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SELECT queries perform data retrieval. By default, the requested data is returned to the client, while in conjunction with INSERT INTO it can be forwarded to a different table.


[WITH expr_list|(subquery)]
SELECT [DISTINCT [ON (column1, column2, ...)]] expr_list
[FROM [db.]table | (subquery) | table_function] [FINAL]
[SAMPLE sample_coeff]
[GLOBAL] [ANY|ALL|ASOF] [INNER|LEFT|RIGHT|FULL|CROSS] [OUTER|SEMI|ANTI] JOIN (subquery)|table (ON <expr_list>)|(USING <column_list>)
[WHERE expr]
[HAVING expr]
[ORDER BY expr_list] [WITH FILL] [FROM expr] [TO expr] [STEP expr] [INTERPOLATE [(expr_list)]]
[LIMIT [offset_value, ]n BY columns]
[LIMIT [n, ]m] [WITH TIES]
[UNION ...]
[INTO OUTFILE filename [COMPRESSION type [LEVEL level]] ]
[FORMAT format]

All clauses are optional, except for the required list of expressions immediately after SELECT which is covered in more detail below.

Specifics of each optional clause are covered in separate sections, which are listed in the same order as they are executed:


Expressions specified in the SELECT clause are calculated after all the operations in the clauses described above are finished. These expressions work as if they apply to separate rows in the result. If expressions in the SELECT clause contain aggregate functions, then ClickHouse processes aggregate functions and expressions used as their arguments during the GROUP BY aggregation.

If you want to include all columns in the result, use the asterisk (*) symbol. For example, SELECT * FROM ....

Dynamic column selection

Dynamic column selection (also known as a COLUMNS expression) allows you to match some columns in a result with a re2 regular expression.


For example, consider the table:

CREATE TABLE default.col_names (aa Int8, ab Int8, bc Int8) ENGINE = TinyLog

The following query selects data from all the columns containing the a symbol in their name.

SELECT COLUMNS('a') FROM col_names
│ 1 │ 1 │

The selected columns are returned not in the alphabetical order.

You can use multiple COLUMNS expressions in a query and apply functions to them.

For example:

SELECT COLUMNS('a'), COLUMNS('c'), toTypeName(COLUMNS('c')) FROM col_names
│ 1 │ 1 │ 1 │ Int8 │

Each column returned by the COLUMNS expression is passed to the function as a separate argument. Also you can pass other arguments to the function if it supports them. Be careful when using functions. If a function does not support the number of arguments you have passed to it, ClickHouse throws an exception.

For example:

SELECT COLUMNS('a') + COLUMNS('c') FROM col_names
Received exception from server (version 19.14.1):
Code: 42. DB::Exception: Received from localhost:9000. DB::Exception: Number of arguments for function plus does not match: passed 3, should be 2.

In this example, COLUMNS('a') returns two columns: aa and ab. COLUMNS('c') returns the bc column. The + operator can’t apply to 3 arguments, so ClickHouse throws an exception with the relevant message.

Columns that matched the COLUMNS expression can have different data types. If COLUMNS does not match any columns and is the only expression in SELECT, ClickHouse throws an exception.


You can put an asterisk in any part of a query instead of an expression. When the query is analyzed, the asterisk is expanded to a list of all table columns (excluding the MATERIALIZED and ALIAS columns). There are only a few cases when using an asterisk is justified:

  • When creating a table dump.
  • For tables containing just a few columns, such as system tables.
  • For getting information about what columns are in a table. In this case, set LIMIT 1. But it is better to use the DESC TABLE query.
  • When there is strong filtration on a small number of columns using PREWHERE.
  • In subqueries (since columns that aren’t needed for the external query are excluded from subqueries).

In all other cases, we do not recommend using the asterisk, since it only gives you the drawbacks of a columnar DBMS instead of the advantages. In other words using the asterisk is not recommended.

Extreme Values

In addition to results, you can also get minimum and maximum values for the results columns. To do this, set the extremes setting to 1. Minimums and maximums are calculated for numeric types, dates, and dates with times. For other columns, the default values are output.

An extra two rows are calculated – the minimums and maximums, respectively. These extra two rows are output in XML, JSON*, TabSeparated*, CSV*, Vertical, Template and Pretty* formats, separate from the other rows. They are not output for other formats.

In JSON* and XML formats, the extreme values are output in a separate ‘extremes’ field. In TabSeparated*, CSV* and Vertical formats, the row comes after the main result, and after ‘totals’ if present. It is preceded by an empty row (after the other data). In Pretty* formats, the row is output as a separate table after the main result, and after totals if present. In Template format the extreme values are output according to specified template.

Extreme values are calculated for rows before LIMIT, but after LIMIT BY. However, when using LIMIT offset, size, the rows before offset are included in extremes. In stream requests, the result may also include a small number of rows that passed through LIMIT.


You can use synonyms (AS aliases) in any part of a query.

The GROUP BY, ORDER BY, and LIMIT BY clauses can support positional arguments. To enable this, switch on the enable_positional_arguments setting. Then, for example, ORDER BY 1,2 will be sorting rows in the table on the first and then the second column.

Implementation Details

If the query omits the DISTINCT, GROUP BY and ORDER BY clauses and the IN and JOIN subqueries, the query will be completely stream processed, using O(1) amount of RAM. Otherwise, the query might consume a lot of RAM if the appropriate restrictions are not specified:

  • max_memory_usage
  • max_rows_to_group_by
  • max_rows_to_sort
  • max_rows_in_distinct
  • max_bytes_in_distinct
  • max_rows_in_set
  • max_bytes_in_set
  • max_rows_in_join
  • max_bytes_in_join
  • max_bytes_before_external_sort
  • max_bytes_before_external_group_by

For more information, see the section “Settings”. It is possible to use external sorting (saving temporary tables to a disk) and external aggregation.

SELECT modifiers

You can use the following modifiers in SELECT queries.


Allows you to invoke some function for each row returned by an outer table expression of a query.


SELECT <expr> APPLY( <func> ) FROM [db.]table_name


CREATE TABLE columns_transformers (i Int64, j Int16, k Int64) ENGINE = MergeTree ORDER by (i);
INSERT INTO columns_transformers VALUES (100, 10, 324), (120, 8, 23);
SELECT * APPLY(sum) FROM columns_transformers;
│ 220 │ 18 │ 347 │


Specifies the names of one or more columns to exclude from the result. All matching column names are omitted from the output.


SELECT <expr> EXCEPT ( col_name1 [, col_name2, col_name3, ...] ) FROM [db.]table_name


SELECT * EXCEPT (i) from columns_transformers;
│ 10 │ 324 │
│ 8 │ 23 │


Specifies one or more expression aliases. Each alias must match a column name from the SELECT * statement. In the output column list, the column that matches the alias is replaced by the expression in that REPLACE.

This modifier does not change the names or order of columns. However, it can change the value and the value type.


SELECT <expr> REPLACE( <expr> AS col_name) from [db.]table_name


SELECT * REPLACE(i + 1 AS i) from columns_transformers;
│ 101 │ 10 │ 324 │
│ 121 │ 8 │ 23 │

Modifier Combinations

You can use each modifier separately or combine them.


Using the same modifier multiple times.

SELECT COLUMNS('[jk]') APPLY(toString) APPLY(length) APPLY(max) from columns_transformers;
│ 2 │ 3 │

Using multiple modifiers in a single query.

SELECT * REPLACE(i + 1 AS i) EXCEPT (j) APPLY(sum) from columns_transformers;
┌─sum(plus(i, 1))─┬─sum(k)─┐
│ 222 │ 347 │


You can specify the necessary settings right in the SELECT query. The setting value is applied only to this query and is reset to default or previous value after the query is executed.

Other ways to make settings see here.


SELECT * FROM some_table SETTINGS optimize_read_in_order=1, cast_keep_nullable=1;