0.0.0-Linux-x64.deb.
- Go to the directory where the TDengine-server-2.0.0.0-Linux-x64.deb installation package is located and execute the following installation command.
Enter FQDN:port (like h1.taosdata.com:6030) of an existing TDengine cluster node to join OR leave it blank to build one :
To configure TDengine : edit /etc/taos/taos.cfg
To start TDengine : sudo systemctl start taosd
To access TDengine : use taos in shell
TDengine is installed successfully!
```
Note: When the Enter FQDN: prompt appears when the first node is installed, nothing needs to be entered. Only when installing the second or later more nodes is it necessary to enter the FQDN of any of the available nodes in the existing cluster to support that new node joining the cluster. It is of course possible to not enter it, but to configure it into the new node's configuration file before the new node starts
in the configuration file of the new node before it starts.
The same operation is performed for the other installation packages format.
Created symlink from /etc/systemd/system/multi-user.target.wants/taosd.service to /etc/systemd/system/taosd.service.
Enter FQDN:port (like h1.taosdata.com:6030) of an existing TDengine cluster node to join OR leave it blank to build one :
To configure TDengine : edit /etc/taos/taos.cfg
To start TDengine : sudo systemctl start taosd
To access TDengine : use taos in shell
TDengine is installed successfully!
```
### Uninstall rpm
Uninstall command is following:
```
[root@bogon x86_64]# rpm -e tdengine
TDEngine is removed successfully!
```
## Install and uninstall tar.gz
### Install tar.gz
- Download and obtain the tar.gz installation package from the official website, such as `TDengine-server-2.0.0.0-Linux-x64.tar.gz`.
- Go to the directory where the `TDengine-server-2.0.0.0-Linux-x64.tar.gz` installation package is located, unzip the file first, then enter the subdirectory and execute the install.sh installation script in it as follows
```
plum@ubuntu:~/git/tdengine/release$ sudo tar -xzvf TDengine-server-2.0.0.0-Linux-x64.tar.gz
plum@ubuntu:~/git/tdengine/release$ ll
total 3796
drwxr-xr-x 3 root root 4096 Aug 9 14:20 ./
drwxrwxr-x 11 plum plum 4096 Aug 8 11:03 ../
drwxr-xr-x 5 root root 4096 Aug 8 11:03 TDengine-server/
-rw-r--r-- 1 root root 3871844 Aug 8 11:03 TDengine-server-2.0.0.0-Linux-x64.tar.gz
plum@ubuntu:~/git/tdengine/release$ cd TDengine-server/
Enter FQDN:port (like h1.taosdata.com:6030) of an existing TDengine cluster node to join OR leave it blank to build one :hostname.taosdata.com:7030
To configure TDengine : edit /etc/taos/taos.cfg
To start TDengine : sudo systemctl start taosd
To access TDengine : use taos in shell
Please run: taos -h hostname.taosdata.com:7030 to login into cluster, then execute : create dnode 'newDnodeFQDN:port'; in TAOS shell to add this new node into the clsuter
TDengine is installed successfully!
```
Note: The install.sh install script asks for some configuration information through an interactive command line interface during execution. If you prefer a non-interactive installation, you can execute the install.sh script with the -e no parameter. Run . /install.sh -h command to see detailed information about all parameters.
### Uninstall TDengine after tar.gz package installed
- Automatically generates the configuration file directory, database directory, and log directory.
- Configuration file default directory: /etc/taos/taos.cfg, softlinked to /usr/local/taos/cfg/taos.cfg.
- Database default directory: /var/lib/taos, softlinked to /usr/local/taos/data.
- Log default directory: /var/log/taos, softlinked to /usr/local/taos/log.
- executables in the /usr/local/taos/bin directory, which are soft-linked to the /usr/bin directory.
- Dynamic library files in the /usr/local/taos/driver directory, which are soft-linked to the /usr/lib directory.
- header files in the /usr/local/taos/include directory, which are soft-linked to the /usr/include directory.
## Uninstall and update file instructions
When uninstalling the installation package, the configuration files, database files and log files will be kept, i.e. /etc/taos/taos.cfg, /var/lib/taos, /var/log/taos. If users confirm that they do not need to keep them, they can delete them manually, but must be careful, because after deletion, the data will be permanently lost and cannot be recovered!
If the installation is updated, when the default configuration file (/etc/taos/taos.cfg) exists, the existing configuration file is still used. The configuration file carried in the installation package is modified to taos.cfg.org and saved in the /usr/local/taos/cfg/ directory, which can be used as a reference sample for setting configuration parameters; if the configuration file does not exist, the Use the configuration file that comes with the installation package
file that comes with the installation package.
## Caution
- TDengine provides several installers, but it is best not to use both the tar.gz installer and the deb or rpm installer on one system. Otherwise, they may affect each other and cause problems when using them.
- For deb package installation, if the installation directory is manually deleted by mistake, the uninstallation, or reinstallation cannot be successful. In this case, you need to clear the installation information of the tdengine package by executing the following command:
- For the rpm package after installation, if the installation directory is manually deleted by mistake part of the uninstallation, or reinstallation can not be successful. In this case, you need to clear the installation information of the tdengine package by executing the following command:
TDengine software consists of 3 parts: server, client, and alart module. At the moment, TDengine server only runs on Linux (Windows, mac OS and more OS supports will come soon), but client can run on either Windows or Linux. TDengine client can be installed and run on Windows or Linux. Applications based-on any OSes can all connect to server taosd via a RESTful interface. From 2.4 and later version, TDengine use a stand-alone software, taosAdapteer to provide http service. The early version uses the http server embedded in the taosd. About CPU, TDengine supports X64/ARM64/MIPS64/Alpha64, and ARM32、RISC-V, other more CPU architectures will be supported soon. You can set up and install TDengine server either from the [source code](https://www.taosdata.com/en/getting-started/#Install-from-Source) or the [packages](https://www.taosdata.com/en/getting-started/#Install-from-Package).
TDengine includes server, client, and ecological software and peripheral tools. Currently, version 2.0 of the server can only be installed and run on Linux and will support Windows, macOS, and other OSes in the future. The client can be installed and run on Windows or Linux. Applications on any operating system can use the RESTful interface to connect to the taosd server. After 2.4, TDengine includes taosAdapter to provide an easy-to-use and efficient way to ingest data including RESTful service. taosAdapter needs to be started manually as a stand-alone component. The early version uses an embedded HTTP component to provide the RESTful interface.
### <a class="anchor" id="source-install"></a>Install from Source
TDengine supports X64/ARM64/MIPS64/Alpha64 hardware platforms and will support ARM32, RISC-V, and other CPU architectures in the future.
Please visit our [TDengine github page](https://github.com/taosdata/TDengine) for instructions on installation from the source code.
### Install from Docker Container
For the time being, it is not recommended to use Docker to deploy the client or server side of TDengine in production environments, but it is convenient to use Docker to deploy in development environments or when trying it for the first time. In particular, with Docker, it is easy to try TDengine in Mac OS X and Windows environments.
### Install with Docker Container
```
```
docker run -d -p 6030-6049:6030-6049 -p 6030-6049:6030-6049/udp tdengine/tdengine
docker run -d -p 6030-6049:6030-6049 -p 6030-6049:6030-6049/udp tdengine/tdengine
```
```
Please refer to [Quickly experience TDengine with Docker](https://www.taosdata.com/en/documentation/getting-started/docker) for the details.
Please refer to [Quickly Taste TDengine with Docker](https://www.taosdata.com/en/documentation/getting-started/docker) for the details.
For the time being, using Docker to deploy the client or server of TDengine for production environments is not recommended. However it is a convenient way to deploy TDengine for development purposes. In particular, it is easy to try TDengine in Mac OS X and Windows environments with Docker.
### <a class="anchor" id="package-install"></a>Install from Package
### <a class="anchor" id="package-install"></a>Install from Package
Three different packages for TDengine server are provided, please pick up the one you like. (Lite packages only have execution files and connector of C/C++, but standard packages support connectors of nearly all programming languages.) Beta version has more features, but we suggest you to install stable version for production or testing.
TDengine is very easy to install, from download to successful installation in just a few seconds. For ease of use, the standard server installation package includes the client application and sample code; if you only need the server application and C/C++ language support for the client connection, you can also download the lite version of the installation package only. The installation packages are available in `rpm` and `deb` formats, as well as `tar.gz` format for enterprise customers who need to facilitate use on specific operating systems. Releases include both stable and beta releases. We recommend the stable release for production use or testing. The beta release may contain more new features. You can choose to download from the following as needed:
For detailed installation steps, please refer to [How to install/uninstall TDengine with installation package](https://www.taosdata.com/getting-started/install).
Click [here](https://www.taosdata.com/en/getting-started/#Install-from-Package) to download the install package.
**Click [here](https://github.com/taosdata/TDengine/releases) for release notes.**
### Install TDengine by apt-get
### Install TDengine by apt-get
If you use Debian or Ubuntu system you can use 'apt-get' command to install TDengine from official repository. Please use following commands to setup:
If you use Debian or Ubuntu system you can use the `apt-get` command to install TDengine from the official repository. Please use the following commands to setup:
If the client and server are running on different computers, you can install the client separately. When downloading, please note that the selected client version number should strictly match the server version number downloaded above. Linux and Windows installation packages are as follows (the lite version of the installer comes with connection support for the C/C++ language only, while the standard version of the installer also contains sample code):
### <a class="anchor" id="source-install"></a>Install from Source
If you want to contribute to TDengine, please visit [TDengine GitHub page](https://github.com/taosdata/TDengine) for detailed instructions on build and installation from the source code.
**To download other components, beta version, or early releases, please click [here](https://www.taosdata.com/en/all-downloads/).**
## <a class="anchor" id="start"></a>Quick Launch
## <a class="anchor" id="start"></a>Quick Launch
After installation, you can start the TDengine service by the `systemctl` command.
After installation, you can start the TDengine service by the `systemctl` command.
```bash
```bash
$ systemctl start taosd
systemctl start taosd
```
```
Then check if the service is working now.
Then check if the service is working now.
```bash
```bash
$ systemctl status taosd
systemctl status taosd
```
```
If the service is running successfully, you can play around through TDengine shell `taos`.
If the service is running successfully, you can play around through TDengine shell `taos`.
...
@@ -56,25 +70,25 @@ If the service is running successfully, you can play around through TDengine she
...
@@ -56,25 +70,25 @@ If the service is running successfully, you can play around through TDengine she
**Note:**
**Note:**
- The `systemctl` command needs the **root** privilege. Use **sudo** if you are not the **root** user.
- The `systemctl` command needs the **root** privilege. Use **sudo** if you are not the **root** user.
- To get better product feedback and improve our solution, TDengine will collect basic usage information, but you can modify the configuration parameter **telemetryReporting** in the system configuration file taos.cfg, and set it to 0 to turn it off.
- To get better product feedback and improve our solution, TDengine will collect basic usage information, but you can modify the configuration parameter **telemetryReporting** in the system configuration file `taos.cfg`, and set it to 0 to turn it off.
- TDengine uses FQDN (usually hostname) as the node ID. In order to ensure normal operation, you need to set hostname for the server running taosd, and configure DNS service or hosts file for the machine running client application, to ensure the FQDN can be resolved.
- TDengine uses FQDN (usually hostname) as the node ID. To ensure normal operation, you need to set the host's name for the server running `taosd`, and configure DNS service or hosts file for the machine running the client application, to ensure the FQDN can be resolved.
- TDengine supports installation on Linux systems with [systemd](https://en.wikipedia.org/wiki/Systemd) as the process service management, and uses `which systemctl` command to detect whether `systemd` packages exist in the system:
- TDengine supports installation on Linux systems with [systemd](https://en.wikipedia.org/wiki/Systemd) as the process service management and uses `which systemctl` command to detect whether `systemd` packages exist in the system:
```bash
```bash
$ which systemctl
which systemctl
```
```
If `systemd` is not supported in the system, TDengine service can also be launched via `/usr/local/taos/bin/taosd` manually.
If `systemd` is not supported in the system, TDengine service can also be launched via `/usr/local/taos/bin/taosd` manually.
## <a class="anchor" id="console"></a>TDengine Shell Command Line
## <a class="anchor" id="console"></a>TDengine Shell Command Line
To launch TDengine shell, the commandline interface, in a Linux terminal, type:
To launch TDengine shell, the command-line interface, in a Linux terminal, type:
```bash
```bash
$ taos
taos
```
```
The welcome message is printed if the shell connects to TDengine server successfully, otherwise, an error message will be printed (refer to our [FAQ](https://www.taosdata.com/en/faq) page for troubleshooting the connection error). The TDengine shell prompt is:
The welcome message is printed if the shell connects to the TDengine server successfully, otherwise, an error message will be printed (refer to our [FAQ](https://www.taosdata.com/en/faq) page for troubleshooting the connection error). The TDengine shell prompt is:
```cmd
```cmd
taos>
taos>
...
@@ -110,49 +124,59 @@ Besides the SQL commands, the system administrator can check system status, add
...
@@ -110,49 +124,59 @@ Besides the SQL commands, the system administrator can check system status, add
### Shell Command Line Parameters
### Shell Command Line Parameters
You can configure command parameters to change how TDengine shell executes. Some frequently used options are listed below:
You can configure command parameters to change how the TDengine shell executes. Some frequently used options are listed below:
- -c, --config-dir: set the configuration directory. It is */etc/taos* by default.
- -c, --config-dir: set the configuration directory. It is */etc/taos* by default.
- -h, --host: set the IP address of the server it will connect to. Default is localhost.
- -h, --host: set the IP address of the server it will connect to. Default is localhost.
- -s, --commands: set the command to run without entering the shell.
- -s, --commands: set the command to run without entering the shell.
- -u, -- user: user name to connect to server. Default is root.
- -u, -- user: user name to connect to the server/cluster. Default is root.
- -p, --password: password. Default is 'taosdata'.
- -p, --password: password. Default is 'taosdata'.
- -?, --help: get a full list of supported options.
- -?, --help: get a full list of supported options.
Examples:
Examples:
```bash
```bash
$ taos -h 192.168.0.1 -s"use db; show tables;"
taos -h 192.168.0.1 -s"use db; show tables;"
```
```
### Run SQL Command Scripts
### Run SQL Command Scripts
Inside TDengine shell, you can run SQL scripts in a file with source command.
Inside TDengine shell, you can run SQL scripts in a file with the `source` command.
```mysql
```mysql
taos> source <filename>;
taos> source <filename>;
```
```
### Shell Tips
### taos shell tips
- Use up/down arrow key to check the command history
- Use the up/down arrow key to check the command history
- To change the default password, use "alter user" command
- To change the default password, use `alter user` command
- Use ctrl+c to interrupt any queries
- Use ctrl+c to interrupt any queries
- To clean the schema of local cached tables, execute command `RESET QUERY CACHE`
- To clean the schema of locally cached tables, execute the command `RESET QUERY CACHE`
### <a class="anchor" id="taosBenchmark"></a> Taste insertion speed with taosBenchmark
After starting the TDengine server, you can execute the command `taosBenchmark` (was named `taosdemo`, please install taosTools package if you use TDengine 2.4 or later version) in the Linux terminal.
Once the TDengine server started, you can execute the command `taosBenchmark` (which was named `taosdemo`) in the Linux terminal. In 2.4.0.7 and early release, taosBenchmark is distributed within taosTools package. In later release, taosBenchmark will be included within TDengine again.
```bash
```bash
$ taosBenchmark
taosBenchmark
```
```
Using this command, a STable named `meters` will be created in the database `test`. There are 10k tables under this STable, named from `t0` to `t9999`. In each table there are 100k rows of records, each row with columns （`f1`, `f2` and `f3`. The timestamp is from "2017-07-14 10:40:00 000" to "2017-07-14 10:41:39 999". Each table also has tags `areaid` and `loc`: `areaid` is set from 1 to 10, `loc` is set to "beijing" or "shanghai".
Using this command, a STable named `meters` will be created in the database `test`. There are 10k tables under this STable, named from `d0` to `d9999`. In each table, there are 100k rows of records, each row with columns （`ts`, `current`, `voltage`, and `phase`. The timestamp is from "2017-07-14 10:40:00 000" to "2017-07-14 10:41:39 999". Each table also has tags `location` and `groupId`: `groupId` is set from 1 to 10, `location` is set to "beijing" or "shanghai".
Once execution is finished, 1 billion rows of records will be inserted. It usually takes about a dozen seconds to execute this command on a normal PC server but it may be different depending on the particular hardware platform performance.
### <a class="anchor" id="taosBenchmark"></a> Using taosBenchmark in detail
you can run the command `taosBenchmark` with many options, like the number of tables, rows of records, and so on. To know more about these options, you can execute `taosBenchmark --help` and then take a try using different options.
It takes about 10 minutes to execute this command. Once finished, 1 billion rows of records will be inserted.
For more details on how to use taosBenchmark, please refer to [How to use taosBenchmark to test the performance of TDengine](https://tdengine.com/2021/10/09/3114.html).
In the TDengine client, enter sql query commands and then experience our lightning query speed.
### <a class="anchor" id="taosshell"></a> Taste query speed with taos shell
In the TDengine client, enter sql query commands and then taste our lightning query speed.
- query total rows of records：
- query total rows of records：
...
@@ -160,7 +184,7 @@ In the TDengine client, enter sql query commands and then experience our lightni
...
@@ -160,7 +184,7 @@ In the TDengine client, enter sql query commands and then experience our lightni
taos> select count(*) from test.meters;
taos> select count(*) from test.meters;
```
```
- query average, max and min of the total 1 billion records：
- query average, max, and min of the total 1 billion records：
```mysql
```mysql
taos> select avg(f1), max(f2), min(f3) from test.meters;
taos> select avg(f1), max(f2), min(f3) from test.meters;
...
@@ -184,11 +208,6 @@ taos> select avg(f1), max(f2), min(f3) from test.meters where areaid=10;
...
@@ -184,11 +208,6 @@ taos> select avg(f1), max(f2), min(f3) from test.meters where areaid=10;
taos> select avg(f1), max(f2), min(f3) from test.t10 interval(10s);
taos> select avg(f1), max(f2), min(f3) from test.t10 interval(10s);
```
```
### <a class="anchor" id="taosBenchmark"></a> Using taosBenchmark in detail
you can run command `taosBenchmark` with many options, like number of tables, rows of records and so on. To know more about these options, you can execute `taosBenchmark --help` and then take a try using different options.
Please refer to [How to use taosBenchmark to test the performance of TDengine](https://tdengine.com/2021/10/09/3114.html) for detail.
## <a class="anchor" id="platforms"></a>List of Supported Platforms
## <a class="anchor" id="platforms"></a>List of Supported Platforms
List of platforms supported by TDengine server
List of platforms supported by TDengine server
...
@@ -209,7 +228,7 @@ Note: ● has been verified by official tests; ○ has been verified by unoffici
...
@@ -209,7 +228,7 @@ Note: ● has been verified by official tests; ○ has been verified by unoffici
List of platforms supported by TDengine client and connectors
List of platforms supported by TDengine client and connectors
At the moment, TDengine connectors can support a wide range of platforms, including hardware platforms such as X64/X86/ARM64/ARM32/MIPS/Alpha, and operating system such as Linux/Win64/Win32.
At the moment, TDengine connectors can support a wide range of platforms, including hardware platforms such as X64/X86/ARM64/ARM32/MIPS/Alpha, and operating systems such as Linux/Win64/Win32.
Comparison matrix as following:
Comparison matrix as following:
...
@@ -227,3 +246,5 @@ Comparison matrix as following:
...
@@ -227,3 +246,5 @@ Comparison matrix as following:
Note: ● has been verified by official tests; ○ has been verified by unofficial tests.
Note: ● has been verified by official tests; ○ has been verified by unofficial tests.
Please visit Connectors section for more detailed information.
Please visit Connectors section for more detailed information.
@@ -304,16 +304,6 @@ TCollector is a client-side process that gathers data from local collectors and
...
@@ -304,16 +304,6 @@ TCollector is a client-side process that gathers data from local collectors and
Please find taosAdapter configuration and usage from `taosadapter --help` output.
Please find taosAdapter configuration and usage from `taosadapter --help` output.
## <a class="anchor" id="bailongma2-prometheus"></a> Insert Prometheus data via Bailongma 2.0
**Notice:**
TDengine 2.4.0.4+ provides taosAdapter to support Prometheus data writing. Bailongma v2 will be abandoned and no more maintained.
## <a class="anchor" id="bailongma2-telegraf"></a> Insert data via Bailongma 2.0 and Telegraf
**Notice:**
TDengine 2.3.0.0+ provides taosAdapter to support Telegraf data writing. Bailongma v2 will be abandoned and no more maintained.
## <a class="anchor" id="emq"></a> Data Writing via EMQ Broker
## <a class="anchor" id="emq"></a> Data Writing via EMQ Broker
[EMQ](https://github.com/emqx/emqx) is an open source MQTT Broker software, with no need of coding, only to use "rules" in EMQ Dashboard for simple configuration, and MQTT data can be directly written into TDengine. EMQ X supports storing data to the TDengine by sending it to a Web service, and also provides a native TDengine driver on Enterprise Edition for direct data store. Please refer to [EMQ official documents](https://docs.emqx.io/broker/latest/cn/rule/rule-example.html#%E4%BF%9D%E5%AD%98%E6%95%B0%E6%8D%AE%E5%88%B0-tdengine) for more details.
[EMQ](https://github.com/emqx/emqx) is an open source MQTT Broker software, with no need of coding, only to use "rules" in EMQ Dashboard for simple configuration, and MQTT data can be directly written into TDengine. EMQ X supports storing data to the TDengine by sending it to a Web service, and also provides a native TDengine driver on Enterprise Edition for direct data store. Please refer to [EMQ official documents](https://docs.emqx.io/broker/latest/cn/rule/rule-example.html#%E4%BF%9D%E5%AD%98%E6%95%B0%E6%8D%AE%E5%88%B0-tdengine) for more details.
On Windows systems, the current system encoding cannot be obtained from locale. If string encoding information cannot be read from the configuration file, taos defaults to CP936. It is equivalent to adding the following to the configuration file:
On Windows systems, the current system encoding cannot be obtained from locale. If string encoding information cannot be read from the configuration file, taos defaults to CP936. It is equivalent to adding the following to the configuration file:
j
```
```
charset CP936
charset CP936
```
```
If you need to adjust the character encoding, check the encoding used by the current operating system and set it correctly in the configuration file.
If you need to adjust the character encoding, check the encoding used by the current operating system and set it correctly in the configuration file.
In Linux systems, if user sets both locale and charset encoding charset, and the locale and charset are inconsistent, the value set later will override the value set earlier.
In Linux systems, if user sets both locale and charset encoding charset, and the locale and charset are inconsistent, the value set later will override the value set earlier.
The time zone in which the client runs the system. In order to deal with the problem of data writing and query in multiple time zones, TDengine uses Unix Timestamp to record and store timestamps. The characteristics of UNIX timestamps determine that the generated timestamps are consistent at any time regardless of any time zone. It should be noted that UNIX timestamps are converted and recorded on the client side. In order to ensure that other forms of time on the client are converted into the correct Unix timestamp, the correct time zone needs to be set.
The time zone in which the client runs the system. In order to deal with the problem of data writing and query in multiple time zones, TDengine uses Unix Timestamp to record and store timestamps. The characteristics of UNIX timestamps determine that the generated timestamps are consistent at any time regardless of any time zone. It should be noted that UNIX timestamps are converted and recorded on the client side. In order to ensure that other forms of time on the client are converted into the correct Unix timestamp, the correct time zone needs to be set.
In Linux system, the client will automatically read the time zone information set by the system. Users can also set time zones in profiles in a number of ways. For example:
In Linux system, the client will automatically read the time zone information set by the system. Users can also set time zones in profiles in a number of ways. For example:
In East Eight Zone, the SQL statement is equivalent to
In East Eight Zone, the SQL statement is equivalent to
```sql
```sql
SELECT count(*) FROM table_name WHERE TS<1554955268000;
SELECT count(*) FROM table_name WHERE TS<1554955268000;
```
```
In the UTC time zone, the SQL statement is equivalent to
In the UTC time zone, the SQL statement is equivalent to
```sql
```sql
SELECT count(*) FROM table_name WHERE TS<1554984068000;
SELECT count(*) FROM table_name WHERE TS<1554984068000;
```
```
In order to avoid the uncertainty caused by using string time format, Unix timestamp can also be used directly. In addition, timestamp strings with time zones can also be used in SQL statements, such as: timestamp strings in RFC3339 format, 2013-04-12T15:52:01.123+08:00, or ISO-8601 format timestamp strings 2013-04-12T15:52:01.123+0800. The conversion of the above two strings into Unix timestamps is not affected by the time zone in which the system is located.
In order to avoid the uncertainty caused by using string time format, Unix timestamp can also be used directly. In addition, timestamp strings with time zones can also be used in SQL statements, such as: timestamp strings in RFC3339 format, 2013-04-12T15:52:01.123+08:00, or ISO-8601 format timestamp strings 2013-04-12T15:52:01.123+0800. The conversion of the above two strings into Unix timestamps is not affected by the time zone in which the system is located.
When starting taos, you can also specify an end point for an instance of taosd from the command line, otherwise read from taos.cfg.
When starting taos, you can also specify an end point for an instance of taosd from the command line, otherwise read from taos.cfg.
TDengine provides a convenient database import and export tool, taosdump. Users can import data exported by taosdump from one system into other systems. Please refer to the blog: [User Guide of TDengine DUMP Tool](https://www.taosdata.com/blog/2020/03/09/1334.html).
TDengine provides a convenient database import and export tool, taosdump. Users can import data exported by taosdump from one system into other systems. Please refer to [backup tool for TDengine - taosdump](/tools/taosdump).
