SELECT Clauses

January 3, 2025About 6 min

SELECT Clauses

1 Syntax Overview

SELECT selectItem (',' selectItem)*

selectItem
    : expression (AS? identifier)?                          #selectSingle
    | tableName '.' ASTERISK (AS columnAliases)?            #selectAll
    | ASTERISK                                              #selectAll
    ;

SELECT Clause: SELECT Clause: Specifies the columns to be included in the query results, including aggregate functions (such as SUM, AVG, COUNT, etc.) and window functions, which are logically executed last.

2 Detailed Syntax:

Each selectItem can be one of the following forms:

Expression: expression [ [ AS ] column_alias ] defines a single output column, and a column alias can be specified.
Selecting all columns of a relation: relation.* selects all columns of a certain relation, and column aliases are not allowed.
Selecting all columns in the result set: * selects all columns of the query, and column aliases are not allowed.

3 Example Data

In the Example Data page, there are SQL statements for building the table structure and inserting data. By downloading and executing these statements in the IoTDB CLI, you can import data into IoTDB. You can use this data to test and execute the SQL statements in the examples and obtain the corresponding results.

3.1 Select List

3.1.1 Star Expression

The asterisk (*) can be used to select all columns from a table. Note, the star expression cannot be transformed by most functions, except in the case of count(*).

Example: Select all columns from a table

SELECT * FROM table1;

The execution result is as follows:

+-----------------------------+------+--------+---------+--------+-----------+-----------+--------+------+-----------------------------+
|                         time|region|plant_id|device_id|model_id|maintenance|temperature|humidity|status|                   modifytime|
+-----------------------------+------+--------+---------+--------+-----------+-----------+--------+------+-----------------------------+
|2024-11-29T11:00:00.000+08:00|  上海|    3002|      100|       E|        180|       null|    45.1|  true|                         null|
|2024-11-29T18:30:00.000+08:00|  上海|    3002|      100|       E|        180|       90.0|    35.4|  true|2024-11-29T18:30:15.000+08:00|
|2024-11-28T08:00:00.000+08:00|  上海|    3001|      100|       C|         90|       85.0|    null|  null|2024-11-28T08:00:09.000+08:00|
|2024-11-28T09:00:00.000+08:00|  上海|    3001|      100|       C|         90|       null|    40.9|  true|                         null|
|2024-11-28T10:00:00.000+08:00|  上海|    3001|      100|       C|         90|       85.0|    35.2|  null|2024-11-28T10:00:11.000+08:00|
|2024-11-28T11:00:00.000+08:00|  上海|    3001|      100|       C|         90|       88.0|    45.1|  true|2024-11-28T11:00:12.000+08:00|
|2024-11-26T13:37:00.000+08:00|  北京|    1001|      100|       A|        180|       90.0|    35.1|  true|2024-11-26T13:37:34.000+08:00|
|2024-11-26T13:38:00.000+08:00|  北京|    1001|      100|       A|        180|       90.0|    35.1|  true|2024-11-26T13:38:25.000+08:00|
|2024-11-30T09:30:00.000+08:00|  上海|    3002|      101|       F|        360|       90.0|    35.2|  true|                         null|
|2024-11-30T14:30:00.000+08:00|  上海|    3002|      101|       F|        360|       90.0|    34.8|  true|2024-11-30T14:30:17.000+08:00|
|2024-11-29T10:00:00.000+08:00|  上海|    3001|      101|       D|        360|       85.0|    null|  null|2024-11-29T10:00:13.000+08:00|
|2024-11-27T16:38:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    35.1|  true|2024-11-26T16:37:01.000+08:00|
|2024-11-27T16:39:00.000+08:00|  北京|    1001|      101|       B|        180|       85.0|    35.3|  null|                         null|
|2024-11-27T16:40:00.000+08:00|  北京|    1001|      101|       B|        180|       85.0|    null|  null|2024-11-26T16:37:03.000+08:00|
|2024-11-27T16:41:00.000+08:00|  北京|    1001|      101|       B|        180|       85.0|    null|  null|2024-11-26T16:37:04.000+08:00|
|2024-11-27T16:42:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    35.2| false|                         null|
|2024-11-27T16:43:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    null| false|                         null|
|2024-11-27T16:44:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    null| false|2024-11-26T16:37:08.000+08:00|
+-----------------------------+------+--------+---------+--------+-----------+-----------+--------+------+-----------------------------+
Total line number = 18
It costs 0.653s

3.1.2 Aggregate Functions

Aggregate functions summarize multiple rows of data into a single value. When the SELECT clause contains aggregate functions, the query is considered an aggregate query. In aggregate queries, all expressions must be part of an aggregate function or specified by the GROUP BY clause for grouping.

Example 1: Return the total number of rows in the address table:

SELECT count(*) FROM table1;

The execution result is as follows:

+-----+
|_col0|
+-----+
|   18|
+-----+
Total line number = 1
It costs 0.091s

Example 2: Return the total number of rows in the address table grouped by city:

SELECT region, count(*) 
  FROM table1 
  GROUP BY region;

The execution result is as follows:

+------+-----+
|region|_col1|
+------+-----+
|  上海|    9|
|  北京|    9|
+------+-----+
Total line number = 2
It costs 0.071s

3.1.3 Aliases

The keyword AS is used to specify an alias for the selected column, which overrides the existing column name to improve the readability of the query results.

Example 1: Original Table:

IoTDB> SELECT * FROM table1;

The execution result is as follows:

+-----------------------------+------+--------+---------+--------+-----------+-----------+--------+------+-----------------------------+
|                         time|region|plant_id|device_id|model_id|maintenance|temperature|humidity|status|                   modifytime|
+-----------------------------+------+--------+---------+--------+-----------+-----------+--------+------+-----------------------------+
|2024-11-29T11:00:00.000+08:00|  上海|    3002|      100|       E|        180|       null|    45.1|  true|                         null|
|2024-11-29T18:30:00.000+08:00|  上海|    3002|      100|       E|        180|       90.0|    35.4|  true|2024-11-29T18:30:15.000+08:00|
|2024-11-28T08:00:00.000+08:00|  上海|    3001|      100|       C|         90|       85.0|    null|  null|2024-11-28T08:00:09.000+08:00|
|2024-11-28T09:00:00.000+08:00|  上海|    3001|      100|       C|         90|       null|    40.9|  true|                         null|
|2024-11-28T10:00:00.000+08:00|  上海|    3001|      100|       C|         90|       85.0|    35.2|  null|2024-11-28T10:00:11.000+08:00|
|2024-11-28T11:00:00.000+08:00|  上海|    3001|      100|       C|         90|       88.0|    45.1|  true|2024-11-28T11:00:12.000+08:00|
|2024-11-26T13:37:00.000+08:00|  北京|    1001|      100|       A|        180|       90.0|    35.1|  true|2024-11-26T13:37:34.000+08:00|
|2024-11-26T13:38:00.000+08:00|  北京|    1001|      100|       A|        180|       90.0|    35.1|  true|2024-11-26T13:38:25.000+08:00|
|2024-11-30T09:30:00.000+08:00|  上海|    3002|      101|       F|        360|       90.0|    35.2|  true|                         null|
|2024-11-30T14:30:00.000+08:00|  上海|    3002|      101|       F|        360|       90.0|    34.8|  true|2024-11-30T14:30:17.000+08:00|
|2024-11-29T10:00:00.000+08:00|  上海|    3001|      101|       D|        360|       85.0|    null|  null|2024-11-29T10:00:13.000+08:00|
|2024-11-27T16:38:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    35.1|  true|2024-11-26T16:37:01.000+08:00|
|2024-11-27T16:39:00.000+08:00|  北京|    1001|      101|       B|        180|       85.0|    35.3|  null|                         null|
|2024-11-27T16:40:00.000+08:00|  北京|    1001|      101|       B|        180|       85.0|    null|  null|2024-11-26T16:37:03.000+08:00|
|2024-11-27T16:41:00.000+08:00|  北京|    1001|      101|       B|        180|       85.0|    null|  null|2024-11-26T16:37:04.000+08:00|
|2024-11-27T16:42:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    35.2| false|                         null|
|2024-11-27T16:43:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    null| false|                         null|
|2024-11-27T16:44:00.000+08:00|  北京|    1001|      101|       B|        180|       null|    null| false|2024-11-26T16:37:08.000+08:00|
+-----------------------------+------+--------+---------+--------+-----------+-----------+--------+------+-----------------------------+
Total line number = 18
It costs 0.653s

Example 2: Single column alias setting:

IoTDB> SELECT device_id 
         AS device 
         FROM table1;

The execution result is as follows:

+------+
|device|
+------+
|   100|
|   100|
|   100|
|   100|
|   100|
|   100|
|   100|
|   100|
|   101|
|   101|
|   101|
|   101|
|   101|
|   101|
|   101|
|   101|
|   101|
|   101|
+------+
Total line number = 18
It costs 0.053s

Example 3: Aliases for all columns:

IoTDB> SELECT table1.* 
         AS (timestamp, Reg, Pl, DevID, Mod, Mnt, Temp, Hum, Stat,MTime) 
         FROM table1;

The execution result is as follows:

+-----------------------------+----+----+-----+---+---+----+----+-----+-----------------------------+
|                    TIMESTAMP| REG|  PL|DEVID|MOD|MNT|TEMP| HUM| STAT|                        MTIME|
+-----------------------------+----+----+-----+---+---+----+----+-----+-----------------------------+
|2024-11-29T11:00:00.000+08:00|上海|3002|  100|  E|180|null|45.1| true|                         null|
|2024-11-29T18:30:00.000+08:00|上海|3002|  100|  E|180|90.0|35.4| true|2024-11-29T18:30:15.000+08:00|
|2024-11-28T08:00:00.000+08:00|上海|3001|  100|  C| 90|85.0|null| null|2024-11-28T08:00:09.000+08:00|
|2024-11-28T09:00:00.000+08:00|上海|3001|  100|  C| 90|null|40.9| true|                         null|
|2024-11-28T10:00:00.000+08:00|上海|3001|  100|  C| 90|85.0|35.2| null|2024-11-28T10:00:11.000+08:00|
|2024-11-28T11:00:00.000+08:00|上海|3001|  100|  C| 90|88.0|45.1| true|2024-11-28T11:00:12.000+08:00|
|2024-11-26T13:37:00.000+08:00|北京|1001|  100|  A|180|90.0|35.1| true|2024-11-26T13:37:34.000+08:00|
|2024-11-26T13:38:00.000+08:00|北京|1001|  100|  A|180|90.0|35.1| true|2024-11-26T13:38:25.000+08:00|
|2024-11-30T09:30:00.000+08:00|上海|3002|  101|  F|360|90.0|35.2| true|                         null|
|2024-11-30T14:30:00.000+08:00|上海|3002|  101|  F|360|90.0|34.8| true|2024-11-30T14:30:17.000+08:00|
|2024-11-29T10:00:00.000+08:00|上海|3001|  101|  D|360|85.0|null| null|2024-11-29T10:00:13.000+08:00|
|2024-11-27T16:38:00.000+08:00|北京|1001|  101|  B|180|null|35.1| true|2024-11-26T16:37:01.000+08:00|
|2024-11-27T16:39:00.000+08:00|北京|1001|  101|  B|180|85.0|35.3| null|                         null|
|2024-11-27T16:40:00.000+08:00|北京|1001|  101|  B|180|85.0|null| null|2024-11-26T16:37:03.000+08:00|
|2024-11-27T16:41:00.000+08:00|北京|1001|  101|  B|180|85.0|null| null|2024-11-26T16:37:04.000+08:00|
|2024-11-27T16:42:00.000+08:00|北京|1001|  101|  B|180|null|35.2|false|                         null|
|2024-11-27T16:43:00.000+08:00|北京|1001|  101|  B|180|null|null|false|                         null|
|2024-11-27T16:44:00.000+08:00|北京|1001|  101|  B|180|null|null|false|2024-11-26T16:37:08.000+08:00|
+-----------------------------+----+----+-----+---+---+----+----+-----+-----------------------------+
Total line number = 18
It costs 0.189s

4 Result Set Column Order

Column order: The column order in the result set is the same as the order specified in the SELECT clause.
Multi column sorting: If an expression is selected to return multiple columns, their sorting method is the same as the sorting method in the source relationship.