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TDengine
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Merge pull request #12493 from taosdata/docs/wade-20220515-1 

docs: correct some terms
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docs-en/04-develop/01-connect/index.md
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...@@ -19,7 +19,7 @@ import InstallOnLinux from "../../14-reference/03-connector/\_windows_install.md ...@@ -19,7 +19,7 @@ import InstallOnLinux from "../../14-reference/03-connector/\_windows_install.md
import VerifyLinux from "../../14-reference/03-connector/\_verify_linux.mdx"; import VerifyLinux from "../../14-reference/03-connector/\_verify_linux.mdx";
import VerifyWindows from "../../14-reference/03-connector/\_verify_windows.mdx"; import VerifyWindows from "../../14-reference/03-connector/\_verify_windows.mdx";
Any application programs running on any kind of platforms can access TDengine through the REST API provided by TDengine. For the details please refer to [REST API](/reference/rest-api/). Besides, application programs can use the connectors of multiple languages to access TDengine, including C/C++, Java, Python, Go, Node.js, C#, and Rust. This chapter describes how to establish connection to TDengine and briefly introduce how to install and use connectors. For details about the connectors please refer to [Connectors](https://docs.taosdata.com/reference/connector/) Any application programs running on any kind of platforms can access TDengine through the REST API provided by TDengine. For the details please refer to [REST API](/reference/rest-api/). Besides, application programs can use the connectors of multiple languages to access TDengine, including C/C++, Java, Python, Go, Node.js, C#, and Rust. This chapter describes how to establish connection to TDengine and briefly introduce how to install and use connectors. For details about the connectors please refer to [Connectors](/reference/connector/)
## Establish Connection ## Establish Connection
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docs-en/04-develop/02-model/index.mdx
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...@@ -24,7 +24,7 @@ USE power; ...@@ -24,7 +24,7 @@ USE power;
:::note :::note
- Any table or stable must belong to a database. To create a table or stable, the database it belongs to must be ready. - Any table or STable must belong to a database. To create a table or STable, the database it belongs to must be ready.
- JOIN operation can't be performed tables from two different databases. - JOIN operation can't be performed tables from two different databases.
- Timestamp needs to be specified when inserting rows or querying historical rows. - Timestamp needs to be specified when inserting rows or querying historical rows.
...@@ -35,11 +35,11 @@ USE power; ...@@ -35,11 +35,11 @@ USE power;
In a time-series application, there may be multiple kinds of data collection points. For example, in the electrical power system there are meters, transformers, bus bars, switches, etc. For easy and efficient aggregation of multiple tables, one STable needs to be created for each kind of data collection point. For example, for the meters in [table 1](/tdinternal/arch#model_table1), below SQL statement can be used to create the super table. In a time-series application, there may be multiple kinds of data collection points. For example, in the electrical power system there are meters, transformers, bus bars, switches, etc. For easy and efficient aggregation of multiple tables, one STable needs to be created for each kind of data collection point. For example, for the meters in [table 1](/tdinternal/arch#model_table1), below SQL statement can be used to create the super table.
```sql ```sql
CREATE STABLE meters (ts timestamp, current float, voltage int, phase float) TAGS (location binary(64), groupId int); CREATE STable meters (ts timestamp, current float, voltage int, phase float) TAGS (location binary(64), groupId int);
``` ```
:::note :::note
If you are using versions prior to 2.0.15, the `STABLE` keyword needs to be replaced with `TABLE`. If you are using versions prior to 2.0.15, the `STable` keyword needs to be replaced with `TABLE`.
::: :::
...@@ -49,6 +49,7 @@ Each kind of data collecting points needs a corresponding STable to be created, ...@@ -49,6 +49,7 @@ Each kind of data collecting points needs a corresponding STable to be created,
At most 4096 (or 1024 prior to version 2.1.7.0) columns are allowed in a STable. If there are more than 4096 of metrics to bo collected for a data collection point, multiple STables are required for such kind of data collection point. There can be multiple databases in system, while one or more STables can exist in a database. At most 4096 (or 1024 prior to version 2.1.7.0) columns are allowed in a STable. If there are more than 4096 of metrics to bo collected for a data collection point, multiple STables are required for such kind of data collection point. There can be multiple databases in system, while one or more STables can exist in a database.
## Create Table ## Create Table
A specific table needs to be created for each data collection point. Similar to RDBMS, table name and schema are required to create a table. Beside, one or more tags can be created for each table. To create a table, a STable needs to be used as template and the values need to be specified for the tags. For example, for the meters in [Table 1](/tdinternal/arch#model_table1), the table can be created using below SQL statement. A specific table needs to be created for each data collection point. Similar to RDBMS, table name and schema are required to create a table. Beside, one or more tags can be created for each table. To create a table, a STable needs to be used as template and the values need to be specified for the tags. For example, for the meters in [Table 1](/tdinternal/arch#model_table1), the table can be created using below SQL statement.
...@@ -59,11 +60,12 @@ CREATE TABLE d1001 USING meters TAGS ("Beijing.Chaoyang", 2); ...@@ -59,11 +60,12 @@ CREATE TABLE d1001 USING meters TAGS ("Beijing.Chaoyang", 2);
In the above SQL statement, "d1001" is the table name, "meters" is the STable name, followed by the value of tag "Location" and the value of tag "groupId", which are "Beijing.Chaoyang" and "2" respectively in the example. The tag values can be updated after the table is created. Please refer to [Tables](/taos-sql/table) for details. In the above SQL statement, "d1001" is the table name, "meters" is the STable name, followed by the value of tag "Location" and the value of tag "groupId", which are "Beijing.Chaoyang" and "2" respectively in the example. The tag values can be updated after the table is created. Please refer to [Tables](/taos-sql/table) for details.
:::warning :::warning
It's not recommended to create a table in a database while using a stable from another database as template. It's not recommended to create a table in a database while using a STable from another database as template.
:::tip :::tip
It's suggested to use the global unique ID of a data collecting point as the table name, for example the device serial number. If there isn't such a unique ID, multiple IDs that are not global unique can be combined to form a global unique ID. It's not recommended to use a global unique ID as tag value. It's suggested to use the global unique ID of a data collection point as the table name, for example the device serial number. If there isn't such a unique ID, multiple IDs that are not global unique can be combined to form a global unique ID. It's not recommended to use a global unique ID as tag value.
## Create Table Automatically ## Create Table Automatically
...@@ -73,7 +75,7 @@ In some circumstances, it's not sure whether the table already exists when inser ...@@ -73,7 +75,7 @@ In some circumstances, it's not sure whether the table already exists when inser
INSERT INTO d1001 USING meters TAGS ("Beijng.Chaoyang", 2) VALUES (now, 10.2, 219, 0.32); INSERT INTO d1001 USING meters TAGS ("Beijng.Chaoyang", 2) VALUES (now, 10.2, 219, 0.32);
``` ```
In the above SQL statement, a row with value `(now, 10.2, 219, 0.32)` will be inserted into table "d1001". If table "d1001" doesn't exist, it will be created automatically using stable "meters" as template with tag value `"Beijing.Chaoyang", 2`. In the above SQL statement, a row with value `(now, 10.2, 219, 0.32)` will be inserted into table "d1001". If table "d1001" doesn't exist, it will be created automatically using STable "meters" as template with tag value `"Beijing.Chaoyang", 2`.
For more details please refer to [Create Table Automatically](/taos-sql/insert#automatically-create-table-when-inserting). For more details please refer to [Create Table Automatically](/taos-sql/insert#automatically-create-table-when-inserting).
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docs-en/04-develop/03-insert-data/02-influxdb-line.mdx
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measurement,tag_set field_set timestamp measurement,tag_set field_set timestamp
``` ```
- `measurement` will be used as the stable name - `measurement` will be used as the STable name
- `tag_set` will be used as tags, with format like `<tag_key>=<tag_value>,<tag_key>=<tag_value>` - `tag_set` will be used as tags, with format like `<tag_key>=<tag_value>,<tag_key>=<tag_value>`
- `field_set`will be used as data columns, with format like `<field_key>=<field_value>,<field_key>=<field_value>` - `field_set`will be used as data columns, with format like `<field_key>=<field_value>,<field_key>=<field_value>`
- `timestamp` is the primary key timestamp corresponding to this row of data - `timestamp` is the primary key timestamp corresponding to this row of data
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docs-en/04-develop/03-insert-data/03-opentsdb-telnet.mdx
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...@@ -21,9 +21,9 @@ A single line of text is used in OpenTSDB line protocol to represent one row of ...@@ -21,9 +21,9 @@ A single line of text is used in OpenTSDB line protocol to represent one row of
<metric> <timestamp> <value> <tagk_1>=<tagv_1>[ <tagk_n>=<tagv_n>] <metric> <timestamp> <value> <tagk_1>=<tagv_1>[ <tagk_n>=<tagv_n>]
``` ```
- `metric` will be used as stable name. - `metric` will be used as STable name.
- `timestamp` is the timestamp of current row of data. The time precision will be determined automatically based on the length of the timestamp. second and millisecond time precision are supported.\ - `timestamp` is the timestamp of current row of data. The time precision will be determined automatically based on the length of the timestamp. second and millisecond time precision are supported.\
- `value` is a physical variable which must be a numeric value, the corresponding column name is "value". - `value` is a metric which must be a numeric value, the corresponding column name is "value".
- The last part is tag sets separated by space, all tags will be converted to nchar type automatically. - The last part is tag sets separated by space, all tags will be converted to nchar type automatically.
For example: For example:
...@@ -60,13 +60,13 @@ Please refer to [OpenTSDB Telnet API](http://opentsdb.net/docs/build/html/api_te ...@@ -60,13 +60,13 @@ Please refer to [OpenTSDB Telnet API](http://opentsdb.net/docs/build/html/api_te
</TabItem> </TabItem>
</Tabs> </Tabs>
2 stables will be crated automatically while each stable has 4 rows of data in the above sample code. 2 STables will be crated automatically while each STable has 4 rows of data in the above sample code.
```cmd ```cmd
taos> use test; taos> use test;
Database changed. Database changed.
taos> show stables; taos> show STables;
name | created_time | columns | tags | tables | name | created_time | columns | tags | tables |
============================================================================================ ============================================================================================
meters.current | 2022-03-30 17:04:10.877 | 2 | 2 | 2 | meters.current | 2022-03-30 17:04:10.877 | 2 | 2 | 2 |
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docs-en/04-develop/03-insert-data/04-opentsdb-json.mdx
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] ]
``` ```
Similar to OpenTSDB line protocol, `metric` will be used as the stable name, `timestamp` is the timestamp to be used, `value` represents the physical variable collected, `tags` are the tag sets. Similar to OpenTSDB line protocol, `metric` will be used as the STable name, `timestamp` is the timestamp to be used, `value` represents the metric collected, `tags` are the tag sets.
Please refer to [OpenTSDB HTTP API](http://opentsdb.net/docs/build/html/api_http/put.html) for more details. Please refer to [OpenTSDB HTTP API](http://opentsdb.net/docs/build/html/api_http/put.html) for more details.
...@@ -77,13 +77,13 @@ Please refer to [OpenTSDB HTTP API](http://opentsdb.net/docs/build/html/api_http ...@@ -77,13 +77,13 @@ Please refer to [OpenTSDB HTTP API](http://opentsdb.net/docs/build/html/api_http
</TabItem> </TabItem>
</Tabs> </Tabs>
The above sample code will created 2 stables automatically while each stable has 2 rows of data. The above sample code will created 2 STables automatically while each STable has 2 rows of data.
```cmd ```cmd
taos> use test; taos> use test;
Database changed. Database changed.
taos> show stables; taos> show STables;
name | created_time | columns | tags | tables | name | created_time | columns | tags | tables |
============================================================================================ ============================================================================================
meters.current | 2022-03-29 16:05:25.193 | 2 | 2 | 1 | meters.current | 2022-03-29 16:05:25.193 | 2 | 2 | 1 |
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docs-en/04-develop/04-query-data/index.mdx
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...@@ -53,7 +53,7 @@ For detailed query syntax please refer to [Select](/taos-sql/select). ...@@ -53,7 +53,7 @@ For detailed query syntax please refer to [Select](/taos-sql/select).
## Join Query ## Join Query
In IoT use cases, there are always multiple data collecting points of same kind. A new concept, called STable (abbreviated for super table), is used in TDengine to represent a kind of data collecting points, and a table is used to represent a specific data collecting point. Tags are used by TDengine to represent the static properties of data collecting points. A specific data collecting point has its own values for static properties. By specifying filter conditions on tags, join query can be performed efficiently between all the tables belonging to same stable, i.e. same kind of data collecting points, can be. Aggregate functions applicable for tables can be used directly on stables, syntax is exactly same. In IoT use cases, there are always multiple data collection points of same kind. A new concept, called STable (abbreviated for super table), is used in TDengine to represent a kind of data collection points, and a table is used to represent a specific data collection point. Tags are used by TDengine to represent the static properties of data collection points. A specific data collection point has its own values for static properties. By specifying filter conditions on tags, join query can be performed efficiently between all the tables belonging to same STable, i.e. same kind of data collection points, can be. Aggregate functions applicable for tables can be used directly on STables, syntax is exactly same.
### Example 1 ### Example 1
...@@ -80,7 +80,7 @@ taos> SELECT count(*), max(current) FROM meters where groupId = 2 and ts > now - ...@@ -80,7 +80,7 @@ taos> SELECT count(*), max(current) FROM meters where groupId = 2 and ts > now -
Query OK, 1 row(s) in set (0.002136s) Query OK, 1 row(s) in set (0.002136s)
``` ```
Join query is allowed between only the tables of same stable. In [Select](/taos-sql/select), all query operations are marked as whether it supports stable or not. Join query is allowed between only the tables of same STable. In [Select](/taos-sql/select), all query operations are marked as whether it supports STable or not.
## Down Sampling and Interpolation ## Down Sampling and Interpolation
...@@ -95,7 +95,7 @@ taos> SELECT sum(current) FROM d1001 INTERVAL(10s); ...@@ -95,7 +95,7 @@ taos> SELECT sum(current) FROM d1001 INTERVAL(10s);
Query OK, 2 row(s) in set (0.000883s) Query OK, 2 row(s) in set (0.000883s)
``` ```
Down sampling can also be used for stable. For example, below SQL statement can be used to get the sum of current from all meters in BeiJing. Down sampling can also be used for STable. For example, below SQL statement can be used to get the sum of current from all meters in BeiJing.
``` ```
taos> SELECT SUM(current) FROM meters where location like "Beijing%" INTERVAL(1s); taos> SELECT SUM(current) FROM meters where location like "Beijing%" INTERVAL(1s);
...@@ -123,7 +123,7 @@ taos> SELECT SUM(current) FROM meters INTERVAL(1s, 500a); ...@@ -123,7 +123,7 @@ taos> SELECT SUM(current) FROM meters INTERVAL(1s, 500a);
Query OK, 5 row(s) in set (0.001521s) Query OK, 5 row(s) in set (0.001521s)
``` ```
In IoT use cases, it's hard to align the timestamp of the data collected by each collecting point. However, a lot of algorithms like FFT require the data to be aligned with same time interval and application programs have to handle by themselves in many systems. In TDengine, it's easy to achieve the alignment using down sampling. In IoT use cases, it's hard to align the timestamp of the data collected by each collection point. However, a lot of algorithms like FFT require the data to be aligned with same time interval and application programs have to handle by themselves in many systems. In TDengine, it's easy to achieve the alignment using down sampling.
Interpolation can be performed in TDengine if there is no data in a time range. Interpolation can be performed in TDengine if there is no data in a time range.
...@@ -133,7 +133,7 @@ For more details please refer to [Aggregate by Window](/taos-sql/interval). ...@@ -133,7 +133,7 @@ For more details please refer to [Aggregate by Window](/taos-sql/interval).
### Query ### Query
In the section describing [Insert](/develop/insert-data/sql-writing), a database named `power` is created and some data are inserted into stable `meters`. Below sample code demonstrates how to query the data in this stable. In the section describing [Insert](/develop/insert-data/sql-writing), a database named `power` is created and some data are inserted into STable `meters`. Below sample code demonstrates how to query the data in this STable.
<Tabs defaultValue="java" groupId="lang"> <Tabs defaultValue="java" groupId="lang">
<TabItem label="Java" value="java"> <TabItem label="Java" value="java">
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docs-en/04-develop/05-continuous-query.mdx
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...@@ -4,7 +4,7 @@ description: "Continuous query is a query that's executed automatically accordin ...@@ -4,7 +4,7 @@ description: "Continuous query is a query that's executed automatically accordin
title: "Continuous Query" title: "Continuous Query"
--- ---
Continuous query is a query that's executed automatically according to predefined frequency to provide aggregate query capability by time window, it's actually a simplified time driven stream computing. Continuous query can be performed on a table or stable in TDengine. The result of continuous query can be pushed to client or written back to TDengine. Each query is executed on a time window, which moves forward with time. The size of time window and the forward sliding time need to be specified with parameter `INTERVAL` and `SLIDING` respectively. Continuous query is a query that's executed automatically according to predefined frequency to provide aggregate query capability by time window, it's actually a simplified time driven stream computing. Continuous query can be performed on a table or STable in TDengine. The result of continuous query can be pushed to client or written back to TDengine. Each query is executed on a time window, which moves forward with time. The size of time window and the forward sliding time need to be specified with parameter `INTERVAL` and `SLIDING` respectively.
Continuous query in TDengine is time driven, and can be defined using TAOS SQL directly without any extra operations. With continuous query, the result can be generated according to time window to achieve down sampling of 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 client or written to TDengine. Continuous query in TDengine is time driven, and can be defined using TAOS SQL directly without any extra operations. With continuous query, the result can be generated according to time window to achieve down sampling of 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 client or written to TDengine.
...@@ -30,7 +30,7 @@ SLIDING: The time step for which the time window moves forward each time ...@@ -30,7 +30,7 @@ SLIDING: The time step for which the time window moves forward each time
## How to Use ## 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 sub tables have been created using below SQL statement. In this section the use case of meters will be used to introduce how to use continuous query. Assume the STable and sub tables have been created using below SQL statement.
```sql ```sql
create table meters (ts timestamp, current float, voltage int, phase float) tags (location binary(64), groupId int); create table meters (ts timestamp, current float, voltage int, phase float) tags (location binary(64), groupId int);
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docs-en/04-develop/06-subscribe.mdx
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...@@ -28,7 +28,7 @@ taos_consume ...@@ -28,7 +28,7 @@ taos_consume
taos_unsubscribe taos_unsubscribe
``` ```
For more details about these API 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 sub tables please refer to the previous section "continuous query". Full sample code can be found [here](https://github.com/taosdata/TDengine/blob/master/examples/c/subscribe.c). For more details about these API 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 sub tables please refer to the previous section "continuous query". Full sample code can be found [here](https://github.com/taosdata/TDengine/blob/master/examples/c/subscribe.c).
If we want to get notification and take some actions if the current exceeds a threshold, like 10A, from some meters, there are two ways: If we want to get notification and take some actions if the current exceeds a threshold, like 10A, from some meters, there are two ways:
...@@ -42,7 +42,7 @@ select * from D1002 where ts > {last_timestamp2} and current > 10; ...@@ -42,7 +42,7 @@ 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 grows. Finally the performance of both client side and server side will be unacceptable once the number of meters grows to a big enough number. The above way works, but the problem is that the number of `select` statements increases with the number of meters grows. Finally 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: A better way is to query on the STable, only one `select` is enough regardless of the number of meters, like below:
```sql ```sql
select * from meters where ts > {last_timestamp} and current > 10; select * from meters where ts > {last_timestamp} and current > 10;
...@@ -155,7 +155,7 @@ Now let's see the effect of the above sample code, assuming below prerequisites ...@@ -155,7 +155,7 @@ Now let's see the effect of the above sample code, assuming below prerequisites
- The sample code has been downloaded to local system 示 - The sample code has been downloaded to local system 示
- TDengine has been installed and launched properly on same system - TDengine has been installed and launched properly on same system
- The database, stable, sub tables required in the sample code have been ready - The database, STable, sub tables required in the sample code have been ready
It's ready to launch below command in the directory where the sample code resides to compile and start the program. It's ready to launch below command in the directory where the sample code resides to compile and start the program.
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docs-en/04-develop/07-cache.md
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...@@ -12,7 +12,7 @@ The memory space used by TDengine cache is fixed in size, according to the confi ...@@ -12,7 +12,7 @@ The memory space used by TDengine cache is fixed in size, according to the confi
Memory pool is divided into blocks and data is stored in row format in memory and each block follows FIFO policy. The size of each block is determined by configuration parameter `cache`, the number of blocks for each vnode is determined by `blocks`. For each vnode, the total cache size is `cache * blocks`. It's better to set the size of each block to hold at least tends of rows. Memory pool is divided into blocks and data is stored in row format in memory and each block follows FIFO policy. The size of each block is determined by configuration parameter `cache`, the number of blocks for each vnode is determined by `blocks`. For each vnode, the total cache size is `cache * blocks`. It's better to set the size of each block to hold at least tends of rows.
`last_row` function can be used to retrieve the last row of a table or a stable to quickly show the current state of devices on monitoring screen. For example below SQL statement retrieves the latest voltage of all meters in Chaoyang district of Beijing. `last_row` function can be used to retrieve the last row of a table or a STable to quickly show the current state of devices on monitoring screen. For example below SQL statement retrieves the latest voltage of all meters in Chaoyang district of Beijing.
```sql ```sql
select last_row(voltage) from meters where location='Beijing.Chaoyang'; select last_row(voltage) from meters where location='Beijing.Chaoyang';
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docs-en/04-develop/08-udf.md
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...@@ -43,7 +43,7 @@ Below function template can be used to define your own aggregate function. ...@@ -43,7 +43,7 @@ Below function template can be used to define your own aggregate function.
`void abs_max_merge(char* data, int32_t numOfRows, char* dataOutput, int32_t* numOfOutput, SUdfInit* buf)` `void abs_max_merge(char* data, int32_t numOfRows, char* dataOutput, int32_t* numOfOutput, SUdfInit* buf)`
`udfMergeFunc` is the place holder of function name, the function implemented with the above template is used to aggregate the intermediate result, only can be used in the aggregate query for stable. `udfMergeFunc` is the place holder of function name, the function implemented with the above template is used to aggregate the intermediate result, only can be used in the aggregate query for STable.
Definitions of the parameters: Definitions of the parameters:
...@@ -55,7 +55,7 @@ Definitions of the parameters: ...@@ -55,7 +55,7 @@ Definitions of the parameters:
[abs_max.c](https://github.com/taosdata/TDengine/blob/develop/tests/script/sh/abs_max.c) is an user defined aggregate function to get the maximum from the absolute value of a column. [abs_max.c](https://github.com/taosdata/TDengine/blob/develop/tests/script/sh/abs_max.c) is an user defined aggregate function to get the maximum from the absolute value of a column.
The internal processing is that the data affected by the select statement will be divided into multiple row blocks and `udfNormalFunc`, i.e. `abs_max` in this case, is performed on each row block to generate the intermediate of each sub table, then `udfMergeFunc`, i.e. `abs_max_merge` in this case, is performed on the intermediate result of sub tables to aggregate to generate the final or intermediate result of stable. The intermediate result of stable is finally processed by `udfFinalizeFunc` to generate the final result, which contain either 0 or 1 row. The internal processing is that the data affected by the select statement will be divided into multiple row blocks and `udfNormalFunc`, i.e. `abs_max` in this case, is performed on each row block to generate the intermediate of each sub table, then `udfMergeFunc`, i.e. `abs_max_merge` in this case, is performed on the intermediate result of sub tables to aggregate to generate the final or intermediate result of STable. The intermediate result of STable is finally processed by `udfFinalizeFunc` to generate the final result, which contain either 0 or 1 row.
Other typical scenarios, like covariance, can also be achieved by aggregate UDF. Other typical scenarios, like covariance, can also be achieved by aggregate UDF.
...@@ -79,7 +79,7 @@ The naming of 3 kinds of UDF, i.e. udfNormalFunc, udfMergeFunc, and udfFinalizeF ...@@ -79,7 +79,7 @@ The naming of 3 kinds of UDF, i.e. udfNormalFunc, udfMergeFunc, and udfFinalizeF
According to the kind of UDF to implement, the functions that need to be implemented are different. According to the kind of UDF to implement, the functions that need to be implemented are different.
- Scalar function：udfNormalFunc is required - Scalar function：udfNormalFunc is required
- Aggregate function：udfNormalFunc, udfMergeFunc (if query on stable) and udfFinalizeFunc are required - Aggregate function：udfNormalFunc, udfMergeFunc (if query on STable) and udfFinalizeFunc are required
To be more accurate, assuming we want to implement a UDF named "foo". If the function is a scalar function, what we really need to implement is `foo`; if the function is aggregate function, we need to implement `foo`, `foo_merge`, and `foo_finalize`. For aggregate UDF, even though one of the three functions is not necessary, there must be an empty implementation. To be more accurate, assuming we want to implement a UDF named "foo". If the function is a scalar function, what we really need to implement is `foo`; if the function is aggregate function, we need to implement `foo`, `foo_merge`, and `foo_finalize`. For aggregate UDF, even though one of the three functions is not necessary, there must be an empty implementation.
...@@ -164,7 +164,7 @@ SHOW FUNCTIONS; ...@@ -164,7 +164,7 @@ SHOW FUNCTIONS;
The function name specified when creating UDF can be used directly in SQL statements, just like builtin functions. The function name specified when creating UDF can be used directly in SQL statements, just like builtin functions.
```sql ```sql
SELECT X(c) FROM table/stable; SELECT X(c) FROM table/STable;
``` ```
The above SQL statement invokes function X for column c. The above SQL statement invokes function X for column c.
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docs-en/12-taos-sql/04-stable.md
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...@@ -5,14 +5,14 @@ title: Super Table ...@@ -5,14 +5,14 @@ title: Super Table
:::note :::note
Keyword `STABLE`, abbreviated for super table, is supported since version 2.0.15. Keyword `STable`, abbreviated for super table, is supported since version 2.0.15.
::: :::
## Crate STable ## Crate STable
``` ```
CREATE STABLE [IF NOT EXISTS] stb_name (timestamp_field_name TIMESTAMP, field1_name data_type1 [, field2_name data_type2 ...]) TAGS (tag1_name tag_type1, tag2_name tag_type2 [, tag3_name tag_type3]); CREATE STable [IF NOT EXISTS] stb_name (timestamp_field_name TIMESTAMP, field1_name data_type1 [, field2_name data_type2 ...]) TAGS (tag1_name tag_type1, tag2_name tag_type2 [, tag3_name tag_type3]);
``` ```
The SQL statement of creating STable is similar to that of creating table, but a special column named as `TAGS` must be specified with the names and types of the tags. The SQL statement of creating STable is similar to that of creating table, but a special column named as `TAGS` must be specified with the names and types of the tags.
...@@ -29,15 +29,15 @@ The SQL statement of creating STable is similar to that of creating table, but a ...@@ -29,15 +29,15 @@ The SQL statement of creating STable is similar to that of creating table, but a
## Drop STable ## Drop STable
``` ```
DROP STABLE [IF EXISTS] stb_name; DROP STable [IF EXISTS] stb_name;
``` ```
All the sub-tables created using the deleted stable will be deleted automatically. All the sub-tables created using the deleted STable will be deleted automatically.
## Show All STables ## Show All STables
``` ```
SHOW STABLES [LIKE tb_name_wildcard]; SHOW STableS [LIKE tb_name_wildcard];
``` ```
This command can be used to display the information of all STables in the current database, including name, creation time, number of columns, number of tags, number of tables created using this STable. This command can be used to display the information of all STables in the current database, including name, creation time, number of columns, number of tags, number of tables created using this STable.
...@@ -45,7 +45,7 @@ This command can be used to display the information of all STables in the curren ...@@ -45,7 +45,7 @@ This command can be used to display the information of all STables in the curren
## Show The Create Statement of A STable ## Show The Create Statement of A STable
``` ```
SHOW CREATE STABLE stb_name; SHOW CREATE STable stb_name;
``` ```
This command is useful in migrating data from one TDengine cluster to another one because it can be used to create an exactly same STable in the target database. This command is useful in migrating data from one TDengine cluster to another one because it can be used to create an exactly same STable in the target database.
...@@ -61,19 +61,19 @@ DESCRIBE stb_name; ...@@ -61,19 +61,19 @@ DESCRIBE stb_name;
### Add A Column ### Add A Column
``` ```
ALTER STABLE stb_name ADD COLUMN field_name data_type; ALTER STable stb_name ADD COLUMN field_name data_type;
``` ```
### Remove A Column ### Remove A Column
``` ```
ALTER STABLE stb_name DROP COLUMN field_name; ALTER STable stb_name DROP COLUMN field_name;
``` ```
### Change Column Length ### Change Column Length
``` ```
ALTER STABLE stb_name MODIFY COLUMN field_name data_type(length); ALTER STable stb_name MODIFY COLUMN field_name data_type(length);
``` ```
This command can be used to change (or incerase, more specifically) the length of a column of variable length types, like BINARY or NCHAR. This command can be used to change (or incerase, more specifically) the length of a column of variable length types, like BINARY or NCHAR.
...@@ -83,7 +83,7 @@ This command can be used to change (or incerase, more specifically) the length o ...@@ -83,7 +83,7 @@ This command can be used to change (or incerase, more specifically) the length o
### Add A Tag ### Add A Tag
``` ```
ALTER STABLE stb_name ADD TAG new_tag_name tag_type; ALTER STable stb_name ADD TAG new_tag_name tag_type;
``` ```
This command is used to add a new tag for a STable and specify the tag type. This command is used to add a new tag for a STable and specify the tag type.
...@@ -91,7 +91,7 @@ This command is used to add a new tag for a STable and specify the tag type. ...@@ -91,7 +91,7 @@ This command is used to add a new tag for a STable and specify the tag type.
### Remove A Tag ### Remove A Tag
``` ```
ALTER STABLE stb_name DROP TAG tag_name; ALTER STable stb_name DROP TAG tag_name;
``` ```
The tag will be removed automatically from all the sub tables crated using the super table as template once a tag is removed from a super table. The tag will be removed automatically from all the sub tables crated using the super table as template once a tag is removed from a super table.
...@@ -99,7 +99,7 @@ The tag will be removed automatically from all the sub tables crated using the s ...@@ -99,7 +99,7 @@ The tag will be removed automatically from all the sub tables crated using the s
### Change A Tag ### Change A Tag
``` ```
ALTER STABLE stb_name CHANGE TAG old_tag_name new_tag_name; ALTER STable stb_name CHANGE TAG old_tag_name new_tag_name;
``` ```
The tag name will be changed automatically from all the sub tables crated using the super table as template once a tag name is changed for a super table. The tag name will be changed automatically from all the sub tables crated using the super table as template once a tag name is changed for a super table.
...@@ -107,7 +107,7 @@ The tag name will be changed automatically from all the sub tables crated using ...@@ -107,7 +107,7 @@ The tag name will be changed automatically from all the sub tables crated using
### Change Tag Length ### Change Tag Length
``` ```
ALTER STABLE stb_name MODIFY TAG tag_name data_type(length); ALTER STable stb_name MODIFY TAG tag_name data_type(length);
``` ```
This command can be used to change (or incerase, more specifically) the length of a tag of variable length types, like BINARY or NCHAR. This command can be used to change (or incerase, more specifically) the length of a tag of variable length types, like BINARY or NCHAR.
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docs-en/12-taos-sql/05-insert.md
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...@@ -131,10 +131,10 @@ Firstly, a super table is created. ...@@ -131,10 +131,10 @@ Firstly, a super table is created.
CREATE TABLE meters(ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS(location BINARY(30), groupId INT); CREATE TABLE meters(ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS(location BINARY(30), groupId INT);
``` ```
It can be proved that the super table has been created by `SHOW STABLES`, but no table exists by `SHOW TABLES`. It can be proved that the super table has been created by `SHOW STableS`, but no table exists by `SHOW TABLES`.
``` ```
taos> SHOW STABLES; taos> SHOW STableS;
name | created_time | columns | tags | tables | name | created_time | columns | tags | tables |
============================================================================================ ============================================================================================
meters | 2020-08-06 17:50:27.831 | 4 | 2 | 0 | meters | 2020-08-06 17:50:27.831 | 4 | 2 | 0 |
...@@ -156,7 +156,7 @@ The output shows the value to be inserted is invalid. But `SHOW TABLES` proves t ...@@ -156,7 +156,7 @@ The output shows the value to be inserted is invalid. But `SHOW TABLES` proves t
DB error: invalid SQL: 'a' (invalid timestamp) (0.039494s) DB error: invalid SQL: 'a' (invalid timestamp) (0.039494s)
taos> SHOW TABLES; taos> SHOW TABLES;
table_name | created_time | columns | stable_name | table_name | created_time | columns | STable_name |
====================================================================================================== ======================================================================================================
d1001 | 2020-08-06 17:52:02.097 | 4 | meters | d1001 | 2020-08-06 17:52:02.097 | 4 | meters |
Query OK, 1 row(s) in set (0.001091s) Query OK, 1 row(s) in set (0.001091s)
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docs-en/12-taos-sql/06-select.md
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...@@ -216,7 +216,7 @@ Query OK, 1 row(s) in set (0.000081s) ...@@ -216,7 +216,7 @@ Query OK, 1 row(s) in set (0.000081s)
## \_block_dist ## \_block_dist
**Description**: Get the data block distribution of a table or stable. **Description**: Get the data block distribution of a table or STable.
```SQL title="Syntax" ```SQL title="Syntax"
SELECT _block_dist() FROM { tb_name | stb_name } SELECT _block_dist() FROM { tb_name | stb_name }
...@@ -226,7 +226,7 @@ SELECT _block_dist() FROM { tb_name | stb_name } ...@@ -226,7 +226,7 @@ SELECT _block_dist() FROM { tb_name | stb_name }
**Sub Query**：Sub query or nested query are not supported **Sub Query**：Sub query or nested query are not supported
**Return value**: A string which includes the data block distribution of the specified table or stable, i.e. the histogram of rows stored in the data blocks of the table or stable. **Return value**: A string which includes the data block distribution of the specified table or STable, i.e. the histogram of rows stored in the data blocks of the table or STable.
```text title="Result" ```text title="Result"
summary: summary:
...@@ -235,7 +235,7 @@ summary: ...@@ -235,7 +235,7 @@ summary:
**More explanation about above example**: **More explanation about above example**:
- Histogram about the rows stored in the data blocks of the table or stable: the value of rows for 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, and 99% - Histogram about the rows stored in the data blocks of the table or STable: the value of rows for 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, and 99%
- Minimum number of rows stored in a data block, i.e. Min=[392(Rows)] - Minimum number of rows stored in a data block, i.e. Min=[392(Rows)]
- Maximum number of rows stored in a data block, i.e. Max=[800(Rows)] - Maximum number of rows stored in a data block, i.e. Max=[800(Rows)]
- Average number of rows stored in a data block, i.e. Avg=[666(Rows)] - Average number of rows stored in a data block, i.e. Avg=[666(Rows)]
...@@ -347,7 +347,7 @@ The maximum length of regular expression string is 128 bytes. Configuration para ...@@ -347,7 +347,7 @@ The maximum length of regular expression string is 128 bytes. Configuration para
## JOIN ## JOIN
From version 2.2.0.0, inner join is fully supported in TDengine. More specifically, the inner join between table and table, that between stable and stable, and that between sub query and sub query are supported. From version 2.2.0.0, inner join is fully supported in TDengine. More specifically, the inner join between table and table, that between STable and STable, and that between sub query and sub query are supported.
Only primary key, i.e. timestamp, can be used in the join operation between table and table. For example: Only primary key, i.e. timestamp, can be used in the join operation between table and table. For example:
...@@ -357,11 +357,11 @@ FROM temp_tb_1 t1, pressure_tb_1 t2 ...@@ -357,11 +357,11 @@ FROM temp_tb_1 t1, pressure_tb_1 t2
WHERE t1.ts = t2.ts WHERE t1.ts = t2.ts
``` ```
In the join operation between stable and stable, besides the primary key, i.e. timestamp, tags can also be used. For example: In the join operation between STable and STable, besides the primary key, i.e. timestamp, tags can also be used. For example:
```sql ```sql
SELECT * SELECT *
FROM temp_stable t1, temp_stable t2 FROM temp_STable t1, temp_STable t2
WHERE t1.ts = t2.ts AND t1.deviceid = t2.deviceid AND t1.status=0; WHERE t1.ts = t2.ts AND t1.deviceid = t2.deviceid AND t1.status=0;
``` ```
...@@ -370,7 +370,7 @@ Similary, join operation can be performed on the result set of multiple sub quer ...@@ -370,7 +370,7 @@ Similary, join operation can be performed on the result set of multiple sub quer
:::note :::note
Restrictions on join operation: Restrictions on join operation:
- The number of tables or stables in single join operation can't exceed 10. - The number of tables or STables in single join operation can't exceed 10.
- `FILL` is not allowed in the query statement that includes JOIN operation. - `FILL` is not allowed in the query statement that includes JOIN operation.
- Arithmetic operation is not allowed on the result set of join operation. - Arithmetic operation is not allowed on the result set of join operation.
- `GROUP BY` is not allowed on a part of tables that participate in join operation. - `GROUP BY` is not allowed on a part of tables that participate in join operation.
...@@ -394,7 +394,7 @@ SELECT ... FROM (SELECT ... FROM ...) ...; ...@@ -394,7 +394,7 @@ SELECT ... FROM (SELECT ... FROM ...) ...;
- Only one layer of nesting is allowed, that means no sub query is allowed in a sub query - Only one layer of nesting is allowed, that means no sub query is allowed in a sub query
- The result set returned by the inner query will be used as a "virtual table" by the outer query, the "virtual table" can be renamed using `AS` keyword for easy reference in the outer query. - The result set returned by the inner query will be used as a "virtual table" by the outer query, the "virtual table" can be renamed using `AS` keyword for easy reference in the outer query.
- Sub query is not allowed in continuous query. - Sub query is not allowed in continuous query.
- JOIN operation is allowed between tables/stables inside both inner and outer queries. Join operation can be performed on the result set of the inner query. - JOIN operation is allowed between tables/STables inside both inner and outer queries. Join operation can be performed on the result set of the inner query.
- UNION operation is not allowed in either inner query or outer query. - UNION operation is not allowed in either inner query or outer query.
- The functionalities that can be used in the inner query is same as non-nested query. - The functionalities that can be used in the inner query is same as non-nested query.
- `ORDER BY` inside the inner query doesn't make any sense but will slow down the query performance significantly, so please avoid such usage. - `ORDER BY` inside the inner query doesn't make any sense but will slow down the query performance significantly, so please avoid such usage.
......
docs-en/12-taos-sql/07-function.md
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...@@ -48,13 +48,13 @@ Query OK, 1 row(s) in set (0.001075s) ...@@ -48,13 +48,13 @@ Query OK, 1 row(s) in set (0.001075s)
SELECT AVG(field_name) FROM tb_name [WHERE clause]; SELECT AVG(field_name) FROM tb_name [WHERE clause];
``` ```
**Description**:Get the average value of a column in a table or stable **Description**:Get the average value of a column in a table or STable
**Return value type**:Double precision floating number **Return value type**:Double precision floating number
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**Examples**: **Examples**:
...@@ -84,11 +84,11 @@ SELECT TWA(field_name) FROM tb_name WHERE clause; ...@@ -84,11 +84,11 @@ SELECT TWA(field_name) FROM tb_name WHERE clause;
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**More explanations**: **More explanations**:
- From version 2.1.3.0, function TWA can be used on stble with `GROUP BY`, i.e. timelines generated by `GROUP BY tbname` on a stable. - From version 2.1.3.0, function TWA can be used on stble with `GROUP BY`, i.e. timelines generated by `GROUP BY tbname` on a STable.
### IRATE ### IRATE
...@@ -102,11 +102,11 @@ SELECT IRATE(field_name) FROM tb_name WHERE clause; ...@@ -102,11 +102,11 @@ SELECT IRATE(field_name) FROM tb_name WHERE clause;
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**More explanations**: **More explanations**:
- From version 2.1.3.0, function IRATE can be used on stble with `GROUP BY`, i.e. timelines generated by `GROUP BY tbname` on a stable. - From version 2.1.3.0, function IRATE can be used on stble with `GROUP BY`, i.e. timelines generated by `GROUP BY tbname` on a STable.
### SUM ### SUM
...@@ -114,13 +114,13 @@ SELECT IRATE(field_name) FROM tb_name WHERE clause; ...@@ -114,13 +114,13 @@ SELECT IRATE(field_name) FROM tb_name WHERE clause;
SELECT SUM(field_name) FROM tb_name [WHERE clause]; SELECT SUM(field_name) FROM tb_name [WHERE clause];
``` ```
**Description**:The sum of a specific column in a table or stable **Description**:The sum of a specific column in a table or STable
**Return value type**:Double precision floating number or long integer **Return value type**:Double precision floating number or long integer
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**Examples**: **Examples**:
...@@ -144,13 +144,13 @@ Query OK, 1 row(s) in set (0.000980s) ...@@ -144,13 +144,13 @@ Query OK, 1 row(s) in set (0.000980s)
SELECT STDDEV(field_name) FROM tb_name [WHERE clause]; SELECT STDDEV(field_name) FROM tb_name [WHERE clause];
``` ```
**Description**:Standard deviation of a specific column in a table or stable **Description**:Standard deviation of a specific column in a table or STable
**Return value type**:Double precision floating number **Return value type**:Double precision floating number
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable (starting from version 2.0.15.1) **Applicable table types**:table, STable (starting from version 2.0.15.1)
**Examples**: **Examples**:
...@@ -270,13 +270,13 @@ When any selective function is used, timestamp column or tag columns including ` ...@@ -270,13 +270,13 @@ When any selective function is used, timestamp column or tag columns including `
SELECT MIN(field_name) FROM {tb_name | stb_name} [WHERE clause]; SELECT MIN(field_name) FROM {tb_name | stb_name} [WHERE clause];
``` ```
**Description**:The minimum value of a specific column in a table or stable **Description**:The minimum value of a specific column in a table or STable
**Return value type**:Same as the data type of the column being operated **Return value type**:Same as the data type of the column being operated
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**Examples**: **Examples**:
...@@ -300,13 +300,13 @@ Query OK, 1 row(s) in set (0.000950s) ...@@ -300,13 +300,13 @@ Query OK, 1 row(s) in set (0.000950s)
SELECT MAX(field_name) FROM { tb_name | stb_name } [WHERE clause]; SELECT MAX(field_name) FROM { tb_name | stb_name } [WHERE clause];
``` ```
**Description**:The maximum value of a specific column of a table or stable **Description**:The maximum value of a specific column of a table or STable
**Return value type**:Same as the data type of the column being operated **Return value type**:Same as the data type of the column being operated
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**Examples**: **Examples**:
...@@ -330,13 +330,13 @@ Query OK, 1 row(s) in set (0.000987s) ...@@ -330,13 +330,13 @@ Query OK, 1 row(s) in set (0.000987s)
SELECT FIRST(field_name) FROM { tb_name | stb_name } [WHERE clause]; SELECT FIRST(field_name) FROM { tb_name | stb_name } [WHERE clause];
``` ```
**Description**:The first non-null value of a specific column in a table or stable **Description**:The first non-null value of a specific column in a table or STable
**Return value type**:Same as the column being operated **Return value type**:Same as the column being operated
**Applicable column types**:Any data type **Applicable column types**:Any data type
**Applicable table types**:table, stable **Applicable table types**:table, STable
**More explanations**: **More explanations**:
...@@ -366,19 +366,19 @@ Query OK, 1 row(s) in set (0.001023s) ...@@ -366,19 +366,19 @@ Query OK, 1 row(s) in set (0.001023s)
SELECT LAST(field_name) FROM { tb_name | stb_name } [WHERE clause]; SELECT LAST(field_name) FROM { tb_name | stb_name } [WHERE clause];
``` ```
**Description**:The last non-NULL value of a specific column in a table or stable **Description**:The last non-NULL value of a specific column in a table or STable
**Return value type**:Same as the column being operated **Return value type**:Same as the column being operated
**Applicable column types**:Any data type **Applicable column types**:Any data type
**Applicable table types**:table, stable **Applicable table types**:table, STable
**More explanations**: **More explanations**:
- LAST(\*) can be used to get the last non-NULL value of all columns - LAST(\*) can be used to get the last non-NULL value of all columns
- If the values of a column in the result set are all NULL, NULL is returned for that column; if all columns in the result are all NULL, no result will be returned. - If the values of a column in the result set are all NULL, NULL is returned for that column; if all columns in the result are all NULL, no result will be returned.
- When it's used on a stable, if there are multiple values with the timestamp in the result set, one of them will be returned randomly and it's not guaranteed that the same value is returned if the same query is run multiple times. - When it's used on a STable, if there are multiple values with the timestamp in the result set, one of them will be returned randomly and it's not guaranteed that the same value is returned if the same query is run multiple times.
**Examples**: **Examples**:
...@@ -402,13 +402,13 @@ Query OK, 1 row(s) in set (0.000843s) ...@@ -402,13 +402,13 @@ Query OK, 1 row(s) in set (0.000843s)
SELECT TOP(field_name, K) FROM { tb_name | stb_name } [WHERE clause]; SELECT TOP(field_name, K) FROM { tb_name | stb_name } [WHERE clause];
``` ```
**Description**: The greatest _k_ values of a specific column in a table or stable. If a value has multiple occurrences in the column but counting all of them in will exceed the upper limit _k_, then a part of them will be returned randomly. **Description**: The greatest _k_ values of a specific column in a table or STable. If a value has multiple occurrences in the column but counting all of them in will exceed the upper limit _k_, then a part of them will be returned randomly.
**Return value type**:Same as the column being operated **Return value type**:Same as the column being operated
**Applicable column types**:Data types except for timestamp, binary, nchar and bool **Applicable column types**:Data types except for timestamp, binary, nchar and bool
**Applicable table types**:table, stable **Applicable table types**:table, STable
**More explanations**: **More explanations**:
...@@ -441,13 +441,13 @@ Query OK, 2 row(s) in set (0.000810s) ...@@ -441,13 +441,13 @@ Query OK, 2 row(s) in set (0.000810s)
SELECT BOTTOM(field_name, K) FROM { tb_name | stb_name } [WHERE clause]; SELECT BOTTOM(field_name, K) FROM { tb_name | stb_name } [WHERE clause];
``` ```
**Description**:The least _k_ values of a specific column in a table or stable. If a value has multiple occurrences in the column but counting all of them in will exceed the upper limit _k_, then a part of them will be returned randomly. **Description**:The least _k_ values of a specific column in a table or STable. If a value has multiple occurrences in the column but counting all of them in will exceed the upper limit _k_, then a part of them will be returned randomly.
**Return value type**:Same as the column being operated **Return value type**:Same as the column being operated
**Applicable column types**: Data types except for timestamp, binary, nchar and bool **Applicable column types**: Data types except for timestamp, binary, nchar and bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -512,7 +512,7 @@ FROM { tb_name | stb_name } [WHERE clause] ...@@ -512,7 +512,7 @@ FROM { tb_name | stb_name } [WHERE clause]
**Applicable column types**: Data types except for timestamp, binary, nchar and bool **Applicable column types**: Data types except for timestamp, binary, nchar and bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations** **More explanations**
...@@ -548,17 +548,17 @@ Query OK, 1 row(s) in set (0.011639s) ...@@ -548,17 +548,17 @@ Query OK, 1 row(s) in set (0.011639s)
SELECT LAST_ROW(field_name) FROM { tb_name | stb_name }; SELECT LAST_ROW(field_name) FROM { tb_name | stb_name };
``` ```
**Description**: The last row of a table or stable **Description**: The last row of a table or STable
**Return value type**: Same as the column being operated **Return value type**: Same as the column being operated
**Applicable column types**: Any data type **Applicable column types**: Any data type
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
- When it's used against a stable, multiple rows with the same and largest timestamp may exist, in this case one of them is returned randomly and it's not guaranteed that the result is same if the query is run multiple times. - When it's used against a STable, multiple rows with the same and largest timestamp may exist, in this case one of them is returned randomly and it's not guaranteed that the result is same if the query is run multiple times.
- Can't be used with `INTERVAL`. - Can't be used with `INTERVAL`.
**Examples**: **Examples**:
...@@ -589,7 +589,7 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [ ...@@ -589,7 +589,7 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [
**Applicable column types**: Numeric data types **Applicable column types**: Numeric data types
**Applicable table types**: table, stable, nested query **Applicable table types**: table, STable, nested query
**More explanations** **More explanations**
...@@ -598,7 +598,7 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [ ...@@ -598,7 +598,7 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } [WHERE where_condition] [
- 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 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. - 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. - 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. - `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 result of `INTERP` is not influenced by `ORDER BY TIMESTAMP`, which impacts the output order only..
**Examples**: Based on the `meters` schema used throughout the documents **Examples**: Based on the `meters` schema used throughout the documents
...@@ -645,13 +645,13 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } WHERE ts='timestamp' [FILL ...@@ -645,13 +645,13 @@ SELECT INTERP(field_name) FROM { tb_name | stb_name } WHERE ts='timestamp' [FILL
**Applicable column types**: Numeric data type **Applicable column types**: Numeric data type
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
- It can be used from version 2.0.15.0 - It can be used from version 2.0.15.0
- Time slice must be specified. If there is no data matching the specified time slice, interpolation is performed based on `FILL` parameter. Conditions such as tags or `tbname` can be used `Where` clause can be used to filter data. - Time slice must be specified. If there is no data matching the specified time slice, interpolation is performed based on `FILL` parameter. Conditions such as tags or `tbname` can be used `Where` clause can be used to filter data.
- The timestamp specified must be within the time range of the data rows of the table or stable. If it is beyond the valid time range, nothing is returned even with `FILL` parameter. - The timestamp specified must be within the time range of the data rows of the table or STable. If it is beyond the valid time range, nothing is returned even with `FILL` parameter.
- `INTERP` can be used to query only single time point once. `INTERP` can be used with `EVERY` to get the interpolation value every time interval. - `INTERP` can be used to query only single time point once. `INTERP` can be used with `EVERY` to get the interpolation value every time interval.
- **Examples**: - **Examples**:
...@@ -741,7 +741,7 @@ SELECT UNIQUE(field_name) FROM {tb_name | stb_name} [WHERE clause]; ...@@ -741,7 +741,7 @@ SELECT UNIQUE(field_name) FROM {tb_name | stb_name} [WHERE clause];
**More explanations**: **More explanations**:
- It can be used against table or stable, but can't be used together with time window, like `interval`, `state_window` or `session_window` . - It can be used against table or STable, but can't be used together with time window, like `interval`, `state_window` or `session_window` .
- Considering the number of result sets is unpredictable, it's suggested to limit the distinct values under 100,000 to control the memory usage, otherwise error will be returned. - Considering the number of result sets is unpredictable, it's suggested to limit the distinct values under 100,000 to control the memory usage, otherwise error will be returned.
**Examples**: **Examples**:
...@@ -785,12 +785,12 @@ SELECT {DIFF(field_name, ignore_negative) | DIFF(field_name)} FROM tb_name [WHER ...@@ -785,12 +785,12 @@ SELECT {DIFF(field_name, ignore_negative) | DIFF(field_name)} FROM tb_name [WHER
**Applicable column types**: Data types except for timestamp, binary, nchar and bool **Applicable column types**: Data types except for timestamp, binary, nchar and bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
- The number of result rows is the number of rows subtracted by one, no output for the first row - The number of result rows is the number of rows subtracted by one, no output for the first row
- From version 2.1.30, `DIFF` can be used on stable with `GROUP by tbname` - From version 2.1.30, `DIFF` can be used on STable with `GROUP by tbname`
- From version 2.6.0, `ignore_negative` parameter is supported - From version 2.6.0, `ignore_negative` parameter is supported
**Examples**: **Examples**:
...@@ -816,12 +816,12 @@ SELECT DERIVATIVE(field_name, time_interval, ignore_negative) FROM tb_name [WHER ...@@ -816,12 +816,12 @@ SELECT DERIVATIVE(field_name, time_interval, ignore_negative) FROM tb_name [WHER
**Applicable column types**: Data types except for timestamp, binary, nchar and bool **Applicable column types**: Data types except for timestamp, binary, nchar and bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
- It is available from version 2.1.3.0, the number of result rows is the number of total rows in the time range subtracted by one, no output for the first row.\ - It is available from version 2.1.3.0, the number of result rows is the number of total rows in the time range subtracted by one, no output for the first row.\
- It can be used together with `GROUP BY tbname` against a stable. - It can be used together with `GROUP BY tbname` against a STable.
**Examples**: **Examples**:
...@@ -849,7 +849,7 @@ SELECT SPREAD(field_name) FROM { tb_name | stb_name } [WHERE clause]; ...@@ -849,7 +849,7 @@ SELECT SPREAD(field_name) FROM { tb_name | stb_name } [WHERE clause];
**Applicable column types**: Data types except for binary, nchar, and bool **Applicable column types**: Data types except for binary, nchar, and bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: Can be used on a column of TIMESTAMP type, the result is the time range size.可 **More explanations**: Can be used on a column of TIMESTAMP type, the result is the time range size.可
...@@ -881,7 +881,7 @@ SELECT CEIL(field_name) FROM { tb_name | stb_name } [WHERE clause]; ...@@ -881,7 +881,7 @@ SELECT CEIL(field_name) FROM { tb_name | stb_name } [WHERE clause];
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: inner query and outer query **Applicable nested query**: inner query and outer query
...@@ -913,9 +913,9 @@ SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause]; ...@@ -913,9 +913,9 @@ SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause];
### CSUM ### CSUM
```sql ```sql
SELECT CSUM(field_name) FROM { tb_name | stb_name } [WHERE clause] SELECT CSUM(field_name) FROM { tb_name | stb_name } [WHERE clause]
``` ```
**Description**: The cumulative sum of each row for a specific column. The number of output rows is same as that of the input rows. **Description**: The cumulative sum of each row for a specific column. The number of output rows is same as that of the input rows.
...@@ -923,24 +923,24 @@ SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause]; ...@@ -923,24 +923,24 @@ SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause];
**Applicable data types**: Data types except for timestamp, binary, nchar, and bool **Applicable data types**: Data types except for timestamp, binary, nchar, and bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
**More explanations**: **More explanations**:
- Can't be used on tags when it's used on stable - Can't be used on tags when it's used on STable
- Arithmetic operation can't be performed on the result of `csum` function - Arithmetic operation can't be performed on the result of `csum` function
- Can only be used with aggregate functions - Can only be used with aggregate functions
- `Group by tbname` must be used together on a stable to force the result on a single timeline - `Group by tbname` must be used together on a STable to force the result on a single timeline
**Applicable versions**: From 2.3.0.x **Applicable versions**: From 2.3.0.x
### MAVG ### MAVG
```sql ```sql
SELECT MAVG(field_name, K) FROM { tb_name | stb_name } [WHERE clause] SELECT MAVG(field_name, K) FROM { tb_name | stb_name } [WHERE clause]
``` ```
**Description**: The moving average of continuous _k_ values of a specific column. If the number of input rows is less than _k_, nothing is returned. The applicable range is _k_ is [1,1000]. **Description**: The moving average of continuous _k_ values of a specific column. If the number of input rows is less than _k_, nothing is returned. The applicable range is _k_ is [1,1000].
...@@ -950,37 +950,37 @@ SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause]; ...@@ -950,37 +950,37 @@ SELECT ROUND(field_name) FROM { tb_name | stb_name } [WHERE clause];
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
- Arithmetic operation can't be performed on the result of `MAVG`. - Arithmetic operation can't be performed on the result of `MAVG`.
- Can only be used with data columns, can't be used with tags. - Can only be used with data columns, can't be used with tags.
- Can't be used with aggregate functions.\（Aggregation）函数一起使用； - Can't be used with aggregate functions.\（Aggregation）函数一起使用；
- Must be used with `GROUP BY tbname` when it's used on a stable to force the result on each single timeline.该 - Must be used with `GROUP BY tbname` when it's used on a STable to force the result on each single timeline.该
**Applicable versions**: From 2.3.0.x **Applicable versions**: From 2.3.0.x
### SAMPLE ### SAMPLE
```sql ```sql
SELECT SAMPLE(field_name, K) FROM { tb_name | stb_name } [WHERE clause] SELECT SAMPLE(field_name, K) FROM { tb_name | stb_name } [WHERE clause]
``` ```
**Description**: _k_ sampling values of a specific column. The applicable range of _k_ is [1,10000] **Description**: _k_ sampling values of a specific column. The applicable range of _k_ is [1,10000]
**Return value type**: Same as the column being operated plus the associated timestamp **Return value type**: Same as the column being operated plus the associated timestamp
**Applicable data types**: Any data type except for tags of stable **Applicable data types**: Any data type except for tags of STable
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
**More explanations**: **More explanations**:
- Arithmetic operation can't be operated on the result of `SAMPLE` function - Arithmetic operation can't be operated on the result of `SAMPLE` function
- Must be used with `Group by tbname` when it's used on a stable to force the result on each single timeline - Must be used with `Group by tbname` when it's used on a STable to force the result on each single timeline
**Applicable versions**: From 2.3.0.x **Applicable versions**: From 2.3.0.x
...@@ -996,7 +996,7 @@ SELECT ASIN(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -996,7 +996,7 @@ SELECT ASIN(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1019,7 +1019,7 @@ SELECT ACOS(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1019,7 +1019,7 @@ SELECT ACOS(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1044,7 +1044,7 @@ SELECT ATAN(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1044,7 +1044,7 @@ SELECT ATAN(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1069,7 +1069,7 @@ SELECT SIN(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1069,7 +1069,7 @@ SELECT SIN(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1094,7 +1094,7 @@ SELECT COS(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1094,7 +1094,7 @@ SELECT COS(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1119,7 +1119,7 @@ SELECT TAN(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1119,7 +1119,7 @@ SELECT TAN(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1142,7 +1142,7 @@ SELECT POW(field_name, power) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1142,7 +1142,7 @@ SELECT POW(field_name, power) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1165,7 +1165,7 @@ SELECT LOG(field_name, base) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1165,7 +1165,7 @@ SELECT LOG(field_name, base) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1188,7 +1188,7 @@ SELECT ABS(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1188,7 +1188,7 @@ SELECT ABS(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1211,7 +1211,7 @@ SELECT SQRT(field_name) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1211,7 +1211,7 @@ SELECT SQRT(field_name) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: Data types except for timestamp, binary, nchar, bool **Applicable data types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1261,7 +1261,7 @@ SELECT CONCAT(str1|column1, str2|column2, ...) FROM { tb_name | stb_name } [WHER ...@@ -1261,7 +1261,7 @@ SELECT CONCAT(str1|column1, str2|column2, ...) FROM { tb_name | stb_name } [WHER
**Applicable data types**: The input data must be in either all BINARY or in all NCHAR; can't be used on tag columns **Applicable data types**: The input data must be in either all BINARY or in all NCHAR; can't be used on tag columns
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1279,7 +1279,7 @@ SELECT CONCAT_WS(separator, str1|column1, str2|column2, ...) FROM { tb_name | st ...@@ -1279,7 +1279,7 @@ SELECT CONCAT_WS(separator, str1|column1, str2|column2, ...) FROM { tb_name | st
**Applicable data types**: The input data must be in either all BINARY or in all NCHAR; can't be used on tag columns **Applicable data types**: The input data must be in either all BINARY or in all NCHAR; can't be used on tag columns
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1301,7 +1301,7 @@ SELECT LENGTH(str|column) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1301,7 +1301,7 @@ SELECT LENGTH(str|column) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1323,7 +1323,7 @@ SELECT CHAR_LENGTH(str|column) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1323,7 +1323,7 @@ SELECT CHAR_LENGTH(str|column) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1345,7 +1345,7 @@ SELECT LOWER(str|column) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1345,7 +1345,7 @@ SELECT LOWER(str|column) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1367,7 +1367,7 @@ SELECT UPPER(str|column) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1367,7 +1367,7 @@ SELECT UPPER(str|column) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1389,7 +1389,7 @@ SELECT LTRIM(str|column) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1389,7 +1389,7 @@ SELECT LTRIM(str|column) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1411,7 +1411,7 @@ SELECT RTRIM(str|column) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1411,7 +1411,7 @@ SELECT RTRIM(str|column) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1433,7 +1433,7 @@ SELECT SUBSTR(str,pos[,len]) FROM { tb_name | stb_name } [WHERE clause] ...@@ -1433,7 +1433,7 @@ SELECT SUBSTR(str,pos[,len]) FROM { tb_name | stb_name } [WHERE clause]
**Applicable data types**: BINARY or NCHAR, can't be used on tags **Applicable data types**: BINARY or NCHAR, can't be used on tags
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Inner query and Outer query **Applicable nested query**: Inner query and Outer query
...@@ -1457,7 +1457,7 @@ SELECT field_name [+|-|*|/|%][Value|field_name] FROM { tb_name | stb_name } [WH ...@@ -1457,7 +1457,7 @@ SELECT field_name [+|-|*|/|%][Value|field_name] FROM { tb_name | stb_name } [WH
**Applicable column types**: Data types except for timestamp, binary, nchar, bool **Applicable column types**: Data types except for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -1493,7 +1493,7 @@ SELECT STATECOUNT(field_name, oper, val) FROM { tb_name | stb_name } [WHERE clau ...@@ -1493,7 +1493,7 @@ SELECT STATECOUNT(field_name, oper, val) FROM { tb_name | stb_name } [WHERE clau
**Applicable data types**: Data types excpet for timestamp, binary, nchar, bool **Applicable data types**: Data types excpet for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Outer query only **Applicable nested query**: Outer query only
...@@ -1501,7 +1501,7 @@ SELECT STATECOUNT(field_name, oper, val) FROM { tb_name | stb_name } [WHERE clau ...@@ -1501,7 +1501,7 @@ SELECT STATECOUNT(field_name, oper, val) FROM { tb_name | stb_name } [WHERE clau
**More explanations**: **More explanations**:
- Must be used together with `GROUP BY tbname` when it's used on a stable to force the result into each single timeline] - Must be used together with `GROUP BY tbname` when it's used on a STable to force the result into each single timeline]
- Can't be used with window operation, like interval/state_window/session_window - Can't be used with window operation, like interval/state_window/session_window
**Examples**: **Examples**:
...@@ -1548,7 +1548,7 @@ SELECT stateDuration(field_name, oper, val, unit) FROM { tb_name | stb_name } [W ...@@ -1548,7 +1548,7 @@ SELECT stateDuration(field_name, oper, val, unit) FROM { tb_name | stb_name } [W
**Applicable data types**: Data types excpet for timestamp, binary, nchar, bool **Applicable data types**: Data types excpet for timestamp, binary, nchar, bool
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Applicable nested query**: Outer query only **Applicable nested query**: Outer query only
...@@ -1556,7 +1556,7 @@ SELECT stateDuration(field_name, oper, val, unit) FROM { tb_name | stb_name } [W ...@@ -1556,7 +1556,7 @@ SELECT stateDuration(field_name, oper, val, unit) FROM { tb_name | stb_name } [W
**More explanations**: **More explanations**:
- Must be used together with `GROUP BY tbname` when it's used on a stable to force the result into each single timeline] - Must be used together with `GROUP BY tbname` when it's used on a STable to force the result into each single timeline]
- Can't be used with window operation, like interval/state_window/session_window - Can't be used with window operation, like interval/state_window/session_window
**Examples**: **Examples**:
...@@ -1603,7 +1603,7 @@ INSERT INTO tb_name VALUES (NOW(), ...); ...@@ -1603,7 +1603,7 @@ INSERT INTO tb_name VALUES (NOW(), ...);
**Applicable column types**: TIMESTAMP only **Applicable column types**: TIMESTAMP only
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -1650,7 +1650,7 @@ INSERT INTO tb_name VALUES (TODAY(), ...); ...@@ -1650,7 +1650,7 @@ INSERT INTO tb_name VALUES (TODAY(), ...);
**Applicable column types**: TIMESTAMP only **Applicable column types**: TIMESTAMP only
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -1695,7 +1695,7 @@ SELECT TIMEZONE() FROM { tb_name | stb_name } [WHERE clause]; ...@@ -1695,7 +1695,7 @@ SELECT TIMEZONE() FROM { tb_name | stb_name } [WHERE clause];
**Applicable column types**: None **Applicable column types**: None
**Applicable table types**: table, stable **Applicable table types**: table, STable
**Examples**: **Examples**:
...@@ -1719,7 +1719,7 @@ SELECT TO_ISO8601(ts_val | ts_col) FROM { tb_name | stb_name } [WHERE clause]; ...@@ -1719,7 +1719,7 @@ SELECT TO_ISO8601(ts_val | ts_col) FROM { tb_name | stb_name } [WHERE clause];
**Applicable column types**: TIMESTAMP, constant or a column **Applicable column types**: TIMESTAMP, constant or a column
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -1754,7 +1754,7 @@ SELECT TO_UNIXTIMESTAMP(datetime_string | ts_col) FROM { tb_name | stb_name } [W ...@@ -1754,7 +1754,7 @@ SELECT TO_UNIXTIMESTAMP(datetime_string | ts_col) FROM { tb_name | stb_name } [W
**Applicable column types**: Constant or column of BINARY/NCHAR **Applicable column types**: Constant or column of BINARY/NCHAR
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -1789,7 +1789,7 @@ SELECT TIMETRUNCATE(ts_val | datetime_string | ts_col, time_unit) FROM { tb_name ...@@ -1789,7 +1789,7 @@ SELECT TIMETRUNCATE(ts_val | datetime_string | ts_col, time_unit) FROM { tb_name
**Applicable column types**: UNIX timestamp constant, string constant of date/time format, or a column of timestamp **Applicable column types**: UNIX timestamp constant, string constant of date/time format, or a column of timestamp
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
...@@ -1833,7 +1833,7 @@ SELECT TIMEDIFF(ts_val1 | datetime_string1 | ts_col1, ts_val2 | datetime_string2 ...@@ -1833,7 +1833,7 @@ SELECT TIMEDIFF(ts_val1 | datetime_string1 | ts_col1, ts_val2 | datetime_string2
**Applicable column types**: UNIX timestamp constant, string constant of date/time format, or a column of TIMESTAMP type **Applicable column types**: UNIX timestamp constant, string constant of date/time format, or a column of TIMESTAMP type
**Applicable table types**: table, stable **Applicable table types**: table, STable
**More explanations**: **More explanations**:
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docs-en/12-taos-sql/08-interval.md
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...@@ -28,7 +28,7 @@ When the time length specified by `SLIDING` is same as that specified by `INTERV ...@@ -28,7 +28,7 @@ When the time length specified by `SLIDING` is same as that specified by `INTERV
## Status Window ## Status Window
In case of using integer, bool, or string to represent the device status at a moment, the continuous rows with same status belong to same status window. Once the status changes, the status window closes. As shown in the following figure，there are two status windows according to status, [2019-04-28 14:22:07，2019-04-28 14:22:10] and [2019-04-28 14:22:11，2019-04-28 14:22:12]. Status window is not applicable to stable for now. In case of using integer, bool, or string to represent the device status at a moment, the continuous rows with same status belong to same status window. Once the status changes, the status window closes. As shown in the following figure，there are two status windows according to status, [2019-04-28 14:22:07，2019-04-28 14:22:10] and [2019-04-28 14:22:11，2019-04-28 14:22:12]. Status window is not applicable to STable for now.
![Status Window](/img/sql/timewindow-3.png) ![Status Window](/img/sql/timewindow-3.png)
...@@ -48,7 +48,7 @@ The primary key, i.e. timestamp, is used to determine which session window the r ...@@ -48,7 +48,7 @@ The primary key, i.e. timestamp, is used to determine which session window the r
![Session Window](/img/sql/timewindow-2.png) ![Session Window](/img/sql/timewindow-2.png)
If the time interval between two continuous rows are withint the time interval specified by `tol_value` they belong to the same session window; otherwise a new session window is started automatically. Session window is not supported on stable for now. If the time interval between two continuous rows are withint the time interval specified by `tol_value` they belong to the same session window; otherwise a new session window is started automatically. Session window is not supported on STable for now.
## More On Window Aggregate ## More On Window Aggregate
...@@ -89,7 +89,7 @@ SELECT function_list FROM stb_name ...@@ -89,7 +89,7 @@ SELECT function_list FROM stb_name
1. Huge volume of interpolation output may be returned using `FILL`, so it's recommended to specify the time range when using `FILL`. The maximum interpolation values that can be returned in single query is 10,000,000. 1. Huge volume of interpolation output may be returned using `FILL`, so it's recommended to specify the time range when using `FILL`. The maximum interpolation values that can be returned in single query is 10,000,000.
2. The result set is in the ascending order of timestamp in aggregate by time window aggregate. 2. The result set is in the ascending order of timestamp in aggregate by time window aggregate.
3. If aggregate by window is used on stable, the aggregate function is performed on all the rows matching the filter conditions. If `GROUP BY` is not used in the query, the result set will be returned in ascending order of timestamp; otherwise the result set is not exactly in the order of ascending timestamp in each group. 3. If aggregate by window is used on STable, the aggregate function is performed on all the rows matching the filter conditions. If `GROUP BY` is not used in the query, the result set will be returned in ascending order of timestamp; otherwise the result set is not exactly in the order of ascending timestamp in each group.
::: :::
Aggregate by time window is also used in continuous query, please refer to [Continuous Query](/develop/continuous-query). Aggregate by time window is also used in continuous query, please refer to [Continuous Query](/develop/continuous-query).
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docs-en/12-taos-sql/09-limit.md
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...@@ -26,7 +26,7 @@ The legal character set is `[a-zA-Z0-9!?$%^&*()_–+={[}]:;@~#|<,>.?/]`. ...@@ -26,7 +26,7 @@ The legal character set is `[a-zA-Z0-9!?$%^&*()_–+={[}]:;@~#|<,>.?/]`.
- Maximum number of tags is 128. There must be at least 1 tag. The total length of tag values should not exceed 16K bytes. - Maximum number of tags is 128. There must be at least 1 tag. The total length of tag values should not exceed 16K bytes.
- Maximum length of singe SQL statement is 1048576, i.e. 1 MB bytes. It can be configured in the parameter `maxSQLLength` in the client side, the applicable range is [65480, 1048576]. - Maximum length of singe SQL statement is 1048576, i.e. 1 MB bytes. It can be configured in the parameter `maxSQLLength` in the client side, the applicable range is [65480, 1048576].
- At most 4096 columns (or 1024 prior to 2.1.7.0) can be returned by `SELECT`, functions in the query statement may constitute columns. Error will be returned if the limit is exceeded. - At most 4096 columns (or 1024 prior to 2.1.7.0) can be returned by `SELECT`, functions in the query statement may constitute columns. Error will be returned if the limit is exceeded.
- Maximum numbers of databases, stables, tables are only depending on the system resources. - Maximum numbers of databases, STables, tables are only depending on the system resources.
- Maximum of database name is 32 bytes, can't include "." and special characters. - Maximum of database name is 32 bytes, can't include "." and special characters.
- Maximum replica number of database is 3 - Maximum replica number of database is 3
- Maximum length of user name is 23 bytes - Maximum length of user name is 23 bytes
...@@ -47,10 +47,10 @@ The legal character set is `[a-zA-Z0-9!?$%^&*()_–+={[}]:;@~#|<,>.?/]`. ...@@ -47,10 +47,10 @@ The legal character set is `[a-zA-Z0-9!?$%^&*()_–+={[}]:;@~#|<,>.?/]`.
## Restrictions of `ORDER BY` ## Restrictions of `ORDER BY`
- Only one `order by` is allowed for normal table and sub table. - Only one `order by` is allowed for normal table and sub table.
- At most two `order by` are allowed for stable, and the second one must be `ts`. - At most two `order by` are allowed for STable, and the second one must be `ts`.
- `order by tag` must be used with `group by tag` on same tag, this rule is also applicable to `tbname`. - `order by tag` must be used with `group by tag` on same tag, this rule is also applicable to `tbname`.
- `order by column` must be used with `group by column` or `top/bottom` on same column. This rule is applicable to table and stable. - `order by column` must be used with `group by column` or `top/bottom` on same column. This rule is applicable to table and STable.
- `order by ts` is applicable to table and stable. - `order by ts` is applicable to table and STable.
- If `order by ts` is used with `group by`, the result set is sorted using `ts` in each group. - If `order by ts` is used with `group by`, the result set is sorted using `ts` in each group.
## Restrictions of Table/Column Names ## Restrictions of Table/Column Names
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docs-en/12-taos-sql/10-json.md
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...@@ -8,7 +8,7 @@ title: JSON Type ...@@ -8,7 +8,7 @@ title: JSON Type
1. Tag of JSON type 1. Tag of JSON type
```sql ```sql
create stable s1 (ts timestamp, v1 int) tags (info json); create STable s1 (ts timestamp, v1 int) tags (info json);
create table s1_1 using s1 tags ('{"k1": "v1"}'); create table s1_1 using s1 tags ('{"k1": "v1"}');
``` ```
...@@ -78,6 +78,6 @@ title: JSON Type ...@@ -78,6 +78,6 @@ title: JSON Type
For example, below SQL statements are not supported. For example, below SQL statements are not supported.
```sql; ```sql;
select jtag->'key' from (select jtag from stable); select jtag->'key' from (select jtag from STable);
select jtag->'key' from (select jtag from stable) where jtag->'key'>0; select jtag->'key' from (select jtag from STable) where jtag->'key'>0;
``` ```
docs-en/12-taos-sql/12-keywords.md
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...@@ -5,7 +5,7 @@ title: Reserved Keywords ...@@ -5,7 +5,7 @@ title: Reserved Keywords
## Reserved Keywords ## Reserved Keywords
There are about 200 keywords reserved by TDengine, they can't be used as the name of database, stable or table with either upper case, lower case or mixed case. There are about 200 keywords reserved by TDengine, they can't be used as the name of database, STable or table with either upper case, lower case or mixed case.
**Keywords List** **Keywords List**
...@@ -47,5 +47,5 @@ There are about 200 keywords reserved by TDengine, they can't be used as the nam ...@@ -47,5 +47,5 @@ There are about 200 keywords reserved by TDengine, they can't be used as the nam
| CONFLICT | GROUP | NE | SLIMIT | VGROUPS | | CONFLICT | GROUP | NE | SLIMIT | VGROUPS |
| CONNECTION | GT | NONE | SMALLINT | VIEW | | CONNECTION | GT | NONE | SMALLINT | VIEW |
| CONNECTIONS | HAVING | NOT | SOFFSET | VNODES | | CONNECTIONS | HAVING | NOT | SOFFSET | VNODES |
| CONNS | ID | NOTNULL | STABLE | WAL | | CONNS | ID | NOTNULL | STable | WAL |
| COPY | IF | NOW | STABLES | WHERE | | COPY | IF | NOW | STableS | WHERE |
docs-en/13-operation/08-export.md
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...@@ -7,14 +7,14 @@ There are two ways of exporting data from a TDengine cluster, one is SQL stateme ...@@ -7,14 +7,14 @@ There are two ways of exporting data from a TDengine cluster, one is SQL stateme
## Export Using SQL ## Export Using SQL
If you want to export the data of a table or a stable, please execute below SQL statement in TDengine CLI. If you want to export the data of a table or a STable, please execute below SQL statement in TDengine CLI.
```sql ```sql
select * from <tb_name> >> data.csv; select * from <tb_name> >> data.csv;
``` ```
The data of table or stable specified by `tb_name` will be exported into a file named `data.csv` in CSV format. The data of table or STable specified by `tb_name` will be exported into a file named `data.csv` in CSV format.
## Export Using taosdump ## Export Using taosdump
With `taosdump`, you can choose to export the data of all databases, a database, a table or a stable, you can also choose export the data within a time range, or even only export the schema definition of a table. For the details of using `taosdump` please refer to [Tool for exporting and importing data: taosdump](/reference/taosdump). With `taosdump`, you can choose to export the data of all databases, a database, a table or a STable, you can also choose export the data within a time range, or even only export the schema definition of a table. For the details of using `taosdump` please refer to [Tool for exporting and importing data: taosdump](/reference/taosdump).
docs-en/13-operation/11-optimize.md
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...@@ -15,7 +15,7 @@ Please be noted that a lot of disk I/O is required for defragementation operatio ...@@ -15,7 +15,7 @@ Please be noted that a lot of disk I/O is required for defragementation operatio
## Optimize Storage Parameters ## Optimize Storage Parameters
The data in different use cases may have different characteristics, such as the days to keep, number of replicas, collection interval, record size, number of collecting points, compression or not, etc. To achieve best efficiency in storage, the parameters in below table can be used, all of them can be either configured in `taos.cfg` as default configuration or in the command `create database`. For detailed definition of these parameters please refer to [Configuration Parameters](/reference/config/). The data in different use cases may have different characteristics, such as the days to keep, number of replicas, collection interval, record size, number of collection points, compression or not, etc. To achieve best efficiency in storage, the parameters in below table can be used, all of them can be either configured in `taos.cfg` as default configuration or in the command `create database`. For detailed definition of these parameters please refer to [Configuration Parameters](/reference/config/).
| # | Parameter | Unit | Definition | **Value Range** | **Default Value** | | # | Parameter | Unit | Definition | **Value Range** | **Default Value** |
| --- | --------- | ---- | ------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------- | ----------------- | | --- | --------- | ---- | ------------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------- | ----------------- |
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