# JSON functions and operators#

The SQL standard describes functions and operators to process JSON data. They allow you to access JSON data according to its structure, generate JSON data, and store it persistently in SQL tables.

Importantly, the SQL standard imposes that there is no dedicated data type to represent JSON data in SQL. Instead, JSON data is represented as character or binary strings. Although Trino supports JSON type, it is not used or produced by the following functions.

Trino supports three functions for querying JSON data: json_exists, json_query, and json_value. Each of them is based on the same mechanism of exploring and processing JSON input using JSON path.

Trino also supports two functions for generating JSON data – json_array, and json_object.

## JSON path language#

The JSON path language is a special language, used exclusively by certain SQL operators to specify the query to perform on the JSON input. Although JSON path expressions are embedded in a SQL query, their syntax significantly differs from SQL. The semantics of predicates, operators, etc. in JSON path expressions generally follow the semantics of SQL. The JSON path language is case-sensitive for keywords and identifiers.

### JSON path syntax and semantics#

A JSON path expression, similar to a SQL expression, is a recursive structure. Although the name “path” suggests a linear sequence of operations going step by step deeper into the JSON structure, a JSON path expression is in fact a tree. It can access the input JSON item multiple times, in multiple ways, and combine the results. Moreover, the result of a JSON path expression is not a single item, but an ordered sequence of items. Each of the sub-expressions takes one or more input sequences, and returns a sequence as the result.

Note

In the lax mode, most path operations first unnest all JSON arrays in the input sequence. Any divergence from this rule is mentioned in the following listing. Path modes are explained in JSON path modes.

The JSON path language features are divided into: literals, variables, arithmetic binary expressions, arithmetic unary expressions, and a group of operators collectively known as accessors.

#### literals#

• numeric literals

They include exact and approximate numbers, and are interpreted as if they were SQL values.

-1, 1.2e3, NaN

• string literals

They are enclosed in double quotes.

"Some text"

• boolean literals

true, false

• null literal

It has the semantics of the JSON null, not of SQL null. See Comparison rules.

null


#### variables#

• context variable

It refers to the currently processed input of the JSON function.

$ • named variable It refers to a named parameter by its name. $param

• current item variable

It is used inside the filter expression to refer to the currently processed item from the input sequence.

@

• last subscript variable

It refers to the last index of the innermost enclosing array. Array indexes in JSON path expressions are zero-based.

last


#### arithmetic binary expressions#

The JSON path language supports five arithmetic binary operators:

<path1> + <path2>
<path1> - <path2>
<path1> * <path2>
<path1> / <path2>
<path1> % <path2>


Both operands, <path1> and <path2>, are evaluated to sequences of items. For arithmetic binary operators, each input sequence must contain a single numeric item. The arithmetic operation is performed according to SQL semantics, and it returns a sequence containing a single element with the result.

The operators follow the same precedence rules as in SQL arithmetic operations, and parentheses can be used for grouping.

#### arithmetic unary expressions#

+ <path>
- <path>


The operand <path> is evaluated to a sequence of items. Every item must be a numeric value. The unary plus or minus is applied to every item in the sequence, following SQL semantics, and the results form the returned sequence.

#### member accessor#

The member accessor returns the value of the member with the specified key for each JSON object in the input sequence.

<path>.key
<path>."key"


The condition when a JSON object does not have such a member is called a structural error. In the lax mode, it is suppressed, and the faulty object is excluded from the result.

Let <path> return a sequence of three JSON objects:

{"customer" : 100, "region" : "AFRICA"},
{"region" : "ASIA"},
{"customer" : 300, "region" : "AFRICA", "comment" : null}


the expression <path>.customer succeeds in the first and the third object, but the second object lacks the required member. In strict mode, path evaluation fails. In lax mode, the second object is silently skipped, and the resulting sequence is 100, 300.

All items in the input sequence must be JSON objects.

Note

Trino does not support JSON objects with duplicate keys.

#### wildcard member accessor#

Returns values from all key-value pairs for each JSON object in the input sequence. All the partial results are concatenated into the returned sequence.

<path>.*


Let <path> return a sequence of three JSON objects:

{"customer" : 100, "region" : "AFRICA"},
{"region" : "ASIA"},
{"customer" : 300, "region" : "AFRICA", "comment" : null}


The results is:

100, "AFRICA", "ASIA", 300, "AFRICA", null


All items in the input sequence must be JSON objects.

The order of values returned from a single JSON object is arbitrary. The sub-sequences from all JSON objects are concatenated in the same order in which the JSON objects appear in the input sequence.

#### array accessor#

Returns the elements at the specified indexes for each JSON array in the input sequence. Indexes are zero-based.

<path>[ <subscripts> ]


The <subscripts> list contains one or more subscripts. Each subscript specifies a single index or a range (ends inclusive):

<path>[<path1>, <path2> to <path3>, <path4>,...]


In lax mode, any non-array items resulting from the evaluation of the input sequence are wrapped into single-element arrays. Note that this is an exception to the rule of automatic array wrapping.

Each array in the input sequence is processed in the following way:

• The variable last is set to the last index of the array.

• All subscript indexes are computed in order of declaration. For a singleton subscript <path1>, the result must be a singleton numeric item. For a range subscript <path2> to <path3>, two numeric items are expected.

• The specified array elements are added in order to the output sequence.

Let <path> return a sequence of three JSON arrays:

[0, 1, 2], ["a", "b", "c", "d"], [null, null]


The following expression returns a sequence containing the last element from every array:

<path>[last] --> 2, "d", null


The following expression returns the third and fourth element from every array:

<path>[2 to 3] --> 2, "c", "d"


Note that the first array does not have the fourth element, and the last array does not have the third or fourth element. Accessing non-existent elements is a structural error. In strict mode, it causes the path expression to fail. In lax mode, such errors are suppressed, and only the existing elements are returned.

Another example of a structural error is an improper range specification such as 5 to 3.

Note that the subscripts may overlap, and they do not need to follow the element order. The order in the returned sequence follows the subscripts:

<path>[1, 0, 0] --> 1, 0, 0, "b", "a", "a", null, null, null


#### wildcard array accessor#

Returns all elements of each JSON array in the input sequence.

<path>[*]


In lax mode, any non-array items resulting from the evaluation of the input sequence are wrapped into single-element arrays. Note that this is an exception to the rule of automatic array wrapping.

The output order follows the order of the original JSON arrays. Also, the order of elements within the arrays is preserved.

Let <path> return a sequence of three JSON arrays:

[0, 1, 2], ["a", "b", "c", "d"], [null, null]
<path>[*] --> 0, 1, 2, "a", "b", "c", "d", null, null


#### filter#

Retrieves the items from the input sequence which satisfy the predicate.

<path>?( <predicate> )


JSON path predicates are syntactically similar to boolean expressions in SQL. However, the semantics are different in many aspects:

• They operate on sequences of items.

• They have their own error handling (they never fail).

• They behave different depending on the lax or strict mode.

The predicate evaluates to true, false, or unknown. Note that some predicate expressions involve nested JSON path expression. When evaluating the nested path, the variable @ refers to the currently examined item from the input sequence.

The following predicate expressions are supported:

• Conjunction

<predicate1> && <predicate2>

• Disjunction

<predicate1> || <predicate2>

• Negation

! <predicate>

• exists predicate

exists( <path> )


Returns true if the nested path evaluates to a non-empty sequence, and false when the nested path evaluates to an empty sequence. If the path evaluation throws an error, returns unknown.

• starts with predicate

<path> starts with "Some text"
<path> starts with $variable  The nested <path> must evaluate to a sequence of textual items, and the other operand must evaluate to a single textual item. If evaluating of either operand throws an error, the result is unknown. All items from the sequence are checked for starting with the right operand. The result is true if a match is found, otherwise false. However, if any of the comparisons throws an error, the result in the strict mode is unknown. The result in the lax mode depends on whether the match or the error was found first. • is unknown predicate ( <predicate> ) is unknown  Returns true if the nested predicate evaluates to unknown, and false otherwise. • Comparisons <path1> == <path2> <path1> <> <path2> <path1> != <path2> <path1> < <path2> <path1> > <path2> <path1> <= <path2> <path1> >= <path2>  Both operands of a comparison evaluate to sequences of items. If either evaluation throws an error, the result is unknown. Items from the left and right sequence are then compared pairwise. Similarly to the starts with predicate, the result is true if any of the comparisons returns true, otherwise false. However, if any of the comparisons throws an error, for example because the compared types are not compatible, the result in the strict mode is unknown. The result in the lax mode depends on whether the true comparison or the error was found first. ##### Comparison rules# Null values in the context of comparison behave different than SQL null: • null == null –> true • null != null, null < null, … –> false • null compared to a scalar value –> false • null compared to a JSON array or a JSON object –> false When comparing two scalar values, true or false is returned if the comparison is successfully performed. The semantics of the comparison is the same as in SQL. In case of an error, e.g. comparing text and number, unknown is returned. Comparing a scalar value with a JSON array or a JSON object, and comparing JSON arrays/objects is an error, so unknown is returned. ##### Examples of filter# Let <path> return a sequence of three JSON objects: {"customer" : 100, "region" : "AFRICA"}, {"region" : "ASIA"}, {"customer" : 300, "region" : "AFRICA", "comment" : null}  <path>?(@.region != "ASIA") --> {"customer" : 100, "region" : "AFRICA"}, {"customer" : 300, "region" : "AFRICA", "comment" : null} <path>?(!exists(@.customer)) --> {"region" : "ASIA"}  The following accessors are collectively referred to as item methods. #### double()# Converts numeric or text values into double values. <path>.double()  Let <path> return a sequence -1, 23e4, "5.6": <path>.double() --> -1e0, 23e4, 5.6e0  #### ceiling(), floor(), and abs()# Gets the ceiling, the floor or the absolute value for every numeric item in the sequence. The semantics of the operations is the same as in SQL. Let <path> return a sequence -1.5, -1, 1.3: <path>.ceiling() --> -1.0, -1, 2.0 <path>.floor() --> -2.0, -1, 1.0 <path>.abs() --> 1.5, 1, 1.3  #### keyvalue()# Returns a collection of JSON objects including one object per every member of the original object for every JSON object in the sequence. <path>.keyvalue()  The returned objects have three members: • “name”, which is the original key, • “value”, which is the original bound value, • “id”, which is the unique number, specific to an input object. Let <path> be a sequence of three JSON objects: {"customer" : 100, "region" : "AFRICA"}, {"region" : "ASIA"}, {"customer" : 300, "region" : "AFRICA", "comment" : null}  <path>.keyvalue() --> {"name" : "customer", "value" : 100, "id" : 0}, {"name" : "region", "value" : "AFRICA", "id" : 0}, {"name" : "region", "value" : "ASIA", "id" : 1}, {"name" : "customer", "value" : 300, "id" : 2}, {"name" : "region", "value" : "AFRICA", "id" : 2}, {"name" : "comment", "value" : null, "id" : 2}  It is required that all items in the input sequence are JSON objects. The order of the returned values follows the order of the original JSON objects. However, within objects, the order of returned entries is arbitrary. #### type()# Returns a textual value containing the type name for every item in the sequence. <path>.type()  This method does not perform array unwrapping in the lax mode. The returned values are: • "null" for JSON null, • "number" for a numeric item, • "string" for a textual item, • "boolean" for a boolean item, • "date" for an item of type date, • "time without time zone" for an item of type time, • "time with time zone" for an item of type time with time zone, • "timestamp without time zone" for an item of type timestamp, • "timestamp with time zone" for an item of type timestamp with time zone, • "array" for JSON array, • "object" for JSON object, #### size()# Returns a numeric value containing the size for every JSON array in the sequence. <path>.size()  This method does not perform array unwrapping in the lax mode. Instead, all non-array items are wrapped in singleton JSON arrays, so their size is 1. It is required that all items in the input sequence are JSON arrays. Let <path> return a sequence of three JSON arrays: [0, 1, 2], ["a", "b", "c", "d"], [null, null] <path>.size() --> 3, 4, 2  ### Limitations# The SQL standard describes the datetime() JSON path item method and the like_regex() JSON path predicate. Trino does not support them. ### JSON path modes# The JSON path expression can be evaluated in two modes: strict and lax. In the strict mode, it is required that the input JSON data strictly fits the schema required by the path expression. In the lax mode, the input JSON data can diverge from the expected schema. The following table shows the differences between the two modes. Condition strict mode lax mode Performing an operation which requires a non-array on an array, e.g.: $.key requires a JSON object

$.floor() requires a numeric value ERROR The array is automatically unnested, and the operation is performed on each array element. Performing an operation which requires an array on an non-array, e.g.: $[0], $[*], $.size()

ERROR

The non-array item is automatically wrapped in a singleton array, and the operation is performed on the array.

A structural error: accessing a non-existent element of an array or a non-existent member of a JSON object, e.g.:

$[-1] (array index out of bounds) $.key, where the input JSON object does not have a member key

ERROR

The error is suppressed, and the operation results in an empty sequence.

#### Examples of the lax mode behavior#

Let <path> return a sequence of three items, a JSON array, a JSON object, and a scalar numeric value:

[1, "a", null], {"key1" : 1.0, "key2" : true}, -2e3


The following example shows the wildcard array accessor in the lax mode. The JSON array returns all its elements, while the JSON object and the number are wrapped in singleton arrays and then unnested, so effectively they appear unchanged in the output sequence:

<path>[*] --> 1, "a", null, {"key1" : 1.0, "key2" : true}, -2e3


When calling the size() method, the JSON object and the number are also wrapped in singleton arrays:

<path>.size() --> 3, 1, 1


In some cases, the lax mode cannot prevent failure. In the following example, even though the JSON array is unwrapped prior to calling the floor() method, the item "a" causes type mismatch.

<path>.floor() --> ERROR


## json_exists#

The json_exists function determines whether a JSON value satisfies a JSON path specification.

JSON_EXISTS(
json_input [ FORMAT JSON [ ENCODING { UTF8 | UTF16 | UTF32 } ] ],
json_path
[ PASSING json_argument [, ...] ]
[ { TRUE | FALSE | UNKNOWN | ERROR } ON ERROR ]
)


The json_path is evaluated using the json_input as the context variable ($), and the passed arguments as the named variables ($variable_name). The returned value is true if the path returns a non-empty sequence, and false if the path returns an empty sequence. If an error occurs, the returned value depends on the ON ERROR clause. The default value returned ON ERROR is FALSE. The ON ERROR clause is applied for the following kinds of errors:

• Input conversion errors, such as malformed JSON

• JSON path evaluation errors, e.g. division by zero

json_input is a character string or a binary string. It should contain a single JSON item. For a binary string, you can specify encoding.

json_path is a string literal, containing the path mode specification, and the path expression, following the syntax rules described in JSON path syntax and semantics.

'strict ($.price +$.tax)?(@ > 99.9)'
'lax $[0 to 1].floor()?(@ > 10)'  In the PASSING clause you can pass arbitrary expressions to be used by the path expression. PASSING orders.totalprice AS O_PRICE, orders.tax % 10 AS O_TAX  The passed parameters can be referenced in the path expression by named variables, prefixed with $.

'lax $?(@.price >$O_PRICE || @.tax > $O_TAX)'  Additionally to SQL values, you can pass JSON values, specifying the format and optional encoding: PASSING orders.json_desc FORMAT JSON AS o_desc, orders.binary_record FORMAT JSON ENCODING UTF16 AS o_rec  Note that the JSON path language is case-sensitive, while the unquoted SQL identifiers are upper-cased. Therefore, it is recommended to use quoted identifiers in the PASSING clause: 'lax$.$KeyName' PASSING nation.name AS KeyName --> ERROR; no passed value found 'lax$.$KeyName' PASSING nation.name AS "KeyName" --> correct  ### Examples# Let customers be a table containing two columns: id:bigint, description:varchar. id description 101 ‘{“comment” : “nice”, “children” : [10, 13, 16]}’ 102 ‘{“comment” : “problematic”, “children” : [8, 11]}’ 103 ‘{“comment” : “knows best”, “children” : [2]}’ The following query checks which customers have children above the age of 10: SELECT id, json_exists( description, 'lax$.children[*]?(@ > 10)'
) AS children_above_ten
FROM customers


id

children_above_ten

101

true

102

true

103

false

In the following query, the path mode is strict. We check the third child for each customer. This should cause a structural error for the customers who do not have three or more children. This error is handled according to the ON ERROR clause.

SELECT
id,
json_exists(
description,
'strict $.children[2]?(@ > 10)' UNKNOWN ON ERROR ) AS child_3_above_ten FROM customers  id child_3_above_ten 101 true 102 NULL 103 NULL ## json_query# The json_query function extracts a JSON value from a JSON value. JSON_QUERY( json_input [ FORMAT JSON [ ENCODING { UTF8 | UTF16 | UTF32 } ] ], json_path [ PASSING json_argument [, ...] ] [ RETURNING type [ FORMAT JSON [ ENCODING { UTF8 | UTF16 | UTF32 } ] ] ] [ WITHOUT [ ARRAY ] WRAPPER | WITH [ { CONDITIONAL | UNCONDITIONAL } ] [ ARRAY ] WRAPPER ] [ { KEEP | OMIT } QUOTES [ ON SCALAR STRING ] ] [ { ERROR | NULL | EMPTY ARRAY | EMPTY OBJECT } ON EMPTY ] [ { ERROR | NULL | EMPTY ARRAY | EMPTY OBJECT } ON ERROR ] )  The json_path is evaluated using the json_input as the context variable ($), and the passed arguments as the named variables ($variable_name). The returned value is a JSON item returned by the path. By default, it is represented as a character string (varchar). In the RETURNING clause, you can specify other character string type or varbinary. With varbinary, you can also specify the desired encoding. json_input is a character string or a binary string. It should contain a single JSON item. For a binary string, you can specify encoding. json_path is a string literal, containing the path mode specification, and the path expression, following the syntax rules described in JSON path syntax and semantics. 'strict$.keyvalue()?(@.name == $cust_id)' 'lax$[5 to last]'


In the PASSING clause you can pass arbitrary expressions to be used by the path expression.

PASSING orders.custkey AS CUST_ID


The passed parameters can be referenced in the path expression by named variables, prefixed with $. 'strict$.keyvalue()?(@.value == $CUST_ID)'  Additionally to SQL values, you can pass JSON values, specifying the format and optional encoding: PASSING orders.json_desc FORMAT JSON AS o_desc, orders.binary_record FORMAT JSON ENCODING UTF16 AS o_rec  Note that the JSON path language is case-sensitive, while the unquoted SQL identifiers are upper-cased. Therefore, it is recommended to use quoted identifiers in the PASSING clause: 'lax$.$KeyName' PASSING nation.name AS KeyName --> ERROR; no passed value found 'lax$.$KeyName' PASSING nation.name AS "KeyName" --> correct  The ARRAY WRAPPER clause lets you modify the output by wrapping the results in a JSON array. WITHOUT ARRAY WRAPPER is the default option. WITH CONDITIONAL ARRAY WRAPPER wraps every result which is not a singleton JSON array or JSON object. WITH UNCONDITIONAL ARRAY WRAPPER wraps every result. The QUOTES clause lets you modify the result for a scalar string by removing the double quotes being part of the JSON string representation. ### Examples# Let customers be a table containing two columns: id:bigint, description:varchar. id description 101 ‘{“comment” : “nice”, “children” : [10, 13, 16]}’ 102 ‘{“comment” : “problematic”, “children” : [8, 11]}’ 103 ‘{“comment” : “knows best”, “children” : [2]}’ The following query gets the children array for each customer: SELECT id, json_query( description, 'lax$.children'
) AS children
FROM customers


id

children

101

‘[10,13,16]’

102

‘[8,11]’

103

‘[2]’

The following query gets the collection of children for each customer. Note that the json_query function can only output a single JSON item. If you don’t use array wrapper, you get an error for every customer with multiple children. The error is handled according to the ON ERROR clause.

SELECT
id,
json_query(
description,
'lax $.children[*]' WITHOUT ARRAY WRAPPER NULL ON ERROR ) AS children FROM customers  id children 101 NULL 102 NULL 103 ‘2’ The following query gets the last child for each customer, wrapped in a JSON array: SELECT id, json_query( description, 'lax$.children[last]'
WITH ARRAY WRAPPER
) AS last_child
FROM customers


id

last_child

101

‘[16]’

102

‘[11]’

103

‘[2]’

The following query gets all children above the age of 12 for each customer, wrapped in a JSON array. The second and the third customer don’t have children of this age. Such case is handled according to the ON EMPTY clause. The default value returned ON EMPTY is NULL. In the following example, EMPTY ARRAY ON EMPTY is specified.

SELECT
id,
json_query(
description,
'strict $.children[*]?(@ > 12)' WITH ARRAY WRAPPER EMPTY ARRAY ON EMPTY ) AS children FROM customers  id children 101 ‘[13,16]’ 102 ‘[]’ 103 ‘[]’ The following query shows the result of the QUOTES clause. Note that KEEP QUOTES is the default. SELECT id, json_query(description, 'strict$.comment' KEEP QUOTES) AS quoted_comment,
json_query(description, 'strict $.comment' OMIT QUOTES) AS unquoted_comment FROM customers  id quoted_comment unquoted_comment 101 ‘“nice”’ ‘nice’ 102 ‘“problematic”’ ‘problematic’ 103 ‘“knows best”’ ‘knows best’ If an error occurs, the returned value depends on the ON ERROR clause. The default value returned ON ERROR is NULL. One example of error is multiple items returned by the path. Other errors caught and handled according to the ON ERROR clause are: • Input conversion errors, such as malformed JSON • JSON path evaluation errors, e.g. division by zero • Output conversion errors ## json_value# The json_value function extracts an SQL scalar from a JSON value. JSON_VALUE( json_input [ FORMAT JSON [ ENCODING { UTF8 | UTF16 | UTF32 } ] ], json_path [ PASSING json_argument [, ...] ] [ RETURNING type ] [ { ERROR | NULL | DEFAULT expression } ON EMPTY ] [ { ERROR | NULL | DEFAULT expression } ON ERROR ] )  The json_path is evaluated using the json_input as the context variable ($), and the passed arguments as the named variables ($variable_name). The returned value is the SQL scalar returned by the path. By default, it is converted to string (varchar). In the RETURNING clause, you can specify other desired type: a character string type, numeric, boolean or datetime type. json_input is a character string or a binary string. It should contain a single JSON item. For a binary string, you can specify encoding. json_path is a string literal, containing the path mode specification, and the path expression, following the syntax rules described in JSON path syntax and semantics. 'strict$.price + $tax' 'lax$[last].abs().floor()'


In the PASSING clause you can pass arbitrary expressions to be used by the path expression.

PASSING orders.tax AS O_TAX


The passed parameters can be referenced in the path expression by named variables, prefixed with $. 'strict$[last].price + $O_TAX'  Additionally to SQL values, you can pass JSON values, specifying the format and optional encoding: PASSING orders.json_desc FORMAT JSON AS o_desc, orders.binary_record FORMAT JSON ENCODING UTF16 AS o_rec  Note that the JSON path language is case-sensitive, while the unquoted SQL identifiers are upper-cased. Therefore, it is recommended to use quoted identifiers in the PASSING clause: 'lax$.$KeyName' PASSING nation.name AS KeyName --> ERROR; no passed value found 'lax$.$KeyName' PASSING nation.name AS "KeyName" --> correct  If the path returns an empty sequence, the ON EMPTY clause is applied. The default value returned ON EMPTY is NULL. You can also specify the default value: DEFAULT -1 ON EMPTY  If an error occurs, the returned value depends on the ON ERROR clause. The default value returned ON ERROR is NULL. One example of error is multiple items returned by the path. Other errors caught and handled according to the ON ERROR clause are: • Input conversion errors, such as malformed JSON • JSON path evaluation errors, e.g. division by zero • Returned scalar not convertible to the desired type ### Examples# Let customers be a table containing two columns: id:bigint, description:varchar. id description 101 ‘{“comment” : “nice”, “children” : [10, 13, 16]}’ 102 ‘{“comment” : “problematic”, “children” : [8, 11]}’ 103 ‘{“comment” : “knows best”, “children” : [2]}’ The following query gets the comment for each customer as char(12): SELECT id, json_value( description, 'lax$.comment'
RETURNING char(12)
) AS comment
FROM customers


id

comment

101

‘nice ‘

102

‘problematic ‘

103

‘knows best ‘

The following query gets the first child’s age for each customer as tinyint:

SELECT id, json_value(
description,
'lax $.children[0]' RETURNING tinyint ) AS child FROM customers  id child 101 10 102 8 103 2 The following query gets the third child’s age for each customer. In the strict mode, this should cause a structural error for the customers who do not have the third child. This error is handled according to the ON ERROR clause. SELECT id, json_value( description, 'strict$.children[2]'
DEFAULT 'err' ON ERROR
) AS child
FROM customers


id

child

101

‘16’

102

‘err’

103

‘err’

After changing the mode to lax, the structural error is suppressed, and the customers without a third child produce empty sequence. This case is handled according to the ON EMPTY clause.

SELECT id, json_value(
description,
'lax $.children[2]' DEFAULT 'missing' ON EMPTY ) AS child FROM customers  id child 101 ‘16’ 102 ‘missing’ 103 ‘missing’ ## json_array# The json_array function creates a JSON array containing given elements. JSON_ARRAY( [ array_element [, ...] [ { NULL ON NULL | ABSENT ON NULL } ] ], [ RETURNING type [ FORMAT JSON [ ENCODING { UTF8 | UTF16 | UTF32 } ] ] ] )  ### Argument types# The array elements can be arbitrary expressions. Each passed value is converted into a JSON item according to its type, and optional FORMAT and ENCODING specification. You can pass SQL values of types boolean, numeric, and character string. They are converted to corresponding JSON literals: SELECT json_array(true, 12e-1, 'text') --> '[true,1.2,"text"]'  Additionally to SQL values, you can pass JSON values. They are character or binary strings with a specified format and optional encoding: SELECT json_array( '[ "text" ] ' FORMAT JSON, X'5B0035005D00' FORMAT JSON ENCODING UTF16 ) --> '[["text"],[5]]'  You can also nest other JSON-returning functions. In that case, the FORMAT option is implicit: SELECT json_array( json_query('{"key" : [ "value" ]}', 'lax$.key')
)
--> '[["value"]]'


Other passed values are cast to varchar, and they become JSON text literals:

SELECT json_array(
DATE '2001-01-31',
UUID '12151fd2-7586-11e9-8f9e-2a86e4085a59'
)
--> '["2001-01-31","12151fd2-7586-11e9-8f9e-2a86e4085a59"]'


You can omit the arguments altogether to get an empty array:

SELECT json_array() --> '[]'


### Null handling#

If a value passed for an array element is null, it is treated according to the specified null treatment option. If ABSENT ON NULL is specified, the null element is omitted in the result. If NULL ON NULL is specified, JSON null is added to the result. ABSENT ON NULL is the default configuration:

SELECT json_array(true, null, 1)
--> '[true,1]'

SELECT json_array(true, null, 1 ABSENT ON NULL)
--> '[true,1]'

SELECT json_array(true, null, 1 NULL ON NULL)
--> '[true,null,1]'


### Returned type#

The SQL standard imposes that there is no dedicated data type to represent JSON data in SQL. Instead, JSON data is represented as character or binary strings. By default, the json_array function returns varchar containing the textual representation of the JSON array. With the RETURNING clause, you can specify other character string type:

SELECT json_array(true, 1 RETURNING VARCHAR(100))
--> '[true,1]'


You can also specify to use varbinary and the required encoding as return type. The default encoding is UTF8:

SELECT json_array(true, 1 RETURNING VARBINARY)
--> X'5b 74 72 75 65 2c 31 5d'

SELECT json_array(true, 1 RETURNING VARBINARY FORMAT JSON ENCODING UTF8)
--> X'5b 74 72 75 65 2c 31 5d'

SELECT json_array(true, 1 RETURNING VARBINARY FORMAT JSON ENCODING UTF16)
--> X'5b 00 74 00 72 00 75 00 65 00 2c 00 31 00 5d 00'

SELECT json_array(true, 1 RETURNING VARBINARY FORMAT JSON ENCODING UTF32)
--> X'5b 00 00 00 74 00 00 00 72 00 00 00 75 00 00 00 65 00 00 00 2c 00 00 00 31 00 00 00 5d 00 00 00'


## json_object#

The json_object function creates a JSON object containing given key-value pairs.

JSON_OBJECT(
[ key_value [, ...]
[ { NULL ON NULL | ABSENT ON NULL } ] ],
[ { WITH UNIQUE [ KEYS ] | WITHOUT UNIQUE [ KEYS ] } ]
[ RETURNING type [ FORMAT JSON [ ENCODING { UTF8 | UTF16 | UTF32 } ] ] ]
)


### Argument passing conventions#

There are two conventions for passing keys and values:

SELECT json_object('key1' : 1, 'key2' : true)
--> '{"key1":1,"key2":true}'

SELECT json_object(KEY 'key1' VALUE 1, KEY 'key2' VALUE true)
--> '{"key1":1,"key2":true}'


In the second convention, you can omit the KEY keyword:

SELECT json_object('key1' VALUE 1, 'key2' VALUE true)
--> '{"key1":1,"key2":true}'


### Argument types#

The keys can be arbitrary expressions. They must be of character string type. Each key is converted into a JSON text item, and it becomes a key in the created JSON object. Keys must not be null.

The values can be arbitrary expressions. Each passed value is converted into a JSON item according to its type, and optional FORMAT and ENCODING specification.

You can pass SQL values of types boolean, numeric, and character string. They are converted to corresponding JSON literals:

SELECT json_object('x' : true, 'y' : 12e-1, 'z' : 'text')
--> '{"x":true,"y":1.2,"z":"text"}'


Additionally to SQL values, you can pass JSON values. They are character or binary strings with a specified format and optional encoding:

SELECT json_object(
'x' : '[  "text"  ] ' FORMAT JSON,
'y' : X'5B0035005D00' FORMAT JSON ENCODING UTF16
)
--> '{"x":["text"],"y":[5]}'


You can also nest other JSON-returning functions. In that case, the FORMAT option is implicit:

SELECT json_object(
'x' : json_query('{"key" : [  "value"  ]}', 'lax $.key') ) --> '{"x":["value"]}'  Other passed values are cast to varchar, and they become JSON text literals: SELECT json_object( 'x' : DATE '2001-01-31', 'y' : UUID '12151fd2-7586-11e9-8f9e-2a86e4085a59' ) --> '{"x":"2001-01-31","y":"12151fd2-7586-11e9-8f9e-2a86e4085a59"}'  You can omit the arguments altogether to get an empty object: SELECT json_object() --> '{}'  ### Null handling# The values passed for JSON object keys must not be null. It is allowed to pass null for JSON object values. A null value is treated according to the specified null treatment option. If NULL ON NULL is specified, a JSON object entry with null value is added to the result. If ABSENT ON NULL is specified, the entry is omitted in the result. NULL ON NULL is the default configuration.: SELECT json_object('x' : null, 'y' : 1) --> '{"x":null,"y":1}' SELECT json_object('x' : null, 'y' : 1 NULL ON NULL) --> '{"x":null,"y":1}' SELECT json_object('x' : null, 'y' : 1 ABSENT ON NULL) --> '{"y":1}'  ### Key uniqueness# If a duplicate key is encountered, it is handled according to the specified key uniqueness constraint. If WITH UNIQUE KEYS is specified, a duplicate key results in a query failure: SELECT json_object('x' : null, 'x' : 1 WITH UNIQUE KEYS) --> failure: "duplicate key passed to JSON_OBJECT function"  Note that this option is not supported if any of the arguments has a FORMAT specification. If WITHOUT UNIQUE KEYS is specified, duplicate keys are not supported due to implementation limitation. WITHOUT UNIQUE KEYS is the default configuration. ### Returned type# The SQL standard imposes that there is no dedicated data type to represent JSON data in SQL. Instead, JSON data is represented as character or binary strings. By default, the json_object function returns varchar containing the textual representation of the JSON object. With the RETURNING clause, you can specify other character string type: SELECT json_object('x' : 1 RETURNING VARCHAR(100)) --> '{"x":1}'  You can also specify to use varbinary and the required encoding as return type. The default encoding is UTF8: SELECT json_object('x' : 1 RETURNING VARBINARY) --> X'7b 22 78 22 3a 31 7d' SELECT json_object('x' : 1 RETURNING VARBINARY FORMAT JSON ENCODING UTF8) --> X'7b 22 78 22 3a 31 7d' SELECT json_object('x' : 1 RETURNING VARBINARY FORMAT JSON ENCODING UTF16) --> X'7b 00 22 00 78 00 22 00 3a 00 31 00 7d 00' SELECT json_object('x' : 1 RETURNING VARBINARY FORMAT JSON ENCODING UTF32) --> X'7b 00 00 00 22 00 00 00 78 00 00 00 22 00 00 00 3a 00 00 00 31 00 00 00 7d 00 00 00'  Warning The following functions and operators are not compliant with the SQL standard, and should be considered deprecated. According to the SQL standard, there shall be no JSON data type. Instead, JSON values should be represented as string values. The remaining functionality of the following functions is covered by the functions described previously. ## Cast to JSON# The following types can be cast to JSON: • BOOLEAN • TINYINT • SMALLINT • INTEGER • BIGINT • REAL • DOUBLE • VARCHAR Additionally, ARRAY, MAP, and ROW types can be cast to JSON when the following requirements are met: • ARRAY types can be cast when the element type of the array is one of the supported types. • MAP types can be cast when the key type of the map is VARCHAR and the value type of the map is a supported type, • ROW types can be cast when every field type of the row is a supported type. Note Cast operations with supported character string types treat the input as a string, not validated as JSON. This means that a cast operation with a string-type input of invalid JSON results in a succesful cast to invalid JSON. Instead, consider using the json_parse() function to create validated JSON from a string. The following examples show the behavior of casting to JSON with these types: SELECT CAST(NULL AS JSON); -- NULL SELECT CAST(1 AS JSON); -- JSON '1' SELECT CAST(9223372036854775807 AS JSON); -- JSON '9223372036854775807' SELECT CAST('abc' AS JSON); -- JSON '"abc"' SELECT CAST(true AS JSON); -- JSON 'true' SELECT CAST(1.234 AS JSON); -- JSON '1.234' SELECT CAST(ARRAY[1, 23, 456] AS JSON); -- JSON '[1,23,456]' SELECT CAST(ARRAY[1, NULL, 456] AS JSON); -- JSON '[1,null,456]' SELECT CAST(ARRAY[ARRAY[1, 23], ARRAY[456]] AS JSON); -- JSON '[[1,23],[456]]' SELECT CAST(MAP(ARRAY['k1', 'k2', 'k3'], ARRAY[1, 23, 456]) AS JSON); -- JSON '{"k1":1,"k2":23,"k3":456}' SELECT CAST(CAST(ROW(123, 'abc', true) AS ROW(v1 BIGINT, v2 VARCHAR, v3 BOOLEAN)) AS JSON); -- JSON '{"v1":123,"v2":"abc","v3":true}'  Casting from NULL to JSON is not straightforward. Casting from a standalone NULL will produce a SQL NULL instead of JSON 'null'. However, when casting from arrays or map containing NULLs, the produced JSON will have nulls in it. ## Cast from JSON# Casting to BOOLEAN, TINYINT, SMALLINT, INTEGER, BIGINT, REAL, DOUBLE or VARCHAR is supported. Casting to ARRAY and MAP is supported when the element type of the array is one of the supported types, or when the key type of the map is VARCHAR and value type of the map is one of the supported types. Behaviors of the casts are shown with the examples below: SELECT CAST(JSON 'null' AS VARCHAR); -- NULL SELECT CAST(JSON '1' AS INTEGER); -- 1 SELECT CAST(JSON '9223372036854775807' AS BIGINT); -- 9223372036854775807 SELECT CAST(JSON '"abc"' AS VARCHAR); -- abc SELECT CAST(JSON 'true' AS BOOLEAN); -- true SELECT CAST(JSON '1.234' AS DOUBLE); -- 1.234 SELECT CAST(JSON '[1,23,456]' AS ARRAY(INTEGER)); -- [1, 23, 456] SELECT CAST(JSON '[1,null,456]' AS ARRAY(INTEGER)); -- [1, NULL, 456] SELECT CAST(JSON '[[1,23],[456]]' AS ARRAY(ARRAY(INTEGER))); -- [[1, 23], [456]] SELECT CAST(JSON '{"k1":1,"k2":23,"k3":456}' AS MAP(VARCHAR, INTEGER)); -- {k1=1, k2=23, k3=456} SELECT CAST(JSON '{"v1":123,"v2":"abc","v3":true}' AS ROW(v1 BIGINT, v2 VARCHAR, v3 BOOLEAN)); -- {v1=123, v2=abc, v3=true} SELECT CAST(JSON '[123,"abc",true]' AS ROW(v1 BIGINT, v2 VARCHAR, v3 BOOLEAN)); -- {v1=123, v2=abc, v3=true}  JSON arrays can have mixed element types and JSON maps can have mixed value types. This makes it impossible to cast them to SQL arrays and maps in some cases. To address this, Trino supports partial casting of arrays and maps: SELECT CAST(JSON '[[1, 23], 456]' AS ARRAY(JSON)); -- [JSON '[1,23]', JSON '456'] SELECT CAST(JSON '{"k1": [1, 23], "k2": 456}' AS MAP(VARCHAR, JSON)); -- {k1 = JSON '[1,23]', k2 = JSON '456'} SELECT CAST(JSON '[null]' AS ARRAY(JSON)); -- [JSON 'null']  When casting from JSON to ROW, both JSON array and JSON object are supported. ## JSON functions# is_json_scalar(json) → boolean# Determine if json is a scalar (i.e. a JSON number, a JSON string, true, false or null): SELECT is_json_scalar('1'); -- true SELECT is_json_scalar('[1, 2, 3]'); -- false  json_array_contains(json, value) → boolean# Determine if value exists in json (a string containing a JSON array): SELECT json_array_contains('[1, 2, 3]', 2); -- true  json_array_get(json_array, index) → json# Warning The semantics of this function are broken. If the extracted element is a string, it will be converted into an invalid JSON value that is not properly quoted (the value will not be surrounded by quotes and any interior quotes will not be escaped). We recommend against using this function. It cannot be fixed without impacting existing usages and may be removed in a future release. Returns the element at the specified index into the json_array. The index is zero-based: SELECT json_array_get('["a", [3, 9], "c"]', 0); -- JSON 'a' (invalid JSON) SELECT json_array_get('["a", [3, 9], "c"]', 1); -- JSON '[3,9]'  This function also supports negative indexes for fetching element indexed from the end of an array: SELECT json_array_get('["c", [3, 9], "a"]', -1); -- JSON 'a' (invalid JSON) SELECT json_array_get('["c", [3, 9], "a"]', -2); -- JSON '[3,9]'  If the element at the specified index doesn’t exist, the function returns null: SELECT json_array_get('[]', 0); -- NULL SELECT json_array_get('["a", "b", "c"]', 10); -- NULL SELECT json_array_get('["c", "b", "a"]', -10); -- NULL  json_array_length(json) → bigint# Returns the array length of json (a string containing a JSON array): SELECT json_array_length('[1, 2, 3]'); -- 3  json_extract(json, json_path) → json# Evaluates the JSONPath-like expression json_path on json (a string containing JSON) and returns the result as a JSON string: SELECT json_extract(json, '$.store.book');
SELECT json_extract(json, '$.store[book]'); SELECT json_extract(json, '$.store["book name"]');

json_extract_scalar(json, json_path) → varchar#

Like json_extract(), but returns the result value as a string (as opposed to being encoded as JSON). The value referenced by json_path must be a scalar (boolean, number or string).

SELECT json_extract_scalar('[1, 2, 3]', '$[2]'); SELECT json_extract_scalar(json, '$.store.book[0].author');

json_format(json) → varchar#

Returns the JSON text serialized from the input JSON value. This is inverse function to json_parse().

SELECT json_format(JSON '[1, 2, 3]'); -- '[1,2,3]'
SELECT json_format(JSON '"a"');       -- '"a"'


Note

json_format() and CAST(json AS VARCHAR) have completely different semantics.

json_format() serializes the input JSON value to JSON text conforming to RFC 7159. The JSON value can be a JSON object, a JSON array, a JSON string, a JSON number, true, false or null.

SELECT json_format(JSON '{"a": 1, "b": 2}'); -- '{"a":1,"b":2}'
SELECT json_format(JSON '[1, 2, 3]');        -- '[1,2,3]'
SELECT json_format(JSON '"abc"');            -- '"abc"'
SELECT json_format(JSON '42');               -- '42'
SELECT json_format(JSON 'true');             -- 'true'
SELECT json_format(JSON 'null');             -- 'null'


CAST(json AS VARCHAR) casts the JSON value to the corresponding SQL VARCHAR value. For JSON string, JSON number, true, false or null, the cast behavior is same as the corresponding SQL type. JSON object and JSON array cannot be cast to VARCHAR.

SELECT CAST(JSON '{"a": 1, "b": 2}' AS VARCHAR); -- ERROR!
SELECT CAST(JSON '[1, 2, 3]' AS VARCHAR);        -- ERROR!
SELECT CAST(JSON '"abc"' AS VARCHAR);            -- 'abc' (the double quote is gone)
SELECT CAST(JSON '42' AS VARCHAR);               -- '42'
SELECT CAST(JSON 'true' AS VARCHAR);             -- 'true'
SELECT CAST(JSON 'null' AS VARCHAR);             -- NULL

json_parse(string) → json#

Returns the JSON value deserialized from the input JSON text. This is inverse function to json_format():

SELECT json_parse('[1, 2, 3]');   -- JSON '[1,2,3]'
SELECT json_parse('"abc"');       -- JSON '"abc"'


Note

json_parse() and CAST(string AS JSON) have completely different semantics.

json_parse() expects a JSON text conforming to RFC 7159, and returns the JSON value deserialized from the JSON text. The JSON value can be a JSON object, a JSON array, a JSON string, a JSON number, true, false or null.

SELECT json_parse('not_json');         -- ERROR!
SELECT json_parse('["a": 1, "b": 2]'); -- JSON '["a": 1, "b": 2]'
SELECT json_parse('[1, 2, 3]');        -- JSON '[1,2,3]'
SELECT json_parse('"abc"');            -- JSON '"abc"'
SELECT json_parse('42');               -- JSON '42'
SELECT json_parse('true');             -- JSON 'true'
SELECT json_parse('null');             -- JSON 'null'


CAST(string AS JSON) takes any VARCHAR value as input, and returns a JSON string with its value set to input string.

SELECT CAST('not_json' AS JSON);         -- JSON '"not_json"'
SELECT CAST('["a": 1, "b": 2]' AS JSON); -- JSON '"[\"a\": 1, \"b\": 2]"'
SELECT CAST('[1, 2, 3]' AS JSON);        -- JSON '"[1, 2, 3]"'
SELECT CAST('"abc"' AS JSON);            -- JSON '"\"abc\""'
SELECT CAST('42' AS JSON);               -- JSON '"42"'
SELECT CAST('true' AS JSON);             -- JSON '"true"'
SELECT CAST('null' AS JSON);             -- JSON '"null"'

json_size(json, json_path) → bigint#

Like json_extract(), but returns the size of the value. For objects or arrays, the size is the number of members, and the size of a scalar value is zero.

SELECT json_size('{"x": {"a": 1, "b": 2}}', '$.x'); -- 2 SELECT json_size('{"x": [1, 2, 3]}', '$.x');          -- 3
SELECT json_size('{"x": {"a": 1, "b": 2}}', '\$.x.a'); -- 0