This page provides an overview of all GoogleSQL for BigQuery data types, including information about their value domains. For information on data type literals and constructors, see Lexical Structure and Syntax.
Data type list
Name | Summary |
---|---|
Array type |
An ordered list of zero or more elements of non-array values. SQL type name: ARRAY
|
Boolean type |
A value that can be either TRUE or FALSE .SQL type name: BOOL
|
Bytes type |
Variable-length binary data. SQL type name: BYTES
|
Date type |
A Gregorian calendar date, independent of time zone. SQL type name: DATE
|
Datetime type |
A Gregorian date and a time, as they might be displayed on a watch,
independent of time zone. SQL type name: DATETIME
|
Geography type |
A collection of points, linestrings, and polygons, which is represented as a
point set, or a subset of the surface of the Earth. SQL type name: GEOGRAPHY
|
Interval type |
A duration of time, without referring to any specific point in time. SQL type name: INTERVAL
|
JSON type |
Represents JSON, a lightweight data-interchange format. SQL type name: JSON
|
Numeric types |
A numeric value. Several types are supported.
A 64-bit integer.
A decimal value with precision of 38 digits.
A decimal value with precision of 76.76 digits (the 77th digit is partial).
An approximate double precision numeric value. |
Range type |
Contiguous range between two dates, datetimes, or timestamps. SQL type name: RANGE
|
String type |
Variable-length character data. SQL type name: STRING
|
Struct type |
Container of ordered fields. SQL type name: STRUCT
|
Time type |
A time of day, as might be displayed on a clock, independent of a specific
date and time zone. SQL type name: TIME
|
Timestamp type |
A timestamp value represents an absolute point in time,
independent of any time zone or convention such as
daylight saving time (DST). SQL type name: TIMESTAMP
|
Data type properties
When storing and querying data, it is helpful to keep the following data type properties in mind:
Nullable data types
For nullable data types, NULL
is a valid value. Currently, all existing
data types are nullable. Conditions apply for
arrays.
Orderable data types
Expressions of orderable data types can be used in an ORDER BY
clause.
Applies to all data types except for:
ARRAY
STRUCT
GEOGRAPHY
JSON
Ordering NULL
s
In the context of the ORDER BY
clause, NULL
s are the minimum
possible value; that is, NULL
s appear first in ASC
sorts and last in
DESC
sorts.
NULL
values can be specified as the first or last values for a column
irrespective of ASC
or DESC
by using the NULLS FIRST
or NULLS LAST
modifiers respectively.
To learn more about using ASC
, DESC
, NULLS FIRST
and NULLS LAST
, see
the ORDER BY
clause.
Ordering floating points
Floating point values are sorted in this order, from least to greatest:
NULL
NaN
— AllNaN
values are considered equal when sorting.-inf
- Negative numbers
- 0 or -0 — All zero values are considered equal when sorting.
- Positive numbers
+inf
Groupable data types
Groupable data types can generally appear in an expression following GROUP BY
,
DISTINCT
, and PARTITION BY
. All data types are supported except for:
GEOGRAPHY
JSON
Grouping with floating point types
Groupable floating point types can appear in an expression following GROUP BY
and DISTINCT
. PARTITION BY
expressions cannot
include floating point types.
Special floating point values are grouped in the following way, including
both grouping done by a GROUP BY
clause and grouping done by the
DISTINCT
keyword:
NULL
NaN
— AllNaN
values are considered equal when grouping.-inf
- 0 or -0 — All zero values are considered equal when grouping.
+inf
Grouping with arrays
An ARRAY
type is groupable if its element type is
groupable. An ARRAY
type
is only groupable in a GROUP BY
clause or in a
SELECT DISTINCT
clause.
Two arrays are in the same group if and only if one of the following statements is true:
- The two arrays are both
NULL
. - The two arrays have the same number of elements and all corresponding elements are in the same groups.
Grouping with structs
A STRUCT
type is groupable if its field types are
groupable. A STRUCT
type
is only groupable in a GROUP BY
clause or in a
SELECT DISTINCT
clause.
Two structs are in the same group if and only if one of the following statements is true:
- The two structs are both
NULL
. - All corresponding field values between the structs are in the same groups.
Comparable data types
Values of the same comparable data type can be compared to each other. All data types are supported except for:
GEOGRAPHY
JSON
ARRAY
Notes:
- Equality comparisons for structs are supported field by field, in field order. Field names are ignored. Less than and greater than comparisons are not supported.
- To compare geography values, use ST_Equals.
- When comparing ranges, the lower bounds are compared. If the lower bounds are equal, the upper bounds are compared, instead.
- When comparing ranges,
NULL
values are handled as follows:NULL
lower bounds are sorted before non-NULL
lower bounds.NULL
upper bounds are sorted after non-NULL
upper bounds.- If two bounds that are being compared are
NULL
, the comparison isTRUE
. - An
UNBOUNDED
bound is treated as aNULL
bound.
- All types that support comparisons can be used in a
JOIN
condition. See JOIN Types for an explanation of join conditions.
Collatable data types
Collatable data types support collation, which determines how to sort and compare strings. These data types support collation:
- String
- String fields in a struct
- String elements in an array
Data type sizes
Use the following table to see the size in logical bytes for each supported data type.
Data type | Size |
---|---|
ARRAY |
The sum of the size of its elements. For example, an array defined as
(ARRAY<INT64> ) that contains 4 entries is
calculated as 32 logical bytes (4 entries x 8 logical bytes). |
BIGNUMERIC |
32 logical bytes |
BOOL |
1 logical byte |
BYTES |
2 logical bytes + the number of logical bytes in the value |
DATE |
8 logical bytes |
DATETIME |
8 logical bytes |
FLOAT64 |
8 logical bytes |
GEOGRAPHY |
16 logical bytes + 24 logical bytes * the number of vertices in the geography type. To verify the number of vertices, use the ST_NumPoints
function. |
INT64 |
8 logical bytes |
INTERVAL |
16 logical bytes |
JSON |
The number of logical bytes in UTF-8 encoding of the JSON-formatted string equivalent after canonicalization. |
NUMERIC |
16 logical bytes |
RANGE |
16 logical bytes |
STRING |
2 logical bytes + the UTF-8 encoded string size |
STRUCT |
0 logical bytes + the size of the contained fields |
TIME |
8 logical bytes |
TIMESTAMP |
8 logical bytes |
A NULL
value for any data type is calculated as 0 logical bytes.
A repeated column is stored as an array, and the size is calculated based on the
column data type and the number of values. For example, an integer column
(INT64
) that is repeated (ARRAY<INT64>
) and contains 4 entries is calculated
as 32 logical bytes (4 entries x 8 logical bytes). The total size of all values
in a table row can't exceed the
maximum row size.
Parameterized data types
Syntax:
DATA_TYPE(param[, ...])
You can use parameters to specify constraints for the following data types:
STRING
BYTES
NUMERIC
BIGNUMERIC
A data type that is declared with parameters is called a parameterized data type. You can only use parameterized data types with columns and script variables. A column with a parameterized data type is a parameterized column and a script variable with a parameterized data type is a parameterized script variable. Parameterized type constraints are enforced when writing a value to a parameterized column or when assigning a value to a parameterized script variable.
A data type's parameters are not propagated in an expression, only the data type is.
Examples
-- Declare a variable with type parameters.
DECLARE x STRING(10);
-- This is a valid assignment to x.
SET x = "hello";
-- This assignment to x violates the type parameter constraint and results in an OUT_OF_RANGE error.
SET x = "this string is too long"
-- Declare variables with type parameters.
DECLARE x NUMERIC(10) DEFAULT 12345;
DECLARE y NUMERIC(5, 2) DEFAULT 123.45;
-- The variable x is treated as a NUMERIC value when read, so the result of this query
-- is a NUMERIC without type parameters.
SELECT x;
-- Type parameters are not propagated within expressions, so variables x and y are treated
-- as NUMERIC values when read and the result of this query is a NUMERIC without type parameters.
SELECT x + y;
Array type
Name | Description |
---|---|
ARRAY |
Ordered list of zero or more elements of any non-array type. |
An array is an ordered list of zero or more elements of non-array values. Elements in an array must share the same type.
Arrays of arrays are not allowed. Queries that would produce an array of
arrays will return an error. Instead, a struct must be inserted between the
arrays using the SELECT AS STRUCT
construct.
To learn more about the literal representation of an array type, see Array literals.
To learn more about using arrays in GoogleSQL, see Work with arrays.
NULL
s and the array type
Currently, GoogleSQL for BigQuery has the following rules with respect to NULL
s and
arrays:
An array can be
NULL
.For example:
SELECT CAST(NULL AS ARRAY<INT64>) IS NULL AS array_is_null; /*---------------* | array_is_null | +---------------+ | TRUE | *---------------*/
GoogleSQL for BigQuery translates a
NULL
array into an empty array in the query result, although inside the query,NULL
and empty arrays are two distinct values.For example:
WITH Items AS ( SELECT [] AS numbers, "Empty array in query" AS description UNION ALL SELECT CAST(NULL AS ARRAY<INT64>), "NULL array in query") SELECT numbers, description, numbers IS NULL AS numbers_null FROM Items; /*---------+----------------------+--------------* | numbers | description | numbers_null | +---------+----------------------+--------------+ | [] | Empty array in query | false | | [] | NULL array in query | true | *---------+----------------------+--------------*/
When you write a
NULL
array to a table, it is converted to an empty array. If you writeItems
to a table from the previous query, then each array is written as an empty array:SELECT numbers, description, numbers IS NULL AS numbers_null FROM Items; /*---------+----------------------+--------------* | numbers | description | numbers_null | +---------+----------------------+--------------+ | [] | Empty array in query | false | | [] | NULL array in query | false | *---------+----------------------+--------------*/
GoogleSQL for BigQuery raises an error if the query result has an array which contains
NULL
elements, although such an array can be used inside the query.For example, this works:
SELECT FORMAT("%T", [1, NULL, 3]) as numbers; /*--------------* | numbers | +--------------+ | [1, NULL, 3] | *--------------*/
But this raises an error:
-- error SELECT [1, NULL, 3] as numbers;
Declaring an array type
ARRAY<T>
Array types are declared using the angle brackets (<
and >
). The type
of the elements of an array can be arbitrarily complex with the exception that
an array cannot directly contain another array.
Examples
Type Declaration | Meaning |
---|---|
ARRAY<INT64>
|
Simple array of 64-bit integers. |
ARRAY<BYTES(5)>
|
Simple array of parameterized bytes. |
ARRAY<STRUCT<INT64, INT64>>
|
An array of structs, each of which contains two 64-bit integers. |
ARRAY<ARRAY<INT64>>
(not supported) |
This is an invalid type declaration which is included here just in case you came looking for how to create a multi-level array. Arrays cannot contain arrays directly. Instead see the next example. |
ARRAY<STRUCT<ARRAY<INT64>>>
|
An array of arrays of 64-bit integers. Notice that there is a struct between the two arrays because arrays cannot hold other arrays directly. |
Constructing an array
You can construct an array using array literals or array functions.
Using array literals
You can build an array literal in GoogleSQL using brackets ([
and
]
). Each element in an array is separated by a comma.
SELECT [1, 2, 3] AS numbers;
SELECT ["apple", "pear", "orange"] AS fruit;
SELECT [true, false, true] AS booleans;
You can also create arrays from any expressions that have compatible types. For example:
SELECT [a, b, c]
FROM
(SELECT 5 AS a,
37 AS b,
406 AS c);
SELECT [a, b, c]
FROM
(SELECT CAST(5 AS INT64) AS a,
CAST(37 AS FLOAT64) AS b,
406 AS c);
Notice that the second example contains three expressions: one that returns an
INT64
, one that returns a FLOAT64
, and one that
declares a literal. This expression works because all three expressions share
FLOAT64
as a supertype.
To declare a specific data type for an array, use angle
brackets (<
and >
). For example:
SELECT ARRAY<FLOAT64>[1, 2, 3] AS floats;
Arrays of most data types, such as INT64
or STRING
, don't require
that you declare them first.
SELECT [1, 2, 3] AS numbers;
You can write an empty array of a specific type using ARRAY<type>[]
. You can
also write an untyped empty array using []
, in which case GoogleSQL
attempts to infer the array type from the surrounding context. If
GoogleSQL cannot infer a type, the default type ARRAY<INT64>
is used.
Using generated values
You can also construct an ARRAY
with generated values.
Generating arrays of integers
GENERATE_ARRAY
generates an array of values from a starting and ending value and a step value.
For example, the following query generates an array that contains all of the odd
integers from 11 to 33, inclusive:
SELECT GENERATE_ARRAY(11, 33, 2) AS odds;
/*--------------------------------------------------*
| odds |
+--------------------------------------------------+
| [11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33] |
*--------------------------------------------------*/
You can also generate an array of values in descending order by giving a negative step value:
SELECT GENERATE_ARRAY(21, 14, -1) AS countdown;
/*----------------------------------*
| countdown |
+----------------------------------+
| [21, 20, 19, 18, 17, 16, 15, 14] |
*----------------------------------*/
Generating arrays of dates
GENERATE_DATE_ARRAY
generates an array of DATE
s from a starting and ending DATE
and a step
INTERVAL
.
You can generate a set of DATE
values using GENERATE_DATE_ARRAY
. For
example, this query returns the current DATE
and the following
DATE
s at 1 WEEK
intervals up to and including a later DATE
:
SELECT
GENERATE_DATE_ARRAY('2017-11-21', '2017-12-31', INTERVAL 1 WEEK)
AS date_array;
/*--------------------------------------------------------------------------*
| date_array |
+--------------------------------------------------------------------------+
| [2017-11-21, 2017-11-28, 2017-12-05, 2017-12-12, 2017-12-19, 2017-12-26] |
*--------------------------------------------------------------------------*/
Boolean type
Name | Description |
---|---|
BOOL |
Boolean values are represented by the keywords TRUE and
FALSE (case-insensitive). |
Boolean values are sorted in this order, from least to greatest:
NULL
FALSE
TRUE
Bytes type
Name | Description |
---|---|
BYTES |
Variable-length binary data. |
String and bytes are separate types that cannot be used interchangeably. Most functions on strings are also defined on bytes. The bytes version operates on raw bytes rather than Unicode characters. Casts between string and bytes enforce that the bytes are encoded using UTF-8.
To learn more about the literal representation of a bytes type, see Bytes literals.
Parameterized bytes type
Parameterized Type | Description |
---|---|
BYTES(L) |
Sequence of bytes with a maximum of L bytes allowed in the binary
string, where L is a positive INT64 value. If a
sequence of bytes has more than L bytes, throws an
OUT_OF_RANGE error. |
See Parameterized Data Types for more information on parameterized types and where they can be used.
Date type
Name | Range |
---|---|
DATE |
0001-01-01 to 9999-12-31. |
The date type represents a Gregorian calendar date, independent of time zone. A date value does not represent a specific 24-hour time period. Rather, a given date value represents a different 24-hour period when interpreted in different time zones, and may represent a shorter or longer day during daylight saving time (DST) transitions. To represent an absolute point in time, use a timestamp.
Canonical format
YYYY-[M]M-[D]D
YYYY
: Four-digit year.[M]M
: One or two digit month.[D]D
: One or two digit day.
To learn more about the literal representation of a date type, see Date literals.
Datetime type
Name | Range |
---|---|
DATETIME |
0001-01-01 00:00:00 to 9999-12-31 23:59:59.999999 |
A datetime value represents a Gregorian date and a time, as they might be displayed on a watch, independent of time zone. It includes the year, month, day, hour, minute, second, and subsecond. To represent an absolute point in time, use a timestamp.
Canonical format
civil_date_part[time_part]
civil_date_part:
YYYY-[M]M-[D]D
time_part:
{ |T|t}[H]H:[M]M:[S]S[.F]
YYYY
: Four-digit year.[M]M
: One or two digit month.[D]D
: One or two digit day.{ |T|t}
: A space or aT
ort
separator. TheT
andt
separators are flags for time.[H]H
: One or two digit hour (valid values from 00 to 23).[M]M
: One or two digit minutes (valid values from 00 to 59).[S]S
: One or two digit seconds (valid values from 00 to 60).[.F]
: Up to six fractional digits (microsecond precision).
To learn more about the literal representation of a datetime type, see Datetime literals.
Geography type
Name | Description |
---|---|
GEOGRAPHY |
A collection of points, linestrings, and polygons, which is represented as a point set, or a subset of the surface of the Earth. |
The geography type is based on the OGC Simple Features specification (SFS), and can contain the following objects:
Geography object | Description |
---|---|
Point |
A single location in coordinate space known as a point. A point has an x-coordinate value and a y-coordinate value, where the x-coordinate is longitude and the y-coordinate is latitude of the point on the WGS84 reference ellipsoid. Syntax: POINT(x_coordinate y_coordinate)Examples: POINT(32 210) POINT EMPTY |
LineString |
Represents a linestring, which is a one-dimensional geometric object, with a sequence of points and geodesic edges between them. Syntax: LINESTRING(point[, ...])Examples: LINESTRING(1 1, 2 1, 3.1 2.88, 3 -3) LINESTRING EMPTY |
Polygon |
A polygon, which is represented as a planar surface defined by 1 exterior boundary and 0 or more interior boundaries. Each interior boundary defines a hole in the polygon. The boundary loops of polygons are oriented so that if you traverse the boundary vertices in order, the interior of the polygon is on the left. Syntax: POLYGON(interior_ring[, ...]) interior_ring: (point[, ...])Examples: POLYGON((0 0, 2 2, 2 0, 0 0), (2 2, 3 4, 2 4, 2 2)) POLYGON EMPTY |
MultiPoint |
A collection of points. Syntax: MULTIPOINT(point[, ...])Examples: MULTIPOINT(0 32, 123 9, 48 67) MULTIPOINT EMPTY |
MultiLineString |
Represents a multilinestring, which is a collection of linestrings. Syntax: MULTILINESTRING((linestring)[, ...])Examples: MULTILINESTRING((2 2, 3 4), (5 6, 7 7)) MULTILINESTRING EMPTY |
MultiPolygon |
Represents a multipolygon, which is a collection of polygons. Syntax: MULTIPOLYGON((polygon)[, ...])Examples: MULTIPOLYGON(((0 -1, 1 0, 1 1, 0 -1)), ((0 0, 2 2, 3 0, 0 0), (2 2, 3 4, 2 4, 1 9))) MULTIPOLYGON EMPTY |
GeometryCollection |
Represents a geometry collection with elements of different dimensions or an empty geography. Syntax: GEOMETRYCOLLECTION(geography_object[, ...])Examples: GEOMETRYCOLLECTION(MULTIPOINT(-1 2, 0 12), LINESTRING(-2 4, 0 6)) GEOMETRYCOLLECTION EMPTY |
The points, linestrings and polygons of a geography value form a simple arrangement on the WGS84 reference ellipsoid. A simple arrangement is one where no point on the WGS84 surface is contained by multiple elements of the collection. If self intersections exist, they are automatically removed.
The geography that contains no points, linestrings or polygons is called an empty geography. An empty geography is not associated with a particular geometry shape. For example, the following query produces the same results:
SELECT
ST_GEOGFROMTEXT('POINT EMPTY') AS a,
ST_GEOGFROMTEXT('GEOMETRYCOLLECTION EMPTY') AS b
/*--------------------------+--------------------------*
| a | b |
+--------------------------+--------------------------+
| GEOMETRYCOLLECTION EMPTY | GEOMETRYCOLLECTION EMPTY |
*--------------------------+--------------------------*/
The structure of compound geometry objects is not preserved if a
simpler type can be produced. For example, in column b
,
GEOMETRYCOLLECTION
with (POINT(1 1)
and POINT(2 2)
is converted into the
simplest possible geometry, MULTIPOINT(1 1, 2 2)
.
SELECT
ST_GEOGFROMTEXT('MULTIPOINT(1 1, 2 2)') AS a,
ST_GEOGFROMTEXT('GEOMETRYCOLLECTION(POINT(1 1), POINT(2 2))') AS b
/*----------------------+----------------------*
| a | b |
+----------------------+----------------------+
| MULTIPOINT(1 1, 2 2) | MULTIPOINT(1 1, 2 2) |
*----------------------+----------------------*/
A geography is the result of, or an argument to, a Geography Function.
Interval type
Name | Range |
---|---|
INTERVAL |
-10000-0 -3660000 -87840000:0:0 to 10000-0 3660000 87840000:0:0 |
An INTERVAL
object represents duration or amount of time, without referring
to any specific point in time.
Canonical format
[sign]Y-M [sign]D [sign]H:M:S[.F]
sign
:+
or-
Y
: YearM
: MonthD
: DayH
: HourM
: MinuteS
: Second[.F]
: Up to six fractional digits (microsecond precision)
To learn more about the literal representation of an interval type, see Interval literals.
Constructing an interval
You can construct an interval with an interval literal that supports a single datetime part or a datetime part range.
Construct an interval with a single datetime part
INTERVAL int64_expression datetime_part
You can construct an INTERVAL
object with an INT64
expression and one
interval-supported datetime part. For example:
-- 1 year, 0 months, 0 days, 0 hours, 0 minutes, and 0 seconds (1-0 0 0:0:0)
INTERVAL 1 YEAR
INTERVAL 4 QUARTER
INTERVAL 12 MONTH
-- 0 years, 3 months, 0 days, 0 hours, 0 minutes, and 0 seconds (0-3 0 0:0:0)
INTERVAL 1 QUARTER
INTERVAL 3 MONTH
-- 0 years, 0 months, 42 days, 0 hours, 0 minutes, and 0 seconds (0-0 42 0:0:0)
INTERVAL 6 WEEK
INTERVAL 42 DAY
-- 0 years, 0 months, 0 days, 25 hours, 0 minutes, and 0 seconds (0-0 0 25:0:0)
INTERVAL 25 HOUR
INTERVAL 1500 MINUTE
INTERVAL 90000 SECOND
-- 0 years, 0 months, 0 days, 1 hours, 30 minutes, and 0 seconds (0-0 0 1:30:0)
INTERVAL 90 MINUTE
-- 0 years, 0 months, 0 days, 0 hours, 1 minutes, and 30 seconds (0-0 0 0:1:30)
INTERVAL 90 SECOND
-- 0 years, 0 months, -5 days, 0 hours, 0 minutes, and 0 seconds (0-0 -5 0:0:0)
INTERVAL -5 DAY
For additional examples, see Interval literals.
Construct an interval with a datetime part range
INTERVAL datetime_parts_string starting_datetime_part TO ending_datetime_part
You can construct an INTERVAL
object with a STRING
that contains the
datetime parts that you want to include, a starting datetime part, and an ending
datetime part. The resulting INTERVAL
object only includes datetime parts in
the specified range.
You can use one of the following formats with the interval-supported datetime parts:
Datetime part string | Datetime parts | Example |
---|---|---|
Y-M |
YEAR TO MONTH |
INTERVAL '2-11' YEAR TO MONTH |
Y-M D |
YEAR TO DAY |
INTERVAL '2-11 28' YEAR TO DAY |
Y-M D H |
YEAR TO HOUR |
INTERVAL '2-11 28 16' YEAR TO HOUR |
Y-M D H:M |
YEAR TO MINUTE |
INTERVAL '2-11 28 16:15' YEAR TO MINUTE |
Y-M D H:M:S |
YEAR TO SECOND |
INTERVAL '2-11 28 16:15:14' YEAR TO SECOND |
M D |
MONTH TO DAY |
INTERVAL '11 28' MONTH TO DAY |
M D H |
MONTH TO HOUR |
INTERVAL '11 28 16' MONTH TO HOUR |
M D H:M |
MONTH TO MINUTE |
INTERVAL '11 28 16:15' MONTH TO MINUTE |
M D H:M:S |
MONTH TO SECOND |
INTERVAL '11 28 16:15:14' MONTH TO SECOND |
D H |
DAY TO HOUR |
INTERVAL '28 16' DAY TO HOUR |
D H:M |
DAY TO MINUTE |
INTERVAL '28 16:15' DAY TO MINUTE |
D H:M:S |
DAY TO SECOND |
INTERVAL '28 16:15:14' DAY TO SECOND |
H:M |
HOUR TO MINUTE |
INTERVAL '16:15' HOUR TO MINUTE |
H:M:S |
HOUR TO SECOND |
INTERVAL '16:15:14' HOUR TO SECOND |
M:S |
MINUTE TO SECOND |
INTERVAL '15:14' MINUTE TO SECOND |
For example:
-- 0 years, 8 months, 20 days, 17 hours, 0 minutes, and 0 seconds (0-8 20 17:0:0)
INTERVAL '8 20 17' MONTH TO HOUR
-- 0 years, 8 months, -20 days, 17 hours, 0 minutes, and 0 seconds (0-8 -20 17:0:0)
INTERVAL '8 -20 17' MONTH TO HOUR
For additional examples, see Interval literals.
Interval-supported date and time parts
You can use the following date parts to construct an interval:
YEAR
: Number of years,Y
.QUARTER
: Number of quarters; each quarter is converted to3
months,M
.MONTH
: Number of months,M
. Each12
months is converted to1
year.WEEK
: Number of weeks; Each week is converted to7
days,D
.DAY
: Number of days,D
.
You can use the following time parts to construct an interval:
HOUR
: Number of hours,H
.MINUTE
: Number of minutes,M
. Each60
minutes is converted to1
hour.SECOND
: Number of seconds,S
. Each60
seconds is converted to1
minute. Can include up to six fractional digits (microsecond precision).MILLISECOND
: Number of milliseconds.MICROSECOND
: Number of microseconds.
JSON type
Name | Description |
---|---|
JSON |
Represents JSON, a lightweight data-interchange format. |
Expect these canonicalization behaviors when creating a value of JSON type:
- Booleans, strings, and nulls are preserved exactly.
- Whitespace characters are not preserved.
- A JSON value can store integers in the range of
-9,223,372,036,854,775,808 (minimum signed 64-bit integer) to
18,446,744,073,709,551,615 (maximum unsigned 64-bit integer) and
floating point numbers within a domain of
FLOAT64
. - The order of elements in an array is preserved exactly.
- The order of the members of an object is not guaranteed or preserved.
- If an object has duplicate keys, the first key that is found is preserved.
- Up to 500 levels can be nested.
- The format of the original string representation of a JSON number may not be preserved.
To learn more about the literal representation of a JSON type, see JSON literals.
Numeric types
Numeric types include the following types:
INT64
with aliasINT
,SMALLINT
,INTEGER
,BIGINT
,TINYINT
,BYTEINT
NUMERIC
with aliasDECIMAL
BIGNUMERIC
with aliasBIGDECIMAL
FLOAT64
Integer type
Integers are numeric values that do not have fractional components.
Name | Range |
---|---|
INT64
INT
SMALLINT
INTEGER
BIGINT
TINYINT
BYTEINT
|
-9,223,372,036,854,775,808 to 9,223,372,036,854,775,807 |
INT
, SMALLINT
, INTEGER
, BIGINT
, TINYINT
, and BYTEINT
are aliases
for INT64
.
To learn more about the literal representation of an integer type, see Integer literals.
Decimal types
Decimal type values are numeric values with fixed decimal precision and scale. Precision is the number of digits that the number contains. Scale is how many of these digits appear after the decimal point.
This type can represent decimal fractions exactly, and is suitable for financial calculations.
Name | Precision, Scale, and Range |
---|---|
NUMERIC
DECIMAL |
Precision: 38 Scale: 9 Minimum value greater than 0 that can be handled: 1e-9 Min: -9.9999999999999999999999999999999999999E+28 Max: 9.9999999999999999999999999999999999999E+28 |
BIGNUMERIC
BIGDECIMAL |
Precision: 76.76 (the 77th digit is partial) Scale: 38 Minimum value greater than 0 that can be handled: 1e-38 Min: -5.7896044618658097711785492504343953926634992332820282019728792003956564819968E+38 Max: 5.7896044618658097711785492504343953926634992332820282019728792003956564819967E+38 |
DECIMAL
is an alias for NUMERIC
.
BIGDECIMAL
is an alias for BIGNUMERIC
.
To learn more about the literal representation of a NUMERIC
type,
see NUMERIC
literals.
To learn more about the literal representation of a BIGNUMERIC
type,
see BIGNUMERIC
literals.
To learn more about how BigQuery rounds values stored as a DECIMAL
type, see rounding mode.
Parameterized decimal type
Parameterized Type | Description |
---|---|
NUMERIC(P[,S])
DECIMAL(P[,S]) |
A NUMERIC or DECIMAL type with a maximum precision
of P and maximum scale of S, where P and
S are INT64 types. S is interpreted to be
0 if unspecified.Maximum scale range: 0 ≤ S ≤ 9 Maximum precision range: max(1, S) ≤ P ≤ S + 29 |
BIGNUMERIC(P[, S])
BIGDECIMAL(P[, S]) |
A BIGNUMERIC or BIGDECIMAL type with a maximum
precision of P and maximum scale of S, where
P and S are INT64 types. S is
interpreted to be 0 if unspecified.Maximum scale range: 0 ≤ S ≤ 38 Maximum precision range: max(1, S) ≤ P ≤ S + 38 |
If a value has more than S
decimal digits, the value is rounded to
S
decimal digits. For example, inserting the value 1.125
into a
NUMERIC(5, 2)
column rounds 1.125
half-up to 1.13
.
If a value has more than P
digits, throws an OUT_OF_RANGE
error.
For example, inserting 1111
into a NUMERIC(5, 2)
column returns an
OUT_OF_RANGE
error since 1111
is larger than 999.99
, the maximum allowed
value in a NUMERIC(5, 2)
column.
See Parameterized Data Types for more information on parameterized types and where they can be used.
Floating point type
Floating point values are approximate numeric values with fractional components.
Name | Description |
---|---|
FLOAT64
|
Double precision (approximate) numeric values. |
To learn more about the literal representation of a floating point type, see Floating point literals.
Floating point semantics
When working with floating point numbers, there are special non-numeric values
that need to be considered: NaN
and +/-inf
Arithmetic operators provide standard IEEE-754 behavior for all finite input values that produce finite output and for all operations for which at least one input is non-finite.
Function calls and operators return an overflow error if the input is finite
but the output would be non-finite. If the input contains non-finite values, the
output can be non-finite. In general functions do not introduce NaN
s or
+/-inf
. However, specific functions like IEEE_DIVIDE
can return non-finite
values on finite input. All such cases are noted explicitly in
Mathematical functions.
Floating point values are approximations.
- The binary format used to represent floating point values can only represent
a subset of the numbers between the most positive number and most
negative number in the value range. This enables efficient handling of a
much larger range than would be possible otherwise.
Numbers that are not exactly representable are approximated by utilizing a
close value instead. For example,
0.1
cannot be represented as an integer scaled by a power of2
. When this value is displayed as a string, it is rounded to a limited number of digits, and the value approximating0.1
might appear as"0.1"
, hiding the fact that the value is not precise. In other situations, the approximation can be visible. - Summation of floating point values might produce surprising results because
of limited precision. For example,
(1e30 + 1) - 1e30 = 0
, while(1e30 - 1e30) + 1 = 1.0
. This is because the floating point value does not have enough precision to represent(1e30 + 1)
, and the result is rounded to1e30
. This example also shows that the result of theSUM
aggregate function of floating points values depends on the order in which the values are accumulated. In general, this order is not deterministic and therefore the result is not deterministic. Thus, the resultingSUM
of floating point values might not be deterministic and two executions of the same query on the same tables might produce different results. - If the above points are concerning, use a decimal type instead.
Mathematical function examples
Left Term | Operator | Right Term | Returns |
---|---|---|---|
Any value | + |
NaN |
NaN |
1.0 | + |
+inf |
+inf |
1.0 | + |
-inf |
-inf |
-inf |
+ |
+inf |
NaN |
Maximum FLOAT64 value |
+ |
Maximum FLOAT64 value |
Overflow error |
Minimum FLOAT64 value |
/ |
2.0 | 0.0 |
1.0 | / |
0.0 |
"Divide by zero" error |
Comparison operators provide standard IEEE-754 behavior for floating point input.
Comparison operator examples
Left Term | Operator | Right Term | Returns |
---|---|---|---|
NaN |
= |
Any value | FALSE |
NaN |
< |
Any value | FALSE |
Any value | < |
NaN |
FALSE |
-0.0 | = |
0.0 | TRUE |
-0.0 | < |
0.0 | FALSE |
For more information on how these values are ordered and grouped so they can be compared, see Ordering floating point values.
Range type
Name | Range |
---|---|
RANGE |
Contiguous range between two dates, datetimes, or timestamps. The lower and upper bound for the range are optional. The lower bound is inclusive and the upper bound is exclusive. |
Declare a range type
A range type can be declared as follows:
Type Declaration | Meaning |
---|---|
RANGE<DATE> |
Contiguous range between two dates. |
RANGE<DATETIME> |
Contiguous range between two datetimes. |
RANGE<TIMESTAMP> |
Contiguous range between two timestamps. |
Construct a range
You can construct a range with the RANGE
constructor
or a range literal.
Construct a range with a constructor
You can construct a range with the RANGE
constructor. To learn more,
see RANGE
.
Construct a range with a literal
You can construct a range with a range literal. The canonical format for a range literal has the following parts:
RANGE<T> '[lower_bound, upper_bound)'
T
: The type of range. This can beDATE
,DATETIME
, orTIMESTAMP
.lower_bound
: The range starts from this value. This can be a date, datetime, or timestamp literal. If this value isUNBOUNDED
orNULL
, the range does not include a lower bound.upper_bound
: The range ends before this value. This can be a date, datetime, or timestamp literal. If this value isUNBOUNDED
orNULL
, the range does not include an upper bound.
T
, lower_bound
, and upper_bound
must be of the same data type.
To learn more about the literal representation of a range type, see Range literals.
Additional details
The range type does not support arithmetic operators.
String type
Name | Description |
---|---|
STRING |
Variable-length character (Unicode) data. |
Input string values must be UTF-8 encoded and output string values will be UTF-8 encoded. Alternate encodings like CESU-8 and Modified UTF-8 are not treated as valid UTF-8.
All functions and operators that act on string values operate on Unicode
characters rather than bytes. For example, functions like SUBSTR
and LENGTH
applied to string input count the number of characters, not bytes.
Each Unicode character has a numeric value called a code point assigned to it. Lower code points are assigned to lower characters. When characters are compared, the code points determine which characters are less than or greater than other characters.
Most functions on strings are also defined on bytes. The bytes version operates on raw bytes rather than Unicode characters. Strings and bytes are separate types that cannot be used interchangeably. There is no implicit casting in either direction. Explicit casting between string and bytes does UTF-8 encoding and decoding. Casting bytes to string returns an error if the bytes are not valid UTF-8.
To learn more about the literal representation of a string type, see String literals.
Parameterized string type
Parameterized Type | Description |
---|---|
STRING(L) |
String with a maximum of L Unicode characters allowed in
the string, where L is a positive INT64 value. If a
string with more than L Unicode characters is assigned, throws an
OUT_OF_RANGE error. |
See Parameterized Data Types for more information on parameterized types and where they can be used.
Struct type
Name | Description |
---|---|
STRUCT |
Container of ordered fields each with a type (required) and field name (optional). |
To learn more about the literal representation of a struct type, see Struct literals.
Declaring a struct type
STRUCT<T>
Struct types are declared using the angle brackets (<
and >
). The type of
the elements of a struct can be arbitrarily complex.
Examples
Type Declaration | Meaning |
---|---|
STRUCT<INT64>
|
Simple struct with a single unnamed 64-bit integer field. |
STRUCT<x STRING(10)>
|
Simple struct with a single parameterized string field named x. |
STRUCT<x STRUCT<y INT64, z INT64>>
|
A struct with a nested struct named x inside it. The struct
x has two fields, y and z , both of which
are 64-bit integers. |
STRUCT<inner_array ARRAY<INT64>>
|
A struct containing an array named inner_array that holds
64-bit integer elements. |
Constructing a struct
Tuple syntax
(expr1, expr2 [, ... ])
The output type is an anonymous struct type with anonymous fields with types matching the types of the input expressions. There must be at least two expressions specified. Otherwise this syntax is indistinguishable from an expression wrapped with parentheses.
Examples
Syntax | Output Type | Notes |
---|---|---|
(x, x+y) |
STRUCT<?,?> |
If column names are used (unquoted strings), the struct field data type is
derived from the column data type. x and y are
columns, so the data types of the struct fields are derived from the column
types and the output type of the addition operator. |
This syntax can also be used with struct comparison for comparison expressions
using multi-part keys, e.g., in a WHERE
clause:
WHERE (Key1,Key2) IN ( (12,34), (56,78) )
Typeless struct syntax
STRUCT( expr1 [AS field_name] [, ... ])
Duplicate field names are allowed. Fields without names are considered anonymous
fields and cannot be referenced by name. struct values can be NULL
, or can
have NULL
field values.
Examples
Syntax | Output Type |
---|---|
STRUCT(1,2,3) |
STRUCT<int64,int64,int64> |
STRUCT() |
STRUCT<> |
STRUCT('abc') |
STRUCT<string> |
STRUCT(1, t.str_col) |
STRUCT<int64, str_col string> |
STRUCT(1 AS a, 'abc' AS b) |
STRUCT<a int64, b string> |
STRUCT(str_col AS abc) |
STRUCT<abc string> |
Typed struct syntax
STRUCT<[field_name] field_type, ...>( expr1 [, ... ])
Typed syntax allows constructing structs with an explicit struct data type. The
output type is exactly the field_type
provided. The input expression is
coerced to field_type
if the two types are not the same, and an error is
produced if the types are not compatible. AS alias
is not allowed on the input
expressions. The number of expressions must match the number of fields in the
type, and the expression types must be coercible or literal-coercible to the
field types.
Examples
Syntax | Output Type |
---|---|
STRUCT<int64>(5) |
STRUCT<int64> |
STRUCT<date>("2011-05-05") |
STRUCT<date> |
STRUCT<x int64, y string>(1, t.str_col) |
STRUCT<x int64, y string> |
STRUCT<int64>(int_col) |
STRUCT<int64> |
STRUCT<x int64>(5 AS x) |
Error - Typed syntax does not allow AS |
Limited comparisons for structs
Structs can be directly compared using equality operators:
- Equal (
=
) - Not Equal (
!=
or<>
) - [
NOT
]IN
Notice, though, that these direct equality comparisons compare the fields of the struct pairwise in ordinal order ignoring any field names. If instead you want to compare identically named fields of a struct, you can compare the individual fields directly.
Time type
Name | Range |
---|---|
TIME |
00:00:00 to 23:59:59.999999 |
A time value represents a time of day, as might be displayed on a clock, independent of a specific date and time zone. To represent an absolute point in time, use a timestamp.
Canonical format
[H]H:[M]M:[S]S[.F]
[H]H
: One or two digit hour (valid values from 00 to 23).[M]M
: One or two digit minutes (valid values from 00 to 59).[S]S
: One or two digit seconds (valid values from 00 to 60).[.F]
: Up to six fractional digits (microsecond precision).
To learn more about the literal representation of a time type, see Time literals.
Timestamp type
Name | Range |
---|---|
TIMESTAMP |
0001-01-01 00:00:00 to 9999-12-31 23:59:59.999999 UTC |
A timestamp value represents an absolute point in time, independent of any time zone or convention such as daylight saving time (DST), with microsecond precision.
A timestamp is typically represented internally as the number of elapsed microseconds since a fixed initial point in time.
Note that a timestamp itself does not have a time zone; it represents the same instant in time globally. However, the display of a timestamp for human readability usually includes a Gregorian date, a time, and a time zone, in an implementation-dependent format. For example, the displayed values "2020-01-01 00:00:00 UTC", "2019-12-31 19:00:00 America/New_York", and "2020-01-01 05:30:00 Asia/Kolkata" all represent the same instant in time and therefore represent the same timestamp value.
- To represent a Gregorian date as it might appear on a calendar (a civil date), use a date value.
- To represent a time as it might appear on a clock (a civil time), use a time value.
- To represent a Gregorian date and time as they might appear on a watch, use a datetime value.
Canonical format
The canonical format for a timestamp literal has the following parts:
{
civil_date_part[time_part [time_zone]] |
civil_date_part[time_part[time_zone_offset]] |
civil_date_part[time_part[utc_time_zone]]
}
civil_date_part:
YYYY-[M]M-[D]D
time_part:
{ |T|t}[H]H:[M]M:[S]S[.F]
YYYY
: Four-digit year.[M]M
: One or two digit month.[D]D
: One or two digit day.{ |T|t}
: A space or aT
ort
separator. TheT
andt
separators are flags for time.[H]H
: One or two digit hour (valid values from 00 to 23).[M]M
: One or two digit minutes (valid values from 00 to 59).[S]S
: One or two digit seconds (valid values from 00 to 60).[.F]
: Up to six fractional digits (microsecond precision).[time_zone]
: String representing the time zone. When a time zone is not explicitly specified, the default time zone, UTC, is used. For details, see time zones.[time_zone_offset]
: String representing the offset from the Coordinated Universal Time (UTC) time zone. For details, see time zones.[utc_time_zone]
: String representing the Coordinated Universal Time (UTC), usually the letterZ
orz
. For details, see time zones.
To learn more about the literal representation of a timestamp type, see Timestamp literals.
Time zones
A time zone is used when converting from a civil date or time (as might appear on a calendar or clock) to a timestamp (an absolute time), or vice versa. This includes the operation of parsing a string containing a civil date and time like "2020-01-01 00:00:00" and converting it to a timestamp. The resulting timestamp value itself does not store a specific time zone, because it represents one instant in time globally.
Time zones are represented by strings in one of these canonical formats:
- Offset from Coordinated Universal Time (UTC), or the letter
Z
orz
for UTC. - Time zone name from the tz database.
The following timestamps are identical because the time zone offset
for America/Los_Angeles
is -08
for the specified date and time.
SELECT UNIX_MILLIS(TIMESTAMP '2008-12-25 15:30:00 America/Los_Angeles') AS millis;
SELECT UNIX_MILLIS(TIMESTAMP '2008-12-25 15:30:00-08:00') AS millis;
Specify Coordinated Universal Time (UTC)
You can specify UTC using the following suffix:
{Z|z}
You can also specify UTC using the following time zone name:
{Etc/UTC}
The Z
suffix is a placeholder that implies UTC when converting an RFC
3339-format value to a TIMESTAMP
value. The value Z
isn't
a valid time zone for functions that accept a time zone. If you're specifying a
time zone, or you're unsure of the format to use to specify UTC, we recommend
using the Etc/UTC
time zone name.
The Z
suffix isn't case sensitive. When using the Z
suffix, no space is
allowed between the Z
and the rest of the timestamp. The following are
examples of using the Z
suffix and the Etc/UTC
time zone name:
SELECT TIMESTAMP '2014-09-27T12:30:00.45Z'
SELECT TIMESTAMP '2014-09-27 12:30:00.45z'
SELECT TIMESTAMP '2014-09-27T12:30:00.45 Etc/UTC'
Specify an offset from Coordinated Universal Time (UTC)
You can specify the offset from UTC using the following format:
{+|-}H[H][:M[M]]
Examples:
-08:00
-8:15
+3:00
+07:30
-7
When using this format, no space is allowed between the time zone and the rest of the timestamp.
2014-09-27 12:30:00.45-8:00
Time zone name
Format:
tz_identifier
A time zone name is a tz identifier from the tz database. For a less comprehensive but simpler reference, see the List of tz database time zones on Wikipedia.
Examples:
America/Los_Angeles
America/Argentina/Buenos_Aires
Etc/UTC
Pacific/Auckland
When using a time zone name, a space is required between the name and the rest of the timestamp:
2014-09-27 12:30:00.45 America/Los_Angeles
Note that not all time zone names are interchangeable even if they do happen to
report the same time during a given part of the year. For example,
America/Los_Angeles
reports the same time as UTC-7:00
during daylight
saving time (DST), but reports the same time as UTC-8:00
outside of DST.
If a time zone is not specified, the default time zone value is used.
Leap seconds
A timestamp is simply an offset from 1970-01-01 00:00:00 UTC, assuming there are exactly 60 seconds per minute. Leap seconds are not represented as part of a stored timestamp.
If the input contains values that use ":60" in the seconds field to represent a leap second, that leap second is not preserved when converting to a timestamp value. Instead that value is interpreted as a timestamp with ":00" in the seconds field of the following minute.
Leap seconds do not affect timestamp computations. All timestamp computations are done using Unix-style timestamps, which do not reflect leap seconds. Leap seconds are only observable through functions that measure real-world time. In these functions, it is possible for a timestamp second to be skipped or repeated when there is a leap second.