JSON Functions and Operators

Processing and Creating JSON Data

The SQL/JSON Path Language

This section describes:

  • functions and operators for processing and creating JSON data
  • the SQL/JSON path language

For details on JSON types supported in ProtonBase, see Section 7.10.

Processing and Creating JSON Data

Table 8.37 shows the operators that are available for use with JSON data types (see Section 7.10). In addition, the usual comparison operators shown in Table 8.1 are available for jsonb, though not for json. The comparison operators follow the ordering rules for B-tree operations outlined in Section 7.10.4.

Table json and jsonb Operators

Operator Description Example(s)

json -> integerjson

jsonb -> integerjsonb

Extracts n'th element of JSON array (array elements are indexed from zero, but negative integers count from the end).

'[{"a":"foo"},{"b":"bar"},{"c":"baz"}]'::json -> 2{"c":"baz"}

'[{"a":"foo"},{"b":"bar"},{"c":"baz"}]'::json -> -3{"a":"foo"}

json -> textjson

jsonb -> textjsonb

Extracts JSON object field with the given key.

'{"a": {"b":"foo"}}'::json -> 'a'{"b":"foo"}

json ->> integertext

jsonb ->> integertext

Extracts n'th element of JSON array, as text.

'[1,2,3]'::json ->> 23

json ->> texttext

jsonb ->> texttext

Extracts JSON object field with the given key, as text.

'{"a":1,"b":2}'::json ->> 'b'2

json #> text[]json

jsonb #> text[]jsonb

Extracts JSON sub-object at the specified path, where path elements can be either field keys or array indexes.

'{"a": {"b": ["foo","bar"]}}'::json #> '{a,b,1}'"bar"

json #>> text[]text

jsonb #>> text[]text

Extracts JSON sub-object at the specified path as text.

'{"a": {"b": ["foo","bar"]}}'::json #>> '{a,b,1}'bar

Some further operators exist only for jsonb, as shown in Table 8.38. Section 7.10.4 describes how these operators can be used to effectively search indexed jsonb data.

Table Additional jsonb Operators

Operator Description Example(s)

jsonb @> jsonbboolean

Does the first JSON value contain the second? (See Section 7.10.3 for details about containment.)

'{"a":1, "b":2}'::jsonb @> '{"b":2}'::jsonbt

jsonb <@ jsonbboolean

Is the first JSON value contained in the second?

'{"b":2}'::jsonb <@ '{"a":1, "b":2}'::jsonbt

jsonb ? textboolean

Does the text string exist as a top-level key or array element within the JSON value?

'{"a":1, "b":2}'::jsonb ? 'b't

'["a", "b", "c"]'::jsonb ? 'b't

jsonb ?| text[]boolean

Do any of the strings in the text array exist as top-level keys or array elements?

'{"a":1, "b":2, "c":3}'::jsonb ?| array['b', 'd']t

jsonb ?& text[]boolean

Do all of the strings in the text array exist as top-level keys or array elements?

'["a", "b", "c"]'::jsonb ?& array['a', 'b']t

jsonb || jsonbjsonb

Concatenates two jsonb values. Concatenating two arrays generates an array containing all the elements of each input. Concatenating two objects generates an object containing the union of their keys, taking the second object's value when there are duplicate keys. All other cases are treated by converting a non-array input into a single-element array, and then proceeding as for two arrays. Does not operate recursively: only the top-level array or object structure is merged.

'["a", "b"]'::jsonb || '["a", "d"]'::jsonb["a", "b", "a", "d"]

'{"a": "b"}'::jsonb || '{"c": "d"}'::jsonb{"a": "b", "c": "d"}

'[1, 2]'::jsonb || '3'::jsonb[1, 2, 3]

'{"a": "b"}'::jsonb || '42'::jsonb[{"a": "b"}, 42]

To append an array to another array as a single entry, wrap it in an additional layer of array, for example:

'[1, 2]'::jsonb || jsonb_build_array('[3, 4]'::jsonb)[1, 2, [3, 4]]

jsonb - textjsonb

Deletes a key (and its value) from a JSON object, or matching string value(s) from a JSON array.

'{"a": "b", "c": "d"}'::jsonb - 'a'{"c": "d"}

'["a", "b", "c", "b"]'::jsonb - 'b'["a", "c"]

jsonb - text[]jsonb

Deletes all matching keys or array elements from the left operand.

'{"a": "b", "c": "d"}'::jsonb - '{a,c}'::text[]{}

jsonb - integerjsonb

Deletes the array element with specified index (negative integers count from the end). Throws an error if JSON value is not an array.

'["a", "b"]'::jsonb - 1["a"]

jsonb #- text[]jsonb

Deletes the field or array element at the specified path, where path elements can be either field keys or array indexes.

'["a", {"b":1}]'::jsonb #- '{1,b}'["a", {}]

Table 8.39 shows the functions that are available for constructing json and jsonb values.

Table JSON Creation Functions

Function Description Example(s)

to_json ( anyelement ) → json

to_jsonb ( anyelement ) → jsonb

Converts any SQL value to json or jsonb. Arrays and composites are converted recursively to arrays and objects (multidimensional arrays become arrays of arrays in JSON). Otherwise, if there is a cast from the SQL data type to json, the cast function will be used to perform the conversion;[a] otherwise, a scalar JSON value is produced. For any scalar other than a number, a Boolean, or a null value, the text representation will be used, with escaping as necessary to make it a valid JSON string value.

to_json('Fred said "Hi."'::text)"Fred said \"Hi.\""

to_jsonb(row(42, 'Fred said "Hi."'::text)){"f1": 42, "f2": "Fred said \"Hi.\""}

row_to_json ( record [, boolean ] ) → json

Converts an SQL composite value to a JSON object. The behavior is the same as to_json except that line feeds will be added between top-level elements if the optional boolean parameter is true.

row_to_json(row(1,'foo')){"f1":1,"f2":"foo"}

json_build_array ( VARIADIC "any" ) → json

jsonb_build_array ( VARIADIC "any" ) → jsonb

Builds a possibly-heterogeneously-typed JSON array out of a variadic argument list. Each argument is converted as per to_json or to_jsonb.

json_build_array(1, 2, 'foo', 4, 5)[1, 2, "foo", 4, 5]

json_build_object ( VARIADIC "any" ) → json

jsonb_build_object ( VARIADIC "any" ) → jsonb

Builds a JSON object out of a variadic argument list. By convention, the argument list consists of alternating keys and values. Key arguments are coerced to text; value arguments are converted as per to_json or to_jsonb.

json_build_object('foo', 1, 2, row(3,'bar')){"foo" : 1, "2" : {"f1":3,"f2":"bar"}}

json_object ( keys text[], values text[] ) → json

jsonb_object ( keys text[], values text[] ) → jsonb

This form of json_object takes keys and values pairwise from separate text arrays. Otherwise it is identical to the one-argument form.

json_object('{a,b}', '{1,2}'){"a": "1", "b": "2"}

[a] For example, the "hstore" extension has a cast from hstore to json, so that hstore values converted via the JSON creation functions will be represented as JSON objects, not as primitive string values.

Table 8.40 shows the functions that are available for processing json and jsonb values.

Table JSON Processing Functions

Function Description Example(s)

json_array_elements ( json ) → setof json

jsonb_array_elements ( jsonb ) → setof jsonb

Expands the top-level JSON array into a set of JSON values.

select * from json_array_elements('[1,true, [2,false]]')

value
-----------
 1
 true
 [2,false]

json_array_elements_text ( json ) → setof text

jsonb_array_elements_text ( jsonb ) → setof text

Expands the top-level JSON array into a set of text values.

select * from json_array_elements_text('["foo", "bar"]')

value
-----------
 foo
 bar

json_array_length ( json ) → integer

jsonb_array_length ( jsonb ) → integer

Returns the number of elements in the top-level JSON array.

json_array_length('[1,2,3,{"f1":1,"f2":[5,6]},4]')5

json_extract_path ( from_json json, VARIADIC path_elems text[] ) → json

jsonb_extract_path ( from_json jsonb, VARIADIC path_elems text[] ) → jsonb

Extracts JSON sub-object at the specified path. (This is functionally equivalent to the #> operator, but writing the path out as a variadic list can be more convenient in some cases.)

json_extract_path('{"f2":{"f3":1},"f4":{"f5":99,"f6":"foo"}}', 'f4', 'f6')"foo"

json_object_keys ( json ) → setof text

jsonb_object_keys ( jsonb ) → setof text

Returns the set of keys in the top-level JSON object.

select * from json_object_keys('{"f1":"abc","f2":{"f3":"a", "f4":"b"}}')

json_object_keys
------------------
 f1
 f2

jsonb_set ( target jsonb, path text[], new_value jsonb [, create_if_missing boolean ] ) → jsonb

Returns target with the item designated by path replaced by new_value, or with new_value added if create_if_missing is true (which is the default) and the item designated by path does not exist. All earlier steps in the path must exist, or the target is returned unchanged. As with the path oriented operators, negative integers that appear in the path count from the end of JSON arrays. If the last path step is an array index that is out of range, and create_if_missing is true, the new value is added at the beginning of the array if the index is negative, or at the end of the array if it is positive.

jsonb_set('[{"f1":1,"f2":null},2,null,3]', '{0,f1}', '[2,3,4]', false)[{"f1": [2, 3, 4], "f2": null}, 2, null, 3]

jsonb_set('[{"f1":1,"f2":null},2]', '{0,f3}', '[2,3,4]')[{"f1": 1, "f2": null, "f3": [2, 3, 4]}, 2]

jsonb_insert ( target jsonb, path text[], new_value jsonb [, insert_after boolean ] ) → jsonb

Returns target with new_value inserted. If the item designated by the path is an array element, new_value will be inserted before that item if insert_after is false (which is the default), or after it if insert_after is true. If the item designated by the path is an object field, new_value will be inserted only if the object does not already contain that key. All earlier steps in the path must exist, or the target is returned unchanged. As with the path oriented operators, negative integers that appear in the path count from the end of JSON arrays. If the last path step is an array index that is out of range, the new value is added at the beginning of the array if the index is negative, or at the end of the array if it is positive.

jsonb_insert('{"a": [0,1,2]}', '{a, 1}', '"new_value"'){"a": [0, "new_value", 1, 2]}

jsonb_insert('{"a": [0,1,2]}', '{a, 1}', '"new_value"', true){"a": [0, 1, "new_value", 2]}

json_strip_nulls ( json ) → json

jsonb_strip_nulls ( jsonb ) → jsonb

Deletes all object fields that have null values from the given JSON value, recursively. Null values that are not object fields are untouched.

json_strip_nulls('[{"f1":1, "f2":null}, 2, null, 3]')[{"f1":1},2,null,3]

jsonb_path_exists ( target jsonb, path jsonpath [, vars jsonb [, silent boolean ]] ) → boolean

Checks whether the JSON path returns any item for the specified JSON value. If the vars argument is specified, it must be a JSON object, and its fields provide named values to be substituted into the jsonpath expression. If the silent argument is specified and is true, the function suppresses the same errors as the @? and @@ operators do.

jsonb_path_exists('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2, "max":4}')t

jsonb_path_match ( target jsonb, path jsonpath [, vars jsonb [, silent boolean ]] ) → boolean

Returns the result of a JSON path predicate check for the specified JSON value. Only the first item of the result is taken into account. If the result is not Boolean, then NULL is returned. The optional vars and silent arguments act the same as for jsonb_path_exists.

jsonb_path_match('{"a":[1,2,3,4,5]}', 'exists($.a[*] ? (@ >= $min && @ <= $max))', '{"min":2, "max":4}')t

jsonb_path_query ( target jsonb, path jsonpath [, vars jsonb [, silent boolean ]] ) → setof jsonb

Returns all JSON items returned by the JSON path for the specified JSON value. The optional vars and silent arguments act the same as for jsonb_path_exists.

select * from jsonb_path_query('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2, "max":4}')

jsonb_path_query
------------------
 2
 3
 4

jsonb_path_query_array ( target jsonb, path jsonpath [, vars jsonb [, silent boolean ]] ) → jsonb

Returns all JSON items returned by the JSON path for the specified JSON value, as a JSON array. The optional vars and silent arguments act the same as for jsonb_path_exists.

jsonb_path_query_array('{"a":[1,2,3,4,5]}', '$.a[*] ? (@ >= $min && @ <= $max)', '{"min":2, "max":4}')[2, 3, 4]

jsonb_pretty ( jsonb ) → text

Converts the given JSON value to pretty-printed, indented text.

jsonb_pretty('[{"f1":1,"f2":null}, 2]')

[
    {
        "f1": 1,
        "f2": null
    },
    2
]

json_typeof ( json ) → text

jsonb_typeof ( jsonb ) → text

Returns the type of the top-level JSON value as a text string. Possible types are object, array, string, number, boolean, and null. (The null result should not be confused with an SQL NULL; see the examples.)

json_typeof('-123.4')number

json_typeof('null'::json)null

json_typeof(NULL::json) IS NULLt

See also Section 8.17 for the aggregate function json_agg which aggregates record values as JSON, the aggregate function json_object_agg which aggregates pairs of values into a JSON object, and their jsonb equivalents, jsonb_agg and jsonb_object_agg.

The SQL/JSON Path Language

SQL/JSON path expressions specify the items to be retrieved from the JSON data, similar to XPath expressions used for SQL access to XML. In ProtonBase, path expressions are implemented as the jsonpath data type and can use any elements described in Section 7.10.5.

JSON query functions and operators pass the provided path expression to the path engine for evaluation. If the expression matches the queried JSON data, the corresponding JSON item, or set of items, is returned. Path expressions are written in the SQL/JSON path language and can include arithmetic expressions and functions.

A path expression consists of a sequence of elements allowed by the jsonpath data type. The path expression is normally evaluated from left to right, but you can use parentheses to change the order of operations. If the evaluation is successful, a sequence of JSON items is produced, and the evaluation result is returned to the JSON query function that completes the specified computation.

To refer to the JSON value being queried (the context item), use the $ variable in the path expression. It can be followed by one or more accessor operators, which go down the JSON structure level by level to retrieve sub-items of the context item. Each operator that follows deals with the result of the previous evaluation step.

For example, suppose you have some JSON data from a GPS tracker that you would like to parse, such as:

{
  "track": {
    "segments": [
      {
        "location":   [ 47.763, 13.4034 ],
        "start time": "2018-10-14 10:05:14",
        "HR": 73
      },
      {
        "location":   [ 47.706, 13.2635 ],
        "start time": "2018-10-14 10:39:21",
        "HR": 135
      }
    ]
  }
}

To retrieve the available track segments, you need to use the .`key` accessor operator to descend through surrounding JSON objects:

$.track.segments

To retrieve the contents of an array, you typically use the [*] operator. For example, the following path will return the location coordinates for all the available track segments:

$.track.segments[*].location

To return the coordinates of the first segment only, you can specify the corresponding subscript in the [] accessor operator. Recall that JSON array indexes are 0-relative:

$.track.segments[0].location

The result of each path evaluation step can be processed by one or more jsonpath operators and methods listed in Section 8.13.2.2. Each method name must be preceded by a dot. For example, you can get the size of an array:

$.track.segments.size()

More examples of using jsonpath operators and methods within path expressions appear below in Section 8.13.2.2.

When defining a path, you can also use one or more filter expressions that work similarly to the WHERE clause in SQL. A filter expression begins with a question mark and provides a condition in parentheses:

? (condition)

Filter expressions must be written just after the path evaluation step to which they should apply. The result of that step is filtered to include only those items that satisfy the provided condition. SQL/JSON defines three-valued logic, so the condition can be true, false, or unknown. The unknown value plays the same role as SQL NULL and can be tested for with the is unknown predicate. Further path evaluation steps use only those items for which the filter expression returned true.

The functions and operators that can be used in filter expressions are listed in Table 8.42. Within a filter expression, the @ variable denotes the value being filtered (i.e., one result of the preceding path step). You can write accessor operators after @ to retrieve component items.

For example, suppose you would like to retrieve all heart rate values higher than You can achieve this using the following expression:

$.track.segments[*].HR ? (@ > 130)

To get the start times of segments with such values, you have to filter out irrelevant segments before returning the start times, so the filter expression is applied to the previous step, and the path used in the condition is different:

$.track.segments[*] ? (@.HR > 130)."start time"

You can use several filter expressions in sequence, if required. For example, the following expression selects start times of all segments that contain locations with relevant coordinates and high heart rate values:

$.track.segments[*] ? (@.location[1] < 13.4) ? (@.HR > 130)."start time"

Using filter expressions at different nesting levels is also allowed. The following example first filters all segments by location, and then returns high heart rate values for these segments, if available:

$.track.segments[*] ? (@.location[1] < 13.4).HR ? (@ > 130)

You can also nest filter expressions within each other:

$.track ? (exists(@.segments[*] ? (@.HR > 130))).segments.size()

This expression returns the size of the track if it contains any segments with high heart rate values, or an empty sequence otherwise.

ProtonBase's implementation of the SQL/JSON path language has the following deviations from the SQL/JSON standard:

  • A path expression can be a Boolean predicate, although the SQL/JSON standard allows predicates only in filters. This is necessary for implementation of the @@ operator. For example, the following jsonpath expression is valid in ProtonBase:

    $.track.segments[*].HR < 70
  • There are minor differences in the interpretation of regular expression patterns used in like_regex filters, as described in Section 8.13.2.3.

Strict and Lax Modes

When you query JSON data, the path expression may not match the actual JSON data structure. An attempt to access a non-existent member of an object or element of an array results in a structural error. SQL/JSON path expressions have two modes of handling structural errors:

  • lax (default) — the path engine implicitly adapts the queried data to the specified path. Any remaining structural errors are suppressed and converted to empty SQL/JSON sequences.
  • strict — if a structural error occurs, an error is raised.

The lax mode facilitates matching of a JSON document structure and path expression if the JSON data does not conform to the expected schema. If an operand does not match the requirements of a particular operation, it can be automatically wrapped as an SQL/JSON array or unwrapped by converting its elements into an SQL/JSON sequence before performing this operation. Besides, comparison operators automatically unwrap their operands in the lax mode, so you can compare SQL/JSON arrays out-of-the-box. An array of size 1 is considered equal to its sole element. Automatic unwrapping is not performed only when:

  • The path expression contains type() or size() methods that return the type and the number of elements in the array, respectively.
  • The queried JSON data contain nested arrays. In this case, only the outermost array is unwrapped, while all the inner arrays remain unchanged. Thus, implicit unwrapping can only go one level down within each path evaluation step.

For example, when querying the GPS data listed above, you can abstract from the fact that it stores an array of segments when using the lax mode:

lax $.track.segments.location

In the strict mode, the specified path must exactly match the structure of the queried JSON document to return an SQL/JSON item, so using this path expression will cause an error. To get the same result as in the lax mode, you have to explicitly unwrap the segments array:

strict $.track.segments[*].location

The .** accessor can lead to surprising results when using the lax mode. For instance, the following query selects every HR value twice:

lax $.**.HR

This happens because the .** accessor selects both the segments array and each of its elements, while the .HR accessor automatically unwraps arrays when using the lax mode. To avoid surprising results, we recommend using the .** accessor only in the strict mode. The following query selects each HR value just once:

strict $.**.HR

SQL/JSON Path Operators and Methods

Table 8.41 shows the operators and methods available in jsonpath. Note that while the unary operators and methods can be applied to multiple values resulting from a preceding path step, the binary operators (addition etc.) can only be applied to single values.

Table jsonpath Operators and Methods

Operator/Method Description Example(s)

number + number`number`

Addition

jsonb_path_query('[2]', '$[0] + 3')5

+ number`number`

Unary plus (no operation); unlike addition, this can iterate over multiple values

jsonb_path_query_array('{"x": [2,3,4]}', '+ $.x')[2, 3, 4]

number - number`number`

Subtraction

jsonb_path_query('[2]', '7 - $[0]')5

- number`number`

Negation; unlike subtraction, this can iterate over multiple values

jsonb_path_query_array('{"x": [2,3,4]}', '- $.x')[-2, -3, -4]

number * number`number`

Multiplication

jsonb_path_query('[4]', '2 * $[0]')8

number / number`number`

Division

jsonb_path_query('[8.5]', '$[0] / 2')4.2500000000000000

number % number`number`

Modulo (remainder)

jsonb_path_query('[32]', '$[0] % 10')2

value . type()`string`

Type of the JSON item (see json_typeof)

jsonb_path_query_array('[1, "2", {}]', '$[*].type()')["number", "string", "object"]

value . size()`number`

Size of the JSON item (number of array elements, or 1 if not an array)

jsonb_path_query('{"m": [11, 15]}', '$.m.size()')2

value . double()`number`

Approximate floating-point number converted from a JSON number or string

jsonb_path_query('{"len": "1.9"}', '$.len.double() * 2')3.8

number . ceiling()`number`

Nearest integer greater than or equal to the given number

jsonb_path_query('{"h": 1.3}', '$.h.ceiling()')2

number . floor()`number`

Nearest integer less than or equal to the given number

jsonb_path_query('{"h": 1.7}', '$.h.floor()')1

number . abs()`number`

Absolute value of the given number

jsonb_path_query('{"z": -0.3}', '$.z.abs()')0.3

string . datetime()`datetime_type` (see note)

Date/time value converted from a string

jsonb_path_query('["2015-8-1", "2015-08-12"]', '$[*] ? (@.datetime() < "2015-08-2".datetime())')"2015-8-1"

string . datetime(`template`)`datetime_type` (see note)

Date/time value converted from a string using the specified to_timestamp template

jsonb_path_query_array('["12:30", "18:40"]', '$[*].datetime("HH24:MI")')["12:30:00", "18:40:00"]

object . keyvalue()`array`

The object's key-value pairs, represented as an array of objects containing three fields: "key", "value", and "id"; "id" is a unique identifier of the object the key-value pair belongs to

jsonb_path_query_array('{"x": "20", "y": 32}', '$.keyvalue()')[{"id": 0, "key": "x", "value": "20"}, {"id": 0, "key": "y", "value": 32}]

The datetime() method sequentially tries to match its input string to the ISO formats for date, timetz, time, timestamptz, and timestamp. It stops on the first matching format and emits the corresponding data type.

The datetime(`template`) method determines the result type according to the fields used in the provided template string.

The datetime() and datetime(`template`) methods use the same parsing rules as the to_timestamp SQL function does (see Section 8.8), with three exceptions. First, these methods don't allow unmatched template patterns. Second, only the following separators are allowed in the template string: minus sign, period, solidus (slash), comma, apostrophe, semicolon, colon and space. Third, separators in the template string must exactly match the input string.

If different date/time types need to be compared, an implicit cast is applied. A date value can be cast to timestamp or timestamptz, timestamp can be cast to timestamptz, and time to timetz. However, all but the first of these conversions depend on the current "guc-timezone" setting, and thus can only be performed within timezone-aware jsonpath functions.

Table 8.42 shows the available filter expression elements.

Table jsonpath Filter Expression Elements

Predicate/Value Description Example(s)

value == valueboolean

Equality comparison (this, and the other comparison operators, work on all JSON scalar values)

jsonb_path_query_array('[1, "a", 1, 3]', '$[*] ? (@ == 1)')[1, 1]

jsonb_path_query_array('[1, "a", 1, 3]', '$[*] ? (@ == "a")')["a"]

value != valueboolean

value <> valueboolean

Non-equality comparison

jsonb_path_query_array('[1, 2, 1, 3]', '$[*] ? (@ != 1)')[2, 3]

jsonb_path_query_array('["a", "b", "c"]', '$[*] ? (@ <> "b")')["a", "c"]

value < valueboolean

Less-than comparison

jsonb_path_query_array('[1, 2, 3]', '$[*] ? (@ < 2)')[1]

value <= valueboolean

Less-than-or-equal-to comparison

jsonb_path_query_array('["a", "b", "c"]', '$[*] ? (@ <= "b")')["a", "b"]

value > valueboolean

Greater-than comparison

jsonb_path_query_array('[1, 2, 3]', '$[*] ? (@ > 2)')[3]

value >= valueboolean

Greater-than-or-equal-to comparison

jsonb_path_query_array('[1, 2, 3]', '$[*] ? (@ >= 2)')[2, 3]

trueboolean

JSON constant true

jsonb_path_query('[{"name": "John", "parent": false}, {"name": "Chris", "parent": true}]', '$[*] ? (@.parent == true)'){"name": "Chris", "parent": true}

falseboolean

JSON constant false

jsonb_path_query('[{"name": "John", "parent": false}, {"name": "Chris", "parent": true}]', '$[*] ? (@.parent == false)'){"name": "John", "parent": false}

null`value`

JSON constant null (note that, unlike in SQL, comparison to null works normally)

jsonb_path_query('[{"name": "Mary", "job": null}, {"name": "Michael", "job": "driver"}]', '$[*] ? (@.job == null) .name')"Mary"

boolean && booleanboolean

Boolean AND

jsonb_path_query('[1, 3, 7]', '$[*] ? (@ > 1 && @ < 5)')3

boolean || booleanboolean

Boolean OR

jsonb_path_query('[1, 3, 7]', '$[*] ? (@ < 1 || @ > 5)')7

! booleanboolean

Boolean NOT

jsonb_path_query('[1, 3, 7]', '$[*] ? (!(@ < 5))')7

boolean is unknownboolean

Tests whether a Boolean condition is unknown.

jsonb_path_query('[-1, 2, 7, "foo"]', '$[*] ? ((@ > 0) is unknown)')"foo"

string like_regex string [ flag string ] → boolean

Tests whether the first operand matches the regular expression given by the second operand, optionally with modifications described by a string of flag characters (see Section 8.13.2.3).

jsonb_path_query_array('["abc", "abd", "aBdC", "abdacb", "babc"]', '$[*] ? (@ like_regex "^ab.*c")')["abc", "abdacb"]

jsonb_path_query_array('["abc", "abd", "aBdC", "abdacb", "babc"]', '$[*] ? (@ like_regex "^ab.*c" flag "i")')["abc", "aBdC", "abdacb"]

string starts with stringboolean

Tests whether the second operand is an initial substring of the first operand.

jsonb_path_query('["John Smith", "Mary Stone", "Bob Johnson"]', '$[*] ? (@ starts with "John")')"John Smith"

exists ( path_expression )boolean

Tests whether a path expression matches at least one SQL/JSON item. Returns unknown if the path expression would result in an error; the second example uses this to avoid a no-such-key error in strict mode.

jsonb_path_query('{"x": [1, 2], "y": [2, 4]}', 'strict $.* ? (exists (@ ? (@[*] > 2)))')[2, 4]

jsonb_path_query_array('{"value": 41}', 'strict $ ? (exists (@.name)) .name')[]

SQL/JSON Regular Expressions

SQL/JSON path expressions allow matching text to a regular expression with the like_regex filter. For example, the following SQL/JSON path query would case-insensitively match all strings in an array that start with an English vowel:

$[*] ? (@ like_regex "^[aeiou]" flag "i")

The optional flag string may include one or more of the characters i for case-insensitive match, m to allow ^ and $ to match at newlines, s to allow . to match a newline, and q to quote the whole pattern (reducing the behavior to a simple substring match).

The SQL/JSON standard borrows its definition for regular expressions from the LIKE_REGEX operator, which in turn uses the XQuery standard. PostgreSQL does not currently support the LIKE_REGEX operator. Therefore, the like_regex filter is implemented using the POSIX regular expression engine described in Section 8.7.3. This leads to various minor discrepancies from standard SQL/JSON behavior, which are cataloged in Section 8.7.3.8"). Note, however, that the flag-letter incompatibilities described there do not apply to SQL/JSON, as it translates the XQuery flag letters to match what the POSIX engine expects.

Keep in mind that the pattern argument of like_regex is a JSON path string literal, written according to the rules given in Section 7.10.5. This means in particular that any backslashes you want to use in the regular expression must be doubled. For example, to match string values of the root document that contain only digits:

$.* ? (@ like_regex "^\\d+$")