Documentation
  • The Fundamental
  • ACTIVE SYNC
    • Data Ingestion
      • Data Tracking
        • API Key Management
        • Generate Tracking ID
        • Install tracking with Tag Manager
        • Install Tracking from the Console
        • Tracking Method on Website
      • Datasource
        • MySQL
        • PostgreSQL
        • MongoDB
        • Microsoft SQL Server
        • Shopify
        • CSV
        • Google Sheets
    • Data Ingestion API
      • Data Lake
        • File upload
        • Tracking API
      • Data Warehouse
        • Batch upload
        • CSV upload
        • Tracking API
      • Data Schema Warehouse API
    • Data Integrations
      • Manage your API Key
      • Get Data using API
  • ROCKET.BI
    • Introduction
    • Data Warehouse
      • Data Management
      • Ad-hoc Query
        • Measure Schema
        • Calculated Field
      • Query Analysis
      • Relationship
    • Row-level Security
    • Dashboard
      • Dashboard Filter
      • Chart Control
        • Tab Control
        • Single Choice
        • Multiple Choice
        • Dropdown Control
        • Slicer Control
        • Date Control
        • Input Control
      • Manage Dashboard
        • Relationship
        • View and Share
        • Select Main Date Filter
        • Boost
        • Settings
        • Add Chart
        • Add Tab
        • Add Text
    • Chart Builder
      • Chart Types
        • Pie Chart
        • Column Chart
        • Bar Chart
        • Line Chart
        • Line Stock Chart
        • Pareto Chart
        • Bubble Chart
        • Scatter Chart
        • Map Chart
        • Area Chart
        • KPI Chart
        • Lollipop Chart
        • Parliament Chart
        • Funnel Chart
        • Pyramid Chart
        • Gauge Chart
        • Bullet Graph Chart
        • Heat Map Chart
        • Word Cloud Chart
        • Tree Map Chart
        • Stacked Column Chart
        • Stacked Bar Chart
        • Sankey Chart
        • Spider Web Chart
        • Wind Rose Chart
        • Histogram Chart
        • Bell Curve Chart
        • Table Chart
        • Pivot Table Chart
      • Chart Settings
        • Zoom
        • Inner chart filter
      • Chart Filters
        • Tab Filter
        • Single Choice
        • Multiple Choice
        • Dropdown Filter
        • Slicer Filter
        • Date Filter
        • Input Filter
      • Right-click Settings
        • Change date function
        • Drill down
        • Drill through
        • Use as a filter
    • SQL Query
      • Syntax
      • Functions
      • Aggregate Functions
      • Data Types
  • UNLOCK.CI
    • Unlock.CI
Powered by GitBook
On this page
  • Spaces​
  • Comments​
  • Keywords​
  • Identifiers​
  • Literals​
  • Functions​
  • Operators​
  • Data Types and Database Table Engines​
  • Expression Aliases​
  • Asterisk​
  • Expressions​
  1. ROCKET.BI
  2. SQL Query

Syntax

PreviousSQL QueryNextFunctions

Last updated 2 years ago

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 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 .

Data can have any format. When a query is received, the server calculates no more than bytes of the request in RAM (by default, 1 MB), and the rest is stream parsed. It allows for avoiding issues with large INSERT queries.

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.

The rest of this article covers the full parser. For more information about format parsers, see the 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

ClickHouse supports either SQL-style and C-style comments:

  • SQL-style comments start with --, #! or # and continue to the end of the line, a space after -- and #! can be omitted.

  • C-style are from /* to */and can be multiline, spaces are not required either.

Keywords

Keywords are case-insensitive when they correspond to:

  • SQL standard. For example, SELECT, select and SeLeCt are all valid.

  • Implementation in some popular DBMS (MySQL or Postgres). For example, DateTime is the same as datetime.

In contrast to standard SQL, all other keywords (including functions names) are case-sensitive.

Identifiers are:

  • Cluster, database, table, partition, and column names.

  • Functions.

  • Data types.

Identifiers can be quoted or non-quoted. The latter is preferred.

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`.

There are numeric, string, compound, and NULL literals.

Numeric literal tries to be parsed:

  • Otherwise, it returns an error.

Examples: 1, 10_000_000, 0xffff_ffff, 18446744073709551615, 0xDEADBEEF, 01, 0.1, 1e100, -1e-100, inf, nan.

In string literals, you need to escape at least ' and \. Single quotes can be escaped with the single quote, literals 'It\'s' and 'It''s' are equal.

Indicates that the value is missing.

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 is also NULL. The same is true for multiplication, addition, and other operations. For more information, read the documentation for each operation.

You can use a heredoc to embed snippets of SQL, HTML, or XML code, etc.

Example

Query:

SELECT $smth$SHOW CREATE VIEW my_view$smth$;

Result:

┌─'SHOW CREATE VIEW my_view'─┐
│ SHOW CREATE VIEW my_view   │
└────────────────────────────┘

Function calls are written like an identifier with a list of arguments (possibly empty) in round brackets. In contrast to standard SQL, the brackets are required, even for an empty argument 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 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 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 argument list in brackets. For more information, see the sections “Data types,” “Table engines,” and “CREATE”.

An alias is a user-defined name for 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 a SELECT clause without using the AS keyword.

    For example, `SELECT table_name_alias.column_name FROM table_name table_name_alias`.
    
    In the [CAST](/docs/en/sql-reference/functions/type-conversion-functions#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`.
  • For example, `SELECT "table t".column_name FROM table_name AS "table t"`.

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 a SELECT query, an asterisk can replace the expression. For more information, see the section “SELECT”.

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.

You can check whether a data type name is case-sensitive in the table.

Keywords are not reserved; they are treated as such only in the corresponding context. If you use with the same name as the keywords, enclose them into double-quotes or backticks. For example, the query SELECT "FROM" FROM table_name is valid if the table table_name has column with the name "FROM".

Identifiers

.

Non-quoted identifiers must match the regex ^[a-zA-Z_][0-9a-zA-Z_]*$ and can not be equal to . Examples: x, _1, X_y__Z123_.

Literals

Numeric

First, as a 64-bit signed number, using the function.

If unsuccessful, as a 64-bit unsigned number, using the function.

If unsuccessful, as a floating-point number using the function.

Literal value has 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 . Underscores _ inside numeric literals are ignored and can be used for better readability.

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, , , , \0, \a, \v, \xHH. In all other cases, escape sequences in the format \c, where c is any character, are converted to c. It means that you can use the sequences \'and\\. The value will have the type.

Compound

Arrays are constructed with square brackets [1, 2, 3]. Tuples are constructed with round brackets (1, 'Hello, world!', 2). Technically 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. There’s a separate case when tuples appear in the IN clause of a SELECT query. Query results can include tuples, but tuples can’t be saved to a database (except of tables with engine).

NULL

In order to store NULL in a table field, it must be of the type.

Depending on the data format (input or output), NULL may have a different representation. For more information, see the documentation for .

In queries, you can check NULL using the and operators and the related functions isNull and isNotNull.

Heredoc

A is a way to define a string (often multiline), while maintaining the original formatting. A heredoc is defined as a custom string literal, placed between two $ symbols, for example $heredoc$. A value between two heredocs is processed "as-is".

Functions

Operators

Data Types and Database Table Engines

Expression Aliases

alias — Name for expr. Aliases should comply with the syntax.

Notes on Usage

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. You can change this default behavior by setting to 1.

Asterisk

Expressions

input_format_values_interpret_expressions
expression
max_query_size
Formats
​
​
​
system.data_type_families
identifiers
​
Expression aliases
keywords
​
​
strtoull
strtoll
strtod
Data types
​
String
​
Memory
​
Nullable
data formats
IS NULL
IS NOT NULL
​
heredoc
​
​
​
​
identifiers
​
prefer_column_name_to_alias
​
​