Skip to main content

Other Functions

hostName()

Returns the name of the host on which this function was executed. If the function executes on a remote server (distributed processing), the remote server name is returned. If the function executes in the context of a distributed table, it generates a normal column with values relevant to each shard. Otherwise it produces a constant value.

getMacro

Returns a named value from the macros section of the server configuration.

Syntax

getMacro(name);

Arguments

  • name — Macro name to retrieve from the <macros> section. String.

Returned value

  • Value of the specified macro.

Type: String.

Example

Example <macros> section in the server configuration file:

<macros>
<test>Value</test>
</macros>

Query:

SELECT getMacro('test');

Result:

┌─getMacro('test')─┐
│ Value │
└──────────────────┘

The same value can be retrieved as follows:

SELECT * FROM system.macros
WHERE macro = 'test';
┌─macro─┬─substitution─┐
│ test │ Value │
└───────┴──────────────┘

FQDN

Returns the fully qualified domain name of the ClickHouse server.

Syntax

fqdn();

This function is case-insensitive.

Returned value

  • String with the fully qualified domain name.

Type: String.

Example

SELECT FQDN();

Result:

┌─FQDN()──────────────────────────┐
│ clickhouse.ru-central1.internal │
└─────────────────────────────────┘

basename

Extracts the tail of a string following its last slash or backslash. This function if often used to extract the filename from a path.

basename(expr)

Arguments

  • expr — A value of type String. Backslashes must be escaped.

Returned Value

A string that contains:

  • The tail of the input string after its last slash or backslash. If the input string ends with a slash or backslash (e.g. / or c:\), the function returns an empty string.
  • The original string if there are no slashes or backslashes.

Example

Query:

SELECT 'some/long/path/to/file' AS a, basename(a)

Result:

┌─a──────────────────────┬─basename('some\\long\\path\\to\\file')─┐
│ some\long\path\to\file │ file │
└────────────────────────┴────────────────────────────────────────┘

Query:

SELECT 'some\\long\\path\\to\\file' AS a, basename(a)

Result:

┌─a──────────────────────┬─basename('some\\long\\path\\to\\file')─┐
│ some\long\path\to\file │ file │
└────────────────────────┴────────────────────────────────────────┘

Query:

SELECT 'some-file-name' AS a, basename(a)

Result:

┌─a──────────────┬─basename('some-file-name')─┐
│ some-file-name │ some-file-name │
└────────────────┴────────────────────────────┘

visibleWidth(x)

Calculates the approximate width when outputting values to the console in text format (tab-separated). This function is used by the system to implement Pretty formats.

NULL is represented as a string corresponding to NULL in Pretty formats.

SELECT visibleWidth(NULL)
┌─visibleWidth(NULL)─┐
│ 4 │
└────────────────────┘

toTypeName(x)

Returns the type name of the passed argument.

If NULL is passed, then the function returns type Nullable(Nothing), which corresponds to ClickHouse's internal NULL representation.

blockSize()

In ClickHouse, queries are processed in blocks (chunks). This function returns the size (row count) of the block the function is called on.

byteSize

Returns an estimation of uncompressed byte size of its arguments in memory.

Syntax

byteSize(argument [, ...])

Arguments

  • argument — Value.

Returned value

  • Estimation of byte size of the arguments in memory.

Type: UInt64.

Examples

For String arguments, the function returns the string length + 9 (terminating zero + length).

Query:

SELECT byteSize('string');

Result:

┌─byteSize('string')─┐
│ 15 │
└────────────────────┘

Query:

CREATE TABLE test
(
`key` Int32,
`u8` UInt8,
`u16` UInt16,
`u32` UInt32,
`u64` UInt64,
`i8` Int8,
`i16` Int16,
`i32` Int32,
`i64` Int64,
`f32` Float32,
`f64` Float64
)
ENGINE = MergeTree
ORDER BY key;

INSERT INTO test VALUES(1, 8, 16, 32, 64, -8, -16, -32, -64, 32.32, 64.64);

SELECT key, byteSize(u8) AS `byteSize(UInt8)`, byteSize(u16) AS `byteSize(UInt16)`, byteSize(u32) AS `byteSize(UInt32)`, byteSize(u64) AS `byteSize(UInt64)`, byteSize(i8) AS `byteSize(Int8)`, byteSize(i16) AS `byteSize(Int16)`, byteSize(i32) AS `byteSize(Int32)`, byteSize(i64) AS `byteSize(Int64)`, byteSize(f32) AS `byteSize(Float32)`, byteSize(f64) AS `byteSize(Float64)` FROM test ORDER BY key ASC FORMAT Vertical;

Result:

Row 1:
──────
key: 1
byteSize(UInt8): 1
byteSize(UInt16): 2
byteSize(UInt32): 4
byteSize(UInt64): 8
byteSize(Int8): 1
byteSize(Int16): 2
byteSize(Int32): 4
byteSize(Int64): 8
byteSize(Float32): 4
byteSize(Float64): 8

If the function has multiple arguments, the function accumulates their byte sizes.

Query:

SELECT byteSize(NULL, 1, 0.3, '');

Result:

┌─byteSize(NULL, 1, 0.3, '')─┐
│ 19 │
└────────────────────────────┘

materialize(x)

Turns a constant into a full column containing a single value. Full columns and constants are represented differently in memory. Functions usually execute different code for normal and constant arguments, although the result should typically be the same. This function can be used to debug this behavior.

ignore(…)

Accepts any arguments, including NULL and does nothing. Always returns 0. The argument is internally still evaluated. Useful e.g. for benchmarks.

sleep(seconds)

Sleeps ‘seconds’ seconds for each data block. The sleep time can be specified as integer or as floating-point number.

sleepEachRow(seconds)

Sleeps ‘seconds’ seconds for each row. The sleep time can be specified as integer or as floating-point number.

currentDatabase()

Returns the name of the current database. Useful in table engine parameters of CREATE TABLE queries where you need to specify the database.

currentUser()

Returns the name of the current user. In case of a distributed query, the name of the user who initiated the query is returned.

SELECT currentUser();

Alias: user(), USER().

Returned values

  • The name of the current user.
  • In distributed queries, the login of the user who initiated the query.

Type: String.

Example

SELECT currentUser();

Result:

┌─currentUser()─┐
│ default │
└───────────────┘

isConstant

Returns whether the argument is a constant expression.

A constant expression is an expression whose result is known during query analysis, i.e. before execution. For example, expressions over literals are constant expressions.

This function is mostly intended for development, debugging and demonstration.

Syntax

isConstant(x)

Arguments

  • x — Expression to check.

Returned values

  • 1 if x is constant.
  • 0 if x is non-constant.

Type: UInt8.

Examples

Query:

SELECT isConstant(x + 1) FROM (SELECT 43 AS x)

Result:

┌─isConstant(plus(x, 1))─┐
│ 1 │
└────────────────────────┘

Query:

WITH 3.14 AS pi SELECT isConstant(cos(pi))

Result:

┌─isConstant(cos(pi))─┐
│ 1 │
└─────────────────────┘

Query:

SELECT isConstant(number) FROM numbers(1)

Result:

┌─isConstant(number)─┐
│ 0 │
└────────────────────┘

isFinite(x)

Returns 1 if the Float32 or Float64 argument not infinite and not a NaN, otherwise this function returns 0.

isInfinite(x)

Returns 1 if the Float32 or Float64 argument is infinite, otherwise this function returns 0. Note that 0 is returned for a NaN.

ifNotFinite

Checks whether a floating point value is finite.

Syntax

ifNotFinite(x,y)

Arguments

  • x — Value to check for infinity. Type: Float*.
  • y — Fallback value. Type: Float*.

Returned value

  • x if x is finite.
  • y if x is not finite.

Example

Query:

SELECT 1/0 as infimum, ifNotFinite(infimum,42)

Result:

┌─infimum─┬─ifNotFinite(divide(1, 0), 42)─┐
│ inf │ 42 │
└─────────┴───────────────────────────────┘

You can get similar result by using the ternary operator: isFinite(x) ? x : y.

isNaN(x)

Returns 1 if the Float32 and Float64 argument is NaN, otherwise this function 0.

hasColumnInTable([‘hostname’[, ‘username’[, ‘password’]],] ‘database’, ‘table’, ‘column’)

Given the database name, the table name, and the column name as constant strings, returns 1 if the given column exists, otherwise 0. If parameter hostname is given, the check is performed on a remote server. If the table does not exist, an exception is thrown. For elements in a nested data structure, the function checks for the existence of a column. For the nested data structure itself, the function returns 0.

bar

Builds a bar chart.

bar(x, min, max, width) draws a band with width proportional to (x - min) and equal to width characters when x = max.

Arguments

  • x — Size to display.
  • min, max — Integer constants. The value must fit in Int64.
  • width — Constant, positive integer, can be fractional.

The band is drawn with accuracy to one eighth of a symbol.

Example:

SELECT
toHour(EventTime) AS h,
count() AS c,
bar(c, 0, 600000, 20) AS bar
FROM test.hits
GROUP BY h
ORDER BY h ASC
┌──h─┬──────c─┬─bar────────────────┐
│ 0 │ 292907 │ █████████▋ │
│ 1 │ 180563 │ ██████ │
│ 2 │ 114861 │ ███▋ │
│ 3 │ 85069 │ ██▋ │
│ 4 │ 68543 │ ██▎ │
│ 5 │ 78116 │ ██▌ │
│ 6 │ 113474 │ ███▋ │
│ 7 │ 170678 │ █████▋ │
│ 8 │ 278380 │ █████████▎ │
│ 9 │ 391053 │ █████████████ │
│ 10 │ 457681 │ ███████████████▎ │
│ 11 │ 493667 │ ████████████████▍ │
│ 12 │ 509641 │ ████████████████▊ │
│ 13 │ 522947 │ █████████████████▍ │
│ 14 │ 539954 │ █████████████████▊ │
│ 15 │ 528460 │ █████████████████▌ │
│ 16 │ 539201 │ █████████████████▊ │
│ 17 │ 523539 │ █████████████████▍ │
│ 18 │ 506467 │ ████████████████▊ │
│ 19 │ 520915 │ █████████████████▎ │
│ 20 │ 521665 │ █████████████████▍ │
│ 21 │ 542078 │ ██████████████████ │
│ 22 │ 493642 │ ████████████████▍ │
│ 23 │ 400397 │ █████████████▎ │
└────┴────────┴────────────────────┘

transform

Transforms a value according to the explicitly defined mapping of some elements to other ones. There are two variations of this function:

transform(x, array_from, array_to, default)

x – What to transform.

array_from – Constant array of values to convert.

array_to – Constant array of values to convert the values in ‘from’ to.

default – Which value to use if ‘x’ is not equal to any of the values in ‘from’.

array_from and array_to must have equally many elements.

Signature:

For x equal to one of the elements in array_from, the function returns the corresponding element in array_to, i.e. the one at the same array index. Otherwise, it returns default. If multiple matching elements exist array_from, an arbitrary corresponding element from array_to is returned.

transform(T, Array(T), Array(U), U) -> U

T and U can be numeric, string, or Date or DateTime types. The same letter (T or U) means that types must be mutually compatible and not necessarily equal. For example, the first argument could have type Int64, while the second argument could have type Array(UInt16).

Example:

SELECT
transform(SearchEngineID, [2, 3], ['Yandex', 'Google'], 'Other') AS title,
count() AS c
FROM test.hits
WHERE SearchEngineID != 0
GROUP BY title
ORDER BY c DESC
┌─title─────┬──────c─┐
│ Yandex │ 498635 │
│ Google │ 229872 │
│ Other │ 104472 │
└───────────┴────────┘

transform(x, array_from, array_to)

Similar to the other variation but has no ‘default’ argument. In case no match can be found, x is returned.

Example:

SELECT
transform(domain(Referer), ['yandex.ru', 'google.ru', 'vkontakte.ru'], ['www.yandex', 'example.com', 'vk.com']) AS s,
count() AS c
FROM test.hits
GROUP BY domain(Referer)
ORDER BY count() DESC
LIMIT 10
┌─s──────────────┬───────c─┐
│ │ 2906259 │
│ www.yandex │ 867767 │
│ ███████.ru │ 313599 │
│ mail.yandex.ru │ 107147 │
│ ██████.ru │ 100355 │
│ █████████.ru │ 65040 │
│ news.yandex.ru │ 64515 │
│ ██████.net │ 59141 │
│ example.com │ 57316 │
└────────────────┴─────────┘

formatReadableDecimalSize(x)

Given a size (number of bytes), this function returns a readable, rounded size with suffix (KB, MB, etc.) as string.

Example:

SELECT
arrayJoin([1, 1024, 1024*1024, 192851925]) AS filesize_bytes,
formatReadableDecimalSize(filesize_bytes) AS filesize
┌─filesize_bytes─┬─filesize───┐
│ 1 │ 1.00 B │
│ 1024 │ 1.02 KB │
│ 1048576 │ 1.05 MB │
│ 192851925 │ 192.85 MB │
└────────────────┴────────────┘

formatReadableSize(x)

Given a size (number of bytes), this function returns a readable, rounded size with suffix (KiB, MiB, etc.) as string.

Example:

SELECT
arrayJoin([1, 1024, 1024*1024, 192851925]) AS filesize_bytes,
formatReadableSize(filesize_bytes) AS filesize

Alias: FORMAT_BYTES.

┌─filesize_bytes─┬─filesize───┐
│ 1 │ 1.00 B │
│ 1024 │ 1.00 KiB │
│ 1048576 │ 1.00 MiB │
│ 192851925 │ 183.92 MiB │
└────────────────┴────────────┘

formatReadableQuantity(x)

Given a number, this function returns a rounded number with suffix (thousand, million, billion, etc.) as string.

Example:

SELECT
arrayJoin([1024, 1234 * 1000, (4567 * 1000) * 1000, 98765432101234]) AS number,
formatReadableQuantity(number) AS number_for_humans
┌─────────number─┬─number_for_humans─┐
│ 1024 │ 1.02 thousand │
│ 1234000 │ 1.23 million │
│ 4567000000 │ 4.57 billion │
│ 98765432101234 │ 98.77 trillion │
└────────────────┴───────────────────┘

formatReadableTimeDelta

Given a time interval (delta) in seconds, this function returns a time delta with year/month/day/hour/minute/second/millisecond/microsecond/nanosecond as string.

Syntax

formatReadableTimeDelta(column[, maximum_unit, minimum_unit])

Arguments

  • column — A column with a numeric time delta.
  • maximum_unit — Optional. Maximum unit to show.
    • Acceptable values: nanoseconds, microseconds, milliseconds, seconds, minutes, hours, days, months, years.
    • Default value: years.
  • minimum_unit — Optional. Minimum unit to show. All smaller units are truncated.
    • Acceptable values: nanoseconds, microseconds, milliseconds, seconds, minutes, hours, days, months, years.
    • If explicitly specified value is bigger than maximum_unit, an exception will be thrown.
    • Default value: seconds if maximum_unit is seconds or bigger, nanoseconds otherwise.

Example

SELECT
arrayJoin([100, 12345, 432546534]) AS elapsed,
formatReadableTimeDelta(elapsed) AS time_delta
┌────elapsed─┬─time_delta ─────────────────────────────────────────────────────┐
│ 100 │ 1 minute and 40 seconds │
│ 12345 │ 3 hours, 25 minutes and 45 seconds │
│ 432546534 │ 13 years, 8 months, 17 days, 7 hours, 48 minutes and 54 seconds │
└────────────┴─────────────────────────────────────────────────────────────────┘
SELECT
arrayJoin([100, 12345, 432546534]) AS elapsed,
formatReadableTimeDelta(elapsed, 'minutes') AS time_delta
┌────elapsed─┬─time_delta ─────────────────────────────────────────────────────┐
│ 100 │ 1 minute and 40 seconds │
│ 12345 │ 205 minutes and 45 seconds │
│ 432546534 │ 7209108 minutes and 54 seconds │
└────────────┴─────────────────────────────────────────────────────────────────┘
SELECT
arrayJoin([100, 12345, 432546534.00000006]) AS elapsed,
formatReadableTimeDelta(elapsed, 'minutes', 'nanoseconds') AS time_delta
┌────────────elapsed─┬─time_delta─────────────────────────────────────┐
│ 100 │ 1 minute and 40 seconds │
│ 12345 │ 205 minutes and 45 seconds │
│ 432546534.00000006 │ 7209108 minutes, 54 seconds and 60 nanoseconds │
└────────────────────┴────────────────────────────────────────────────┘

parseTimeDelta

Parse a sequence of numbers followed by something resembling a time unit.

Syntax

parseTimeDelta(timestr)

Arguments

  • timestr — A sequence of numbers followed by something resembling a time unit.

Returned value

  • A floating-point number with the number of seconds.

Example

SELECT parseTimeDelta('11s+22min')
┌─parseTimeDelta('11s+22min')─┐
│ 1331 │
└─────────────────────────────┘
SELECT parseTimeDelta('1yr2mo')
┌─parseTimeDelta('1yr2mo')─┐
│ 36806400 │
└──────────────────────────┘

least(a, b)

Returns the smaller value of a and b.

greatest(a, b)

Returns the larger value of a and b.

uptime()

Returns the server’s uptime in seconds. If executed in the context of a distributed table, this function generates a normal column with values relevant to each shard. Otherwise it produces a constant value.

version()

Returns the server version as a string. If executed in the context of a distributed table, this function generates a normal column with values relevant to each shard. Otherwise it produces a constant value.

buildId()

Returns the build ID generated by a compiler for the running ClickHouse server binary. If executed in the context of a distributed table, this function generates a normal column with values relevant to each shard. Otherwise it produces a constant value.

blockNumber()

Returns the sequence number of the data block where the row is located.

rowNumberInBlock()

Returns the ordinal number of the row in the data block. Different data blocks are always recalculated.

rowNumberInAllBlocks()

Returns the ordinal number of the row in the data block. This function only considers the affected data blocks.

neighbor

The window function that provides access to a row at a specified offset before or after the current row of a given column.

Syntax

neighbor(column, offset[, default_value])

The result of the function depends on the affected data blocks and the order of data in the block.

note

Only returns neighbor inside the currently processed data block.

The order of rows during calculation of neighbor() can differ from the order of rows returned to the user. To prevent that you can create a subquery with ORDER BY and call the function from outside the subquery.

Arguments

  • column — A column name or scalar expression.
  • offset — The number of rows to look before or ahead of the current row in column. Int64.
  • default_value — Optional. The returned value if offset is beyond the block boundaries. Type of data blocks affected.

Returned values

  • Value of column with offset distance from current row, if offset is not outside the block boundaries.
  • The default value of column or default_value (if given), if offset is outside the block boundaries.

Type: type of data blocks affected or default value type.

Example

Query:

SELECT number, neighbor(number, 2) FROM system.numbers LIMIT 10;

Result:

┌─number─┬─neighbor(number, 2)─┐
│ 0 │ 2 │
│ 1 │ 3 │
│ 2 │ 4 │
│ 3 │ 5 │
│ 4 │ 6 │
│ 5 │ 7 │
│ 6 │ 8 │
│ 7 │ 9 │
│ 8 │ 0 │
│ 9 │ 0 │
└────────┴─────────────────────┘

Query:

SELECT number, neighbor(number, 2, 999) FROM system.numbers LIMIT 10;

Result:

┌─number─┬─neighbor(number, 2, 999)─┐
│ 0 │ 2 │
│ 1 │ 3 │
│ 2 │ 4 │
│ 3 │ 5 │
│ 4 │ 6 │
│ 5 │ 7 │
│ 6 │ 8 │
│ 7 │ 9 │
│ 8 │ 999 │
│ 9 │ 999 │
└────────┴──────────────────────────┘

This function can be used to compute year-over-year metric value:

Query:

WITH toDate('2018-01-01') AS start_date
SELECT
toStartOfMonth(start_date + (number * 32)) AS month,
toInt32(month) % 100 AS money,
neighbor(money, -12) AS prev_year,
round(prev_year / money, 2) AS year_over_year
FROM numbers(16)

Result:

┌──────month─┬─money─┬─prev_year─┬─year_over_year─┐
│ 2018-01-01 │ 32 │ 0 │ 0 │
│ 2018-02-01 │ 63 │ 0 │ 0 │
│ 2018-03-01 │ 91 │ 0 │ 0 │
│ 2018-04-01 │ 22 │ 0 │ 0 │
│ 2018-05-01 │ 52 │ 0 │ 0 │
│ 2018-06-01 │ 83 │ 0 │ 0 │
│ 2018-07-01 │ 13 │ 0 │ 0 │
│ 2018-08-01 │ 44 │ 0 │ 0 │
│ 2018-09-01 │ 75 │ 0 │ 0 │
│ 2018-10-01 │ 5 │ 0 │ 0 │
│ 2018-11-01 │ 36 │ 0 │ 0 │
│ 2018-12-01 │ 66 │ 0 │ 0 │
│ 2019-01-01 │ 97 │ 32 │ 0.33 │
│ 2019-02-01 │ 28 │ 63 │ 2.25 │
│ 2019-03-01 │ 56 │ 91 │ 1.62 │
│ 2019-04-01 │ 87 │ 22 │ 0.25 │
└────────────┴───────┴───────────┴────────────────┘

runningDifference(x)

Calculates the difference between two consecutive row values in the data block. Returns 0 for the first row, and for subsequent rows the difference to the previous row.

note

Only returns differences inside the currently processed data block.

The result of the function depends on the affected data blocks and the order of data in the block.

The order of rows during calculation of runningDifference() can differ from the order of rows returned to the user. To prevent that you can create a subquery with ORDER BY and call the function from outside the subquery.

Example:

SELECT
EventID,
EventTime,
runningDifference(EventTime) AS delta
FROM
(
SELECT
EventID,
EventTime
FROM events
WHERE EventDate = '2016-11-24'
ORDER BY EventTime ASC
LIMIT 5
)
┌─EventID─┬───────────EventTime─┬─delta─┐
│ 1106 │ 2016-11-24 00:00:04 │ 0 │
│ 1107 │ 2016-11-24 00:00:05 │ 1 │
│ 1108 │ 2016-11-24 00:00:05 │ 0 │
│ 1109 │ 2016-11-24 00:00:09 │ 4 │
│ 1110 │ 2016-11-24 00:00:10 │ 1 │
└─────────┴─────────────────────┴───────┘

Please note that the block size affects the result. The internal state of runningDifference state is reset for each new block.

SELECT
number,
runningDifference(number + 1) AS diff
FROM numbers(100000)
WHERE diff != 1
┌─number─┬─diff─┐
│ 0 │ 0 │
└────────┴──────┘
┌─number─┬─diff─┐
│ 65536 │ 0 │
└────────┴──────┘
set max_block_size=100000 -- default value is 65536!

SELECT
number,
runningDifference(number + 1) AS diff
FROM numbers(100000)
WHERE diff != 1
┌─number─┬─diff─┐
│ 0 │ 0 │
└────────┴──────┘

runningDifferenceStartingWithFirstValue

Same as runningDifference, but returns the value of the first row as the value on the first row.

runningConcurrency

Calculates the number of concurrent events. Each event has a start time and an end time. The start time is included in the event, while the end time is excluded. Columns with a start time and an end time must be of the same data type. The function calculates the total number of active (concurrent) events for each event start time.

tip

Events must be ordered by the start time in ascending order. If this requirement is violated the function raises an exception. Every data block is processed separately. If events from different data blocks overlap then they can not be processed correctly.

Syntax

runningConcurrency(start, end)

Arguments

Returned values

  • The number of concurrent events at each event start time.

Type: UInt32

Example

Consider the table:

┌──────start─┬────────end─┐
│ 2021-03-03 │ 2021-03-11 │
│ 2021-03-06 │ 2021-03-12 │
│ 2021-03-07 │ 2021-03-08 │
│ 2021-03-11 │ 2021-03-12 │
└────────────┴────────────┘

Query:

SELECT start, runningConcurrency(start, end) FROM example_table;

Result:

┌──────start─┬─runningConcurrency(start, end)─┐
│ 2021-03-03 │ 1 │
│ 2021-03-06 │ 2 │
│ 2021-03-07 │ 3 │
│ 2021-03-11 │ 2 │
└────────────┴────────────────────────────────┘

MACNumToString(num)

Interprets a UInt64 number as a MAC address in big endian format. Returns the corresponding MAC address in format AA:BB:CC:DD:EE:FF (colon-separated numbers in hexadecimal form) as string.

MACStringToNum(s)

The inverse function of MACNumToString. If the MAC address has an invalid format, it returns 0.

MACStringToOUI(s)

Given a MAC address in format AA:BB:CC:DD:EE:FF (colon-separated numbers in hexadecimal form), returns the first three octets as a UInt64 number. If the MAC address has an invalid format, it returns 0.

getSizeOfEnumType

Returns the number of fields in Enum. An exception is thrown if the type is not Enum.

getSizeOfEnumType(value)

Arguments:

  • value — Value of type Enum.

Returned values

  • The number of fields with Enum input values.

Example

SELECT getSizeOfEnumType( CAST('a' AS Enum8('a' = 1, 'b' = 2) ) ) AS x
┌─x─┐
│ 2 │
└───┘

blockSerializedSize

Returns the size on disk without considering compression.

blockSerializedSize(value[, value[, ...]])

Arguments

  • value — Any value.

Returned values

  • The number of bytes that will be written to disk for block of values without compression.

Example

Query:

SELECT blockSerializedSize(maxState(1)) as x

Result:

┌─x─┐
│ 2 │
└───┘

toColumnTypeName

Returns the internal name of the data type that represents the value.

toColumnTypeName(value)

Arguments:

  • value — Any type of value.

Returned values

  • The internal data type name used to represent value.

Example

Difference between toTypeName ' and ' toColumnTypeName:

SELECT toTypeName(CAST('2018-01-01 01:02:03' AS DateTime))

Result:

┌─toTypeName(CAST('2018-01-01 01:02:03', 'DateTime'))─┐
│ DateTime │
└─────────────────────────────────────────────────────┘

Query:

SELECT toColumnTypeName(CAST('2018-01-01 01:02:03' AS DateTime))

Result:

┌─toColumnTypeName(CAST('2018-01-01 01:02:03', 'DateTime'))─┐
│ Const(UInt32) │
└───────────────────────────────────────────────────────────┘

The example shows that the DateTime data type is internally stored as Const(UInt32).

dumpColumnStructure

Outputs a detailed description of data structures in RAM

dumpColumnStructure(value)

Arguments:

  • value — Any type of value.

Returned values

  • A description of the column structure used for representing value.

Example

SELECT dumpColumnStructure(CAST('2018-01-01 01:02:03', 'DateTime'))
┌─dumpColumnStructure(CAST('2018-01-01 01:02:03', 'DateTime'))─┐
│ DateTime, Const(size = 1, UInt32(size = 1)) │
└──────────────────────────────────────────────────────────────┘

defaultValueOfArgumentType

Returns the default value for the given data type.

Does not include default values for custom columns set by the user.

defaultValueOfArgumentType(expression)

Arguments:

  • expression — Arbitrary type of value or an expression that results in a value of an arbitrary type.

Returned values

  • 0 for numbers.
  • Empty string for strings.
  • ᴺᵁᴸᴸ for Nullable.

Example

Query:

SELECT defaultValueOfArgumentType( CAST(1 AS Int8) )

Result:

┌─defaultValueOfArgumentType(CAST(1, 'Int8'))─┐
│ 0 │
└─────────────────────────────────────────────┘

Query:

SELECT defaultValueOfArgumentType( CAST(1 AS Nullable(Int8) ) )

Result:

┌─defaultValueOfArgumentType(CAST(1, 'Nullable(Int8)'))─┐
│ ᴺᵁᴸᴸ │
└───────────────────────────────────────────────────────┘

defaultValueOfTypeName

Returns the default value for the given type name.

Does not include default values for custom columns set by the user.

defaultValueOfTypeName(type)

Arguments:

  • type — A string representing a type name.

Returned values

  • 0 for numbers.
  • Empty string for strings.
  • ᴺᵁᴸᴸ for Nullable.

Example

Query:

SELECT defaultValueOfTypeName('Int8')

Result:

┌─defaultValueOfTypeName('Int8')─┐
│ 0 │
└────────────────────────────────┘

Query:

SELECT defaultValueOfTypeName('Nullable(Int8)')

Result:

┌─defaultValueOfTypeName('Nullable(Int8)')─┐
│ ᴺᵁᴸᴸ │
└──────────────────────────────────────────┘

indexHint

This function is intended for debugging and introspection. It ignores its argument and always returns 1. The arguments are not evaluated.

But during index analysis, the argument of this function is assumed to be not wrapped in indexHint. This allows to select data in index ranges by the corresponding condition but without further filtering by this condition. The index in ClickHouse is sparse and using indexHint will yield more data than specifying the same condition directly.

Syntax

SELECT * FROM table WHERE indexHint(<expression>)

Returned value

Type: Uint8.

Example

Here is the example of test data from the table ontime.

Table:

SELECT count() FROM ontime
┌─count()─┐
│ 4276457 │
└─────────┘

The table has indexes on the fields (FlightDate, (Year, FlightDate)).

Create a query which does not use the index:

SELECT FlightDate AS k, count() FROM ontime GROUP BY k ORDER BY k

ClickHouse processed the entire table (Processed 4.28 million rows).

Result:

┌──────────k─┬─count()─┐
│ 2017-01-01 │ 13970 │
│ 2017-01-02 │ 15882 │
........................
│ 2017-09-28 │ 16411 │
│ 2017-09-29 │ 16384 │
│ 2017-09-30 │ 12520 │
└────────────┴─────────┘

To apply the index, select a specific date:

SELECT FlightDate AS k, count() FROM ontime WHERE k = '2017-09-15' GROUP BY k ORDER BY k

ClickHouse now uses the index to process a significantly smaller number of rows (Processed 32.74 thousand rows).

Result:

┌──────────k─┬─count()─┐
│ 2017-09-15 │ 16428 │
└────────────┴─────────┘

Now wrap the expression k = '2017-09-15' in function indexHint:

Query:

SELECT
FlightDate AS k,
count()
FROM ontime
WHERE indexHint(k = '2017-09-15')
GROUP BY k
ORDER BY k ASC

ClickHouse used the index the same way as previously (Processed 32.74 thousand rows). The expression k = '2017-09-15' was not used when generating the result. In example, the indexHint function allows to see adjacent dates.

Result:

┌──────────k─┬─count()─┐
│ 2017-09-14 │ 7071 │
│ 2017-09-15 │ 16428 │
│ 2017-09-16 │ 1077 │
│ 2017-09-30 │ 8167 │
└────────────┴─────────┘

replicate

Creates an array with a single value.

Used for the internal implementation of arrayJoin.

SELECT replicate(x, arr);

Arguments:

  • arr — An array.
  • x — The value to fill the result array with.

Returned value

An array of the lame length as arr filled with value x.

Type: Array.

Example

Query:

SELECT replicate(1, ['a', 'b', 'c'])

Result:

┌─replicate(1, ['a', 'b', 'c'])─┐
│ [1,1,1] │
└───────────────────────────────┘

filesystemAvailable

Returns the amount of free space in the filesystem hosting the database persistence. The returned value is always smaller than total free space (filesystemFree) because some space is reserved for the operating system.

Syntax

filesystemAvailable()

Returned value

  • The amount of remaining space available in bytes.

Type: UInt64.

Example

Query:

SELECT formatReadableSize(filesystemAvailable()) AS "Available space";

Result:

┌─Available space─┐
│ 30.75 GiB │
└─────────────────┘

filesystemFree

Returns the total amount of the free space on the filesystem hosting the database persistence. See also filesystemAvailable

Syntax

filesystemFree()

Returned value

  • The amount of free space in bytes.

Type: UInt64.

Example

Query:

SELECT formatReadableSize(filesystemFree()) AS "Free space";

Result:

┌─Free space─┐
│ 32.39 GiB │
└────────────┘

filesystemCapacity

Returns the capacity of the filesystem in bytes. Needs the path to the data directory to be configured.

Syntax

filesystemCapacity()

Returned value

  • Capacity of the filesystem in bytes.

Type: UInt64.

Example

Query:

SELECT formatReadableSize(filesystemCapacity()) AS "Capacity";

Result:

┌─Capacity──┐
│ 39.32 GiB │
└───────────┘

initializeAggregation

Calculates the result of an aggregate function based on a single value. This function can be used to initialize aggregate functions with combinator -State. You can create states of aggregate functions and insert them to columns of type AggregateFunction or use initialized aggregates as default values.

Syntax

initializeAggregation (aggregate_function, arg1, arg2, ..., argN)

Arguments

  • aggregate_function — Name of the aggregation function to initialize. String.
  • arg — Arguments of aggregate function.

Returned value(s)

  • Result of aggregation for every row passed to the function.

The return type is the same as the return type of function, that initializeAggregation takes as first argument.

Example

Query:

SELECT uniqMerge(state) FROM (SELECT initializeAggregation('uniqState', number % 3) AS state FROM numbers(10000));

Result:

┌─uniqMerge(state)─┐
│ 3 │
└──────────────────┘

Query:

SELECT finalizeAggregation(state), toTypeName(state) FROM (SELECT initializeAggregation('sumState', number % 3) AS state FROM numbers(5));

Result:

┌─finalizeAggregation(state)─┬─toTypeName(state)─────────────┐
│ 0 │ AggregateFunction(sum, UInt8) │
│ 1 │ AggregateFunction(sum, UInt8) │
│ 2 │ AggregateFunction(sum, UInt8) │
│ 0 │ AggregateFunction(sum, UInt8) │
│ 1 │ AggregateFunction(sum, UInt8) │
└────────────────────────────┴───────────────────────────────┘

Example with AggregatingMergeTree table engine and AggregateFunction column:

CREATE TABLE metrics
(
key UInt64,
value AggregateFunction(sum, UInt64) DEFAULT initializeAggregation('sumState', toUInt64(0))
)
ENGINE = AggregatingMergeTree
ORDER BY key
INSERT INTO metrics VALUES (0, initializeAggregation('sumState', toUInt64(42)))

See Also

finalizeAggregation

Given a state of aggregate function, this function returns the result of aggregation (or finalized state when using a -State combinator).

Syntax

finalizeAggregation(state)

Arguments

Returned value(s)

  • Value/values that was aggregated.

Type: Value of any types that was aggregated.

Examples

Query:

SELECT finalizeAggregation(( SELECT countState(number) FROM numbers(10)));

Result:

┌─finalizeAggregation(_subquery16)─┐
│ 10 │
└──────────────────────────────────┘

Query:

SELECT finalizeAggregation(( SELECT sumState(number) FROM numbers(10)));

Result:

┌─finalizeAggregation(_subquery20)─┐
│ 45 │
└──────────────────────────────────┘

Note that NULL values are ignored.

Query:

SELECT finalizeAggregation(arrayReduce('anyState', [NULL, 2, 3]));

Result:

┌─finalizeAggregation(arrayReduce('anyState', [NULL, 2, 3]))─┐
│ 2 │
└────────────────────────────────────────────────────────────┘

Combined example:

Query:

WITH initializeAggregation('sumState', number) AS one_row_sum_state
SELECT
number,
finalizeAggregation(one_row_sum_state) AS one_row_sum,
runningAccumulate(one_row_sum_state) AS cumulative_sum
FROM numbers(10);

Result:

┌─number─┬─one_row_sum─┬─cumulative_sum─┐
│ 0 │ 0 │ 0 │
│ 1 │ 1 │ 1 │
│ 2 │ 2 │ 3 │
│ 3 │ 3 │ 6 │
│ 4 │ 4 │ 10 │
│ 5 │ 5 │ 15 │
│ 6 │ 6 │ 21 │
│ 7 │ 7 │ 28 │
│ 8 │ 8 │ 36 │
│ 9 │ 9 │ 45 │
└────────┴─────────────┴────────────────┘

See Also

runningAccumulate

Accumulates the states of an aggregate function for each row of a data block.

note

The state is reset for each new block of data.

Syntax

runningAccumulate(agg_state[, grouping]);

Arguments

  • agg_state — State of the aggregate function. AggregateFunction.
  • grouping — Grouping key. Optional. The state of the function is reset if the grouping value is changed. It can be any of the supported data types for which the equality operator is defined.

Returned value

  • Each resulting row contains a result of the aggregate function, accumulated for all the input rows from 0 to the current position. runningAccumulate resets states for each new data block or when the grouping value changes.

Type depends on the aggregate function used.

Examples

Consider how you can use runningAccumulate to find the cumulative sum of numbers without and with grouping.

Query:

SELECT k, runningAccumulate(sum_k) AS res FROM (SELECT number as k, sumState(k) AS sum_k FROM numbers(10) GROUP BY k ORDER BY k);

Result:

┌─k─┬─res─┐
│ 0 │ 0 │
│ 1 │ 1 │
│ 2 │ 3 │
│ 3 │ 6 │
│ 4 │ 10 │
│ 5 │ 15 │
│ 6 │ 21 │
│ 7 │ 28 │
│ 8 │ 36 │
│ 9 │ 45 │
└───┴─────┘

The subquery generates sumState for every number from 0 to 9. sumState returns the state of the sum function that contains the sum of a single number.

The whole query does the following:

  1. For the first row, runningAccumulate takes sumState(0) and returns 0.
  2. For the second row, the function merges sumState(0) and sumState(1) resulting in sumState(0 + 1), and returns 1 as a result.
  3. For the third row, the function merges sumState(0 + 1) and sumState(2) resulting in sumState(0 + 1 + 2), and returns 3 as a result.
  4. The actions are repeated until the block ends.

The following example shows the groupping parameter usage:

Query:

SELECT
grouping,
item,
runningAccumulate(state, grouping) AS res
FROM
(
SELECT
toInt8(number / 4) AS grouping,
number AS item,
sumState(number) AS state
FROM numbers(15)
GROUP BY item
ORDER BY item ASC
);

Result:

┌─grouping─┬─item─┬─res─┐
│ 0 │ 0 │ 0 │
│ 0 │ 1 │ 1 │
│ 0 │ 2 │ 3 │
│ 0 │ 3 │ 6 │
│ 1 │ 4 │ 4 │
│ 1 │ 5 │ 9 │
│ 1 │ 6 │ 15 │
│ 1 │ 7 │ 22 │
│ 2 │ 8 │ 8 │
│ 2 │ 9 │ 17 │
│ 2 │ 10 │ 27 │
│ 2 │ 11 │ 38 │
│ 3 │ 12 │ 12 │
│ 3 │ 13 │ 25 │
│ 3 │ 14 │ 39 │
└──────────┴──────┴─────┘

As you can see, runningAccumulate merges states for each group of rows separately.

joinGet

The function lets you extract data from the table the same way as from a dictionary.

Gets the data from Join tables using the specified join key.

Only supports tables created with the ENGINE = Join(ANY, LEFT, <join_keys>) statement.

Syntax

joinGet(join_storage_table_name, `value_column`, join_keys)

Arguments

  • join_storage_table_name — an identifier indicating where the search is performed. The identifier is searched in the default database (see setting default_database in the config file). To override the default database, use USE db_name or specify the database and the table through the separator db_name.db_table as in the example.
  • value_column — name of the column of the table that contains required data.
  • join_keys — list of keys.

Returned value

Returns a list of values corresponded to list of keys.

If certain does not exist in source table then 0 or null will be returned based on join_use_nulls setting.

More info about join_use_nulls in Join operation.

Example

Input table:

CREATE DATABASE db_test
CREATE TABLE db_test.id_val(`id` UInt32, `val` UInt32) ENGINE = Join(ANY, LEFT, id) SETTINGS join_use_nulls = 1
INSERT INTO db_test.id_val VALUES (1,11)(2,12)(4,13)
┌─id─┬─val─┐
│ 4 │ 13 │
│ 2 │ 12 │
│ 1 │ 11 │
└────┴─────┘

Query:

SELECT joinGet(db_test.id_val, 'val', toUInt32(number)) from numbers(4) SETTINGS join_use_nulls = 1

Result:

┌─joinGet(db_test.id_val, 'val', toUInt32(number))─┐
│ 0 │
│ 11 │
│ 12 │
│ 0 │
└──────────────────────────────────────────────────┘

catboostEvaluate(path_to_model, feature_1, feature_2, …, feature_n)

note

This function is not available in ClickHouse Cloud.

Evaluate an external catboost model. CatBoost is an open-source gradient boosting library developed by Yandex for machine learning. Accepts a path to a catboost model and model arguments (features). Returns Float64.

SELECT feat1, ..., feat_n, catboostEvaluate('/path/to/model.bin', feat_1, ..., feat_n) AS prediction
FROM data_table

Prerequisites

  1. Build the catboost evaluation library

Before evaluating catboost models, the libcatboostmodel.<so|dylib> library must be made available. See CatBoost documentation how to compile it.

Next, specify the path to libcatboostmodel.<so|dylib> in the clickhouse configuration:

<clickhouse>
...
<catboost_lib_path>/path/to/libcatboostmodel.so</catboost_lib_path>
...
</clickhouse>

For security and isolation reasons, the model evaluation does not run in the server process but in the clickhouse-library-bridge process. At the first execution of catboostEvaluate(), the server starts the library bridge process if it is not running already. Both processes communicate using a HTTP interface. By default, port 9012 is used. A different port can be specified as follows - this is useful if port 9012 is already assigned to a different service.

<library_bridge>
<port>9019</port>
</library_bridge>
  1. Train a catboost model using libcatboost

See Training and applying models for how to train catboost models from a training data set.

throwIf(x[, message[, error_code]])

Throw an exception if argument x is true.

Arguments

  • x - the condition to check.
  • message - a constant string providing a custom error message. Optional.
  • error_code - A constant integer providing a custom error code. Optional.

To use the error_code argument, configuration parameter allow_custom_error_code_in_throwif must be enabled.

Example

SELECT throwIf(number = 3, 'Too many') FROM numbers(10);

Result:

↙ Progress: 0.00 rows, 0.00 B (0.00 rows/s., 0.00 B/s.) Received exception from server (version 19.14.1):
Code: 395. DB::Exception: Received from localhost:9000. DB::Exception: Too many.

identity

Returns its argument. Intended for debugging and testing. Allows to cancel using index, and get the query performance of a full scan. When the query is analyzed for possible use of an index, the analyzer ignores everything in identity functions. Also disables constant folding.

Syntax

identity(x)

Example

Query:

SELECT identity(42);

Result:

┌─identity(42)─┐
│ 42 │
└──────────────┘

getSetting

Returns the current value of a custom setting.

Syntax

getSetting('custom_setting');

Parameter

  • custom_setting — The setting name. String.

Returned value

  • The setting's current value.

Example

SET custom_a = 123;
SELECT getSetting('custom_a');

Result:

123

See Also

isDecimalOverflow

Checks whether the Decimal value is outside its precision or outside the specified precision.

Syntax

isDecimalOverflow(d, [p])

Arguments

  • d — value. Decimal.
  • p — precision. Optional. If omitted, the initial precision of the first argument is used. This parameter can be helpful to migrate data from/to another database or file. UInt8.

Returned values

  • 1 — Decimal value has more digits then allowed by its precision,
  • 0 — Decimal value satisfies the specified precision.

Example

Query:

SELECT isDecimalOverflow(toDecimal32(1000000000, 0), 9),
isDecimalOverflow(toDecimal32(1000000000, 0)),
isDecimalOverflow(toDecimal32(-1000000000, 0), 9),
isDecimalOverflow(toDecimal32(-1000000000, 0));

Result:

1   1   1   1

countDigits

Returns number of decimal digits need to represent a value.

Syntax

countDigits(x)

Arguments

Returned value

Number of digits.

Type: UInt8.

note

For Decimal values takes into account their scales: calculates result over underlying integer type which is (value * scale). For example: countDigits(42) = 2, countDigits(42.000) = 5, countDigits(0.04200) = 4. I.e. you may check decimal overflow for Decimal64 with countDecimal(x) > 18. It's a slow variant of isDecimalOverflow.

Example

Query:

SELECT countDigits(toDecimal32(1, 9)), countDigits(toDecimal32(-1, 9)),
countDigits(toDecimal64(1, 18)), countDigits(toDecimal64(-1, 18)),
countDigits(toDecimal128(1, 38)), countDigits(toDecimal128(-1, 38));

Result:

10  10  19  19  39  39

errorCodeToName

Returns the textual name of an error code.

Type: LowCardinality(String).

Syntax

errorCodeToName(1)

Result:

UNSUPPORTED_METHOD

tcpPort

Returns native interface TCP port number listened by this server. If executed in the context of a distributed table, this function generates a normal column with values relevant to each shard. Otherwise it produces a constant value.

Syntax

tcpPort()

Arguments

  • None.

Returned value

  • The TCP port number.

Type: UInt16.

Example

Query:

SELECT tcpPort();

Result:

┌─tcpPort()─┐
│ 9000 │
└───────────┘

See Also

currentProfiles

Returns a list of the current settings profiles for the current user.

The command SET PROFILE could be used to change the current setting profile. If the command SET PROFILE was not used the function returns the profiles specified at the current user's definition (see CREATE USER).

Syntax

currentProfiles()

Returned value

  • List of the current user settings profiles.

Type: Array(String).

enabledProfiles

Returns settings profiles, assigned to the current user both explicitly and implicitly. Explicitly assigned profiles are the same as returned by the currentProfiles function. Implicitly assigned profiles include parent profiles of other assigned profiles, profiles assigned via granted roles, profiles assigned via their own settings, and the main default profile (see the default_profile section in the main server configuration file).

Syntax

enabledProfiles()

Returned value

  • List of the enabled settings profiles.

Type: Array(String).

defaultProfiles

Returns all the profiles specified at the current user's definition (see CREATE USER statement).

Syntax

defaultProfiles()

Returned value

  • List of the default settings profiles.

Type: Array(String).

currentRoles

Returns the roles assigned to the current user. The roles can be changed by the SET ROLE statement. If no SET ROLE statement was not, the function currentRoles returns the same as defaultRoles.

Syntax

currentRoles()

Returned value

  • A list of the current roles for the current user.

Type: Array(String).

enabledRoles

Returns the names of the current roles and the roles, granted to some of the current roles.

Syntax

enabledRoles()

Returned value

  • List of the enabled roles for the current user.

Type: Array(String).

defaultRoles

Returns the roles which are enabled by default for the current user when he logs in. Initially these are all roles granted to the current user (see GRANT), but that can be changed with the SET DEFAULT ROLE statement.

Syntax

defaultRoles()

Returned value

  • List of the default roles for the current user.

Type: Array(String).

getServerPort

Returns the server port number. When the port is not used by the server, throws an exception.

Syntax

getServerPort(port_name)

Arguments

  • port_name — The name of the server port. String. Possible values:

    • 'tcp_port'
    • 'tcp_port_secure'
    • 'http_port'
    • 'https_port'
    • 'interserver_http_port'
    • 'interserver_https_port'
    • 'mysql_port'
    • 'postgresql_port'
    • 'grpc_port'
    • 'prometheus.port'

Returned value

  • The number of the server port.

Type: UInt16.

Example

Query:

SELECT getServerPort('tcp_port');

Result:

┌─getServerPort('tcp_port')─┐
│ 9000 │
└───────────────────────────┘

queryID

Returns the ID of the current query. Other parameters of a query can be extracted from the system.query_log table via query_id.

In contrast to initialQueryID function, queryID can return different results on different shards (see the example).

Syntax

queryID()

Returned value

  • The ID of the current query.

Type: String

Example

Query:

CREATE TABLE tmp (str String) ENGINE = Log;
INSERT INTO tmp (*) VALUES ('a');
SELECT count(DISTINCT t) FROM (SELECT queryID() AS t FROM remote('127.0.0.{1..3}', currentDatabase(), 'tmp') GROUP BY queryID());

Result:

┌─count()─┐
│ 3 │
└─────────┘

initialQueryID

Returns the ID of the initial current query. Other parameters of a query can be extracted from the system.query_log table via initial_query_id.

In contrast to queryID function, initialQueryID returns the same results on different shards (see example).

Syntax

initialQueryID()

Returned value

  • The ID of the initial current query.

Type: String

Example

Query:

CREATE TABLE tmp (str String) ENGINE = Log;
INSERT INTO tmp (*) VALUES ('a');
SELECT count(DISTINCT t) FROM (SELECT initialQueryID() AS t FROM remote('127.0.0.{1..3}', currentDatabase(), 'tmp') GROUP BY queryID());

Result:

┌─count()─┐
│ 1 │
└─────────┘

shardNum

Returns the index of a shard which processes a part of data in a distributed query. Indices are started from 1. If a query is not distributed then constant value 0 is returned.

Syntax

shardNum()

Returned value

  • Shard index or constant 0.

Type: UInt32.

Example

In the following example a configuration with two shards is used. The query is executed on the system.one table on every shard.

Query:

CREATE TABLE shard_num_example (dummy UInt8)
ENGINE=Distributed(test_cluster_two_shards_localhost, system, one, dummy);
SELECT dummy, shardNum(), shardCount() FROM shard_num_example;

Result:

┌─dummy─┬─shardNum()─┬─shardCount()─┐
│ 0 │ 2 │ 2 │
│ 0 │ 1 │ 2 │
└───────┴────────────┴──────────────┘

See Also

shardCount

Returns the total number of shards for a distributed query. If a query is not distributed then constant value 0 is returned.

Syntax

shardCount()

Returned value

  • Total number of shards or 0.

Type: UInt32.

See Also

  • shardNum() function example also contains shardCount() function call.

getOSKernelVersion

Returns a string with the current OS kernel version.

Syntax

getOSKernelVersion()

Arguments

  • None.

Returned value

  • The current OS kernel version.

Type: String.

Example

Query:

SELECT getOSKernelVersion();

Result:

┌─getOSKernelVersion()────┐
│ Linux 4.15.0-55-generic │
└─────────────────────────┘

zookeeperSessionUptime

Returns the uptime of the current ZooKeeper session in seconds.

Syntax

zookeeperSessionUptime()

Arguments

  • None.

Returned value

  • Uptime of the current ZooKeeper session in seconds.

Type: UInt32.

Example

Query:

SELECT zookeeperSessionUptime();

Result:

┌─zookeeperSessionUptime()─┐
│ 286 │
└──────────────────────────┘

generateRandomStructure

Generates random table structure in a format column1_name column1_type, column2_name column2_type, ....

Syntax

generateRandomStructure([number_of_columns, seed])

Arguments

  • number_of_columns — The desired number of columns in the result table structure. If set to 0 or Null, the number of columns will be random from 1 to 128. Default value: Null.
  • seed - Random seed to produce stable results. If seed is not specified or set to Null, it is randomly generated.

All arguments must be constant.

Returned value

  • Randomly generated table structure.

Type: String.

Examples

Query:

SELECT generateRandomStructure()

Result:

┌─generateRandomStructure()─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ c1 Decimal32(5), c2 Date, c3 Tuple(LowCardinality(String), Int128, UInt64, UInt16, UInt8, IPv6), c4 Array(UInt128), c5 UInt32, c6 IPv4, c7 Decimal256(64), c8 Decimal128(3), c9 UInt256, c10 UInt64, c11 DateTime │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘

Query:

SELECT generateRandomStructure(1)

Result:

┌─generateRandomStructure(1)─┐
│ c1 Map(UInt256, UInt16) │
└────────────────────────────┘

Query:

SELECT generateRandomStructure(NULL, 33)

Result:

┌─generateRandomStructure(NULL, 33)─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ c1 DateTime, c2 Enum8('c2V0' = 0, 'c2V1' = 1, 'c2V2' = 2, 'c2V3' = 3), c3 LowCardinality(Nullable(FixedString(30))), c4 Int16, c5 Enum8('c5V0' = 0, 'c5V1' = 1, 'c5V2' = 2, 'c5V3' = 3), c6 Nullable(UInt8), c7 String, c8 Nested(e1 IPv4, e2 UInt8, e3 UInt16, e4 UInt16, e5 Int32, e6 Map(Date, Decimal256(70))) │
└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘

Note: the maximum nesting depth of complex types (Array, Tuple, Map, Nested) is limited to 16.

This function can be used together with generateRandom to generate completely random tables.

structureToCapnProtoSchema

Converts ClickHouse table structure to CapnProto schema.

Syntax

structureToCapnProtoSchema(structure)

Arguments

  • structure — Table structure in a format column1_name column1_type, column2_name column2_type, ....
  • root_struct_name — Name for root struct in CapnProto schema. Default value - Message;

Returned value

  • CapnProto schema

Type: String.

Examples

Query:

SELECT structureToCapnProtoSchema('column1 String, column2 UInt32, column3 Array(String)') FORMAT RawBLOB

Result:

@0xf96402dd754d0eb7;

struct Message
{
column1 @0 : Data;
column2 @1 : UInt32;
column3 @2 : List(Data);
}

Query:

SELECT structureToCapnProtoSchema('column1 Nullable(String), column2 Tuple(element1 UInt32, element2 Array(String)), column3 Map(String, String)') FORMAT RawBLOB

Result:

@0xd1c8320fecad2b7f;

struct Message
{
struct Column1
{
union
{
value @0 : Data;
null @1 : Void;
}
}
column1 @0 : Column1;
struct Column2
{
element1 @0 : UInt32;
element2 @1 : List(Data);
}
column2 @1 : Column2;
struct Column3
{
struct Entry
{
key @0 : Data;
value @1 : Data;
}
entries @0 : List(Entry);
}
column3 @2 : Column3;
}

Query:

SELECT structureToCapnProtoSchema('column1 String, column2 UInt32', 'Root') FORMAT RawBLOB

Result:

@0x96ab2d4ab133c6e1;

struct Root
{
column1 @0 : Data;
column2 @1 : UInt32;
}

structureToProtobufSchema

Converts ClickHouse table structure to Protobuf schema.

Syntax

structureToProtobufSchema(structure)

Arguments

  • structure — Table structure in a format column1_name column1_type, column2_name column2_type, ....
  • root_message_name — Name for root message in Protobuf schema. Default value - Message;

Returned value

  • Protobuf schema

Type: String.

Examples

Query:

SELECT structureToProtobufSchema('column1 String, column2 UInt32, column3 Array(String)') FORMAT RawBLOB

Result:

syntax = "proto3";

message Message
{
bytes column1 = 1;
uint32 column2 = 2;
repeated bytes column3 = 3;
}

Query:

SELECT structureToProtobufSchema('column1 Nullable(String), column2 Tuple(element1 UInt32, element2 Array(String)), column3 Map(String, String)') FORMAT RawBLOB

Result:

syntax = "proto3";

message Message
{
bytes column1 = 1;
message Column2
{
uint32 element1 = 1;
repeated bytes element2 = 2;
}
Column2 column2 = 2;
map<string, bytes> column3 = 3;
}

Query:

SELECT structureToProtobufSchema('column1 String, column2 UInt32', 'Root') FORMAT RawBLOB

Result:

syntax = "proto3";

message Root
{
bytes column1 = 1;
uint32 column2 = 2;
}

formatQuery

Returns a formatted, possibly multi-line, version of the given SQL query.

Throws an exception if the query is not well-formed. To return NULL instead, function formatQueryOrNull() may be used.

Syntax

formatQuery(query)
formatQueryOrNull(query)

Arguments

  • query - The SQL query to be formatted. String

Returned value

Example

SELECT formatQuery('select a,    b FRom tab WHERE a > 3 and  b < 3');

Result:

┌─formatQuery('select a,    b FRom tab WHERE a > 3 and  b < 3')─┐
│ SELECT
a,
b
FROM tab
WHERE (a > 3) AND (b < 3) │
└───────────────────────────────────────────────────────────────┘

formatQuerySingleLine

Like formatQuery() but the returned formatted string contains no line breaks.

Throws an exception if the query is not well-formed. To return NULL instead, function formatQuerySingleLineOrNull() may be used.

Syntax

formatQuerySingleLine(query)
formatQuerySingleLineOrNull(query)

Arguments

  • query - The SQL query to be formatted. String

Returned value

Example

SELECT formatQuerySingleLine('select a,    b FRom tab WHERE a > 3 and  b < 3');

Result:

┌─formatQuerySingleLine('select a,    b FRom tab WHERE a > 3 and  b < 3')─┐
│ SELECT a, b FROM tab WHERE (a > 3) AND (b < 3) │
└─────────────────────────────────────────────────────────────────────────┘

variantElement

Extracts a column with specified type from a Variant column.

Syntax

variantElement(variant, type_name, [, default_value])

Arguments

  • variant — Variant column. Variant.
  • type_name — The name of the variant type to extract. String.
  • default_value - The default value that will be used if variant doesn't have variant with specified type. Can be any type. Optional.

Returned value

  • Subcolumn of a Variant column with specified type.

Example

CREATE TABLE test (v Variant(UInt64, String, Array(UInt64))) ENGINE = Memory;
INSERT INTO test VALUES (NULL), (42), ('Hello, World!'), ([1, 2, 3]);
SELECT v, variantElement(v, 'String'), variantElement(v, 'UInt64'), variantElement(v, 'Array(UInt64)') FROM test;
┌─v─────────────┬─variantElement(v, 'String')─┬─variantElement(v, 'UInt64')─┬─variantElement(v, 'Array(UInt64)')─┐
│ ᴺᵁᴸᴸ │ ᴺᵁᴸᴸ │ ᴺᵁᴸᴸ │ [] │
│ 42 │ ᴺᵁᴸᴸ │ 42 │ [] │
│ Hello, World! │ Hello, World! │ ᴺᵁᴸᴸ │ [] │
│ [1,2,3] │ ᴺᵁᴸᴸ │ ᴺᵁᴸᴸ │ [1,2,3] │
└───────────────┴─────────────────────────────┴─────────────────────────────┴────────────────────────────────────┘

variantType

Returns the variant type name for each row of Variant column. If row contains NULL, it returns 'None' for it.

Syntax

variantType(variant)

Arguments

  • variant — Variant column. Variant.

Returned value

  • Enum8 column with variant type name for each row.

Example

CREATE TABLE test (v Variant(UInt64, String, Array(UInt64))) ENGINE = Memory;
INSERT INTO test VALUES (NULL), (42), ('Hello, World!'), ([1, 2, 3]);
SELECT variantType(v) FROM test;
┌─variantType(v)─┐
│ None │
│ UInt64 │
│ String │
│ Array(UInt64) │
└────────────────┘
SELECT toTypeName(variantType(v)) FROM test LIMIT 1;
┌─toTypeName(variantType(v))──────────────────────────────────────────┐
│ Enum8('None' = -1, 'Array(UInt64)' = 0, 'String' = 1, 'UInt64' = 2) │
└─────────────────────────────────────────────────────────────────────┘

minSampleSizeConversion

Calculates minimum required sample size for an A/B test comparing conversions (proportions) in two samples.

Syntax

minSampleSizeConversion(baseline, mde, power, alpha)

Uses the formula described in this article. Assumes equal sizes of treatment and control groups. Returns the sample size required for one group (i.e. the sample size required for the whole experiment is twice the returned value).

Arguments

  • baseline — Baseline conversion. Float.
  • mde — Minimum detectable effect (MDE) as percentage points (e.g. for a baseline conversion 0.25 the MDE 0.03 means an expected change to 0.25 ± 0.03). Float.
  • power — Required statistical power of a test (1 - probability of Type II error). Float.
  • alpha — Required significance level of a test (probability of Type I error). Float.

Returned value

A named Tuple with 3 elements:

  • "minimum_sample_size" — Required sample size. Float64.
  • "detect_range_lower" — Lower bound of the range of values not detectable with the returned required sample size (i.e. all values less than or equal to "detect_range_lower" are detectable with the provided alpha and power). Calculated as baseline - mde. Float64.
  • "detect_range_upper" — Upper bound of the range of values not detectable with the returned required sample size (i.e. all values greater than or equal to "detect_range_upper" are detectable with the provided alpha and power). Calculated as baseline + mde. Float64.

Example

The following query calculates the required sample size for an A/B test with baseline conversion of 25%, MDE of 3%, significance level of 5%, and the desired statistical power of 80%:

SELECT minSampleSizeConversion(0.25, 0.03, 0.80, 0.05) AS sample_size;

Result:

┌─sample_size───────────────────┐
│ (3396.077603219163,0.22,0.28) │
└───────────────────────────────┘

minSampleSizeContinuous

Calculates minimum required sample size for an A/B test comparing means of a continuous metric in two samples.

Syntax

minSampleSizeContinous(baseline, sigma, mde, power, alpha)

Alias: minSampleSizeContinous

Uses the formula described in this article. Assumes equal sizes of treatment and control groups. Returns the required sample size for one group (i.e. the sample size required for the whole experiment is twice the returned value). Also assumes equal variance of the test metric in treatment and control groups.

Arguments

  • baseline — Baseline value of a metric. Integer or Float.
  • sigma — Baseline standard deviation of a metric. Integer or Float.
  • mde — Minimum detectable effect (MDE) as percentage of the baseline value (e.g. for a baseline value 112.25 the MDE 0.03 means an expected change to 112.25 ± 112.25*0.03). Integer or Float.
  • power — Required statistical power of a test (1 - probability of Type II error). Integer or Float.
  • alpha — Required significance level of a test (probability of Type I error). Integer or Float.

Returned value

A named Tuple with 3 elements:

  • "minimum_sample_size" — Required sample size. Float64.
  • "detect_range_lower" — Lower bound of the range of values not detectable with the returned required sample size (i.e. all values less than or equal to "detect_range_lower" are detectable with the provided alpha and power). Calculated as baseline * (1 - mde). Float64.
  • "detect_range_upper" — Upper bound of the range of values not detectable with the returned required sample size (i.e. all values greater than or equal to "detect_range_upper" are detectable with the provided alpha and power). Calculated as baseline * (1 + mde). Float64.

Example

The following query calculates the required sample size for an A/B test on a metric with baseline value of 112.25, standard deviation of 21.1, MDE of 3%, significance level of 5%, and the desired statistical power of 80%:

SELECT minSampleSizeContinous(112.25, 21.1, 0.03, 0.80, 0.05) AS sample_size;

Result:

┌─sample_size───────────────────────────┐
│ (616.2931945826209,108.8825,115.6175) │
└───────────────────────────────────────┘