* replace exit with assert in test_single_page * improve save_raw_single_page docs option * More grammar fixes * "Built from" link in new tab * fix mistype * Example of include in docs * add anchor to meeting form * Draft of translation helper * WIP on translation helper * Replace some fa docs content with machine translation * add normalize-en-markdown.sh * normalize some en markdown * normalize some en markdown * admonition support * normalize * normalize * normalize * support wide tables * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * normalize * lightly edited machine translation of introdpection.md * lightly edited machhine translation of lazy.md * WIP on translation utils * Normalize ru docs * Normalize other languages * some fixes * WIP on normalize/translate tools * add requirements.txt * [experimental] add es docs language as machine translated draft * remove duplicate script * Back to wider tab-stop (narrow renders not so well)
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Syntax
There are two types of parsers in the system: the full SQL parser (a recursive descent parser), and the data format parser (a fast stream parser).
In all cases except the INSERT
query, only the full SQL parser is used.
The INSERT
query uses both parsers:
INSERT INTO t VALUES (1, 'Hello, world'), (2, 'abc'), (3, 'def')
The INSERT INTO t VALUES
fragment is parsed by the full parser, and the data (1, 'Hello, world'), (2, 'abc'), (3, 'def')
is parsed by the fast stream parser. You can also turn on the full parser for the data by using the input_format_values_interpret_expressions setting. When input_format_values_interpret_expressions = 1
, ClickHouse first tries to parse values with the fast stream parser. If it fails, ClickHouse tries to use the full parser for the data, treating it like an SQL expression.
Data can have any format. When a query is received, the server calculates no more than max_query_size bytes of the request in RAM (by default, 1 MB), and the rest is stream parsed.
This means the system doesn’t have problems with large INSERT
queries, like MySQL does.
When using the Values
format in an INSERT
query, it may seem that data is parsed the same as expressions in a SELECT
query, but this is not true. The Values
format is much more limited.
Next we will cover the full parser. For more information about format parsers, see the Formats section.
Spaces
There may be any number of space symbols between syntactical constructions (including the beginning and end of a query). Space symbols include the space, tab, line feed, CR, and form feed.
Comments
SQL-style and C-style comments are supported.
SQL-style comments: from --
to the end of the line. The space after --
can be omitted.
Comments in C-style: from /*
to */
. These comments can be multiline. Spaces are not required here, either.
Keywords
Keywords are case-insensitive when they correspond to:
- SQL standard. For example,
SELECT
,select
andSeLeCt
are all valid. - Implementation in some popular DBMS (MySQL or Postgres). For example,
DateTime
is same asdatetime
.
Whether data type name is case-sensitive can be checked in the system.data_type_families
table.
In contrast to standard SQL all other keywords (including functions names) are case-sensitive.
Keywords are not reserved (they are just parsed as keywords in the corresponding context). If you use identifiers the same as the keywords, enclose them into quotes. For example, the query SELECT "FROM" FROM table_name
is valid if the table table_name
has column with the name "FROM"
.
Identifiers
Identifiers are:
- Cluster, database, table, partition and column names.
- Functions.
- Data types.
- Expression aliases.
Identifiers can be quoted or non-quoted. It is recommended to use non-quoted identifiers.
Non-quoted identifiers must match the regex ^[a-zA-Z_][0-9a-zA-Z_]*$
and can not be equal to keywords. Examples: x, _1, X_y__Z123_.
If you want to use identifiers the same as keywords or you want to use other symbols in identifiers, quote it using double quotes or backticks, for example, "id"
, `id`
.
Literals
There are: numeric, string, compound and NULL
literals.
Numeric
A numeric literal tries to be parsed:
- First as a 64-bit signed number, using the strtoull function.
- If unsuccessful, as a 64-bit unsigned number, using the strtoll function.
- If unsuccessful, as a floating-point number using the strtod function.
- Otherwise, an error is returned.
The corresponding value will have the smallest type that the value fits in.
For example, 1 is parsed as UInt8
, but 256 is parsed as UInt16
. For more information, see Data types.
Examples: 1
, 18446744073709551615
, 0xDEADBEEF
, 01
, 0.1
, 1e100
, -1e-100
, inf
, nan
.
String
Only string literals in single quotes are supported. The enclosed characters can be backslash-escaped. The following escape sequences have a corresponding special value: \b
, \f
, \r
, \n
, \t
, \0
, \a
, \v
, \xHH
. In all other cases, escape sequences in the format \c
, where c
is any character, are converted to c
. This means that you can use the sequences \'
and\\
. The value will have the String type.
The minimum set of characters that you need to escape in string literals: '
and \
. Single quote can be escaped with the single quote, literals 'It\'s'
and 'It''s'
are equal.
Compound
Constructions are supported for arrays: [1, 2, 3]
and tuples: (1, 'Hello, world!', 2)
..
Actually, these are not literals, but expressions with the array creation operator and the tuple creation operator, respectively.
An array must consist of at least one item, and a tuple must have at least two items.
Tuples have a special purpose for use in the IN
clause of a SELECT
query. Tuples can be obtained as the result of a query, but they can’t be saved to a database (with the exception of Memory tables).
NULL
Indicates that the value is missing.
In order to store NULL
in a table field, it must be of the Nullable type.
Depending on the data format (input or output), NULL
may have a different representation. For more information, see the documentation for data formats.
There are many nuances to processing NULL
. For example, if at least one of the arguments of a comparison operation is NULL
, the result of this operation will also be NULL
. The same is true for multiplication, addition, and other operations. For more information, read the documentation for each operation.
In queries, you can check NULL
using the IS NULL and IS NOT NULL operators and the related functions isNull
and isNotNull
.
Functions
Functions are written like an identifier with a list of arguments (possibly empty) in brackets. In contrast to standard SQL, the brackets are required, even for an empty arguments list. Example: now()
.
There are regular and aggregate functions (see the section “Aggregate functions”). Some aggregate functions can contain two lists of arguments in brackets. Example: quantile (0.9) (x)
. These aggregate functions are called “parametric” functions, and the arguments in the first list are called “parameters”. The syntax of aggregate functions without parameters is the same as for regular functions.
Operators
Operators are converted to their corresponding functions during query parsing, taking their priority and associativity into account.
For example, the expression 1 + 2 * 3 + 4
is transformed to plus(plus(1, multiply(2, 3)), 4)
.
Data Types and Database Table Engines
Data types and table engines in the CREATE
query are written the same way as identifiers or functions. In other words, they may or may not contain an arguments list in brackets. For more information, see the sections “Data types,” “Table engines,” and “CREATE”.
Expression Aliases
An alias is a user-defined name for an expression in a query.
expr AS alias
-
AS
— The keyword for defining aliases. You can define the alias for a table name or a column name in aSELECT
clause without using theAS
keyword.For example, `SELECT table_name_alias.column_name FROM table_name table_name_alias`. In the [CAST](functions/type_conversion_functions.md#type_conversion_function-cast) function, the `AS` keyword has another meaning. See the description of the function.
-
expr
— Any expression supported by ClickHouse.For example, `SELECT column_name * 2 AS double FROM some_table`.
-
alias
— Name forexpr
. Aliases should comply with the identifiers syntax.For example, `SELECT "table t".column_name FROM table_name AS "table t"`.
Notes on Usage
Aliases are global for a query or subquery and you can define an alias in any part of a query for any expression. For example, SELECT (1 AS n) + 2, n
.
Aliases are not visible in subqueries and between subqueries. For example, while executing the query SELECT (SELECT sum(b.a) + num FROM b) - a.a AS num FROM a
ClickHouse generates the exception Unknown identifier: num
.
If an alias is defined for the result columns in the SELECT
clause of a subquery, these columns are visible in the outer query. For example, SELECT n + m FROM (SELECT 1 AS n, 2 AS m)
.
Be careful with aliases that are the same as column or table names. Let’s consider the following example:
CREATE TABLE t
(
a Int,
b Int
)
ENGINE = TinyLog()
SELECT
argMax(a, b),
sum(b) AS b
FROM t
Received exception from server (version 18.14.17):
Code: 184. DB::Exception: Received from localhost:9000, 127.0.0.1. DB::Exception: Aggregate function sum(b) is found inside another aggregate function in query.
In this example, we declared table t
with column b
. Then, when selecting data, we defined the sum(b) AS b
alias. As aliases are global, ClickHouse substituted the literal b
in the expression argMax(a, b)
with the expression sum(b)
. This substitution caused the exception.
Asterisk
In a SELECT
query, an asterisk can replace the expression. For more information, see the section “SELECT”.
Expressions
An expression is a function, identifier, literal, application of an operator, expression in brackets, subquery, or asterisk. It can also contain an alias. A list of expressions is one or more expressions separated by commas. Functions and operators, in turn, can have expressions as arguments.