9.15. JSON Functions and Operators

Table 9.44 shows the operators that are available for use with JSON data types (see Section 8.14 ).

The standard comparison operators shown in Table 9.1 are available for jsonb , but not for json . They follow the ordering rules for B-tree operations outlined at Section 8.14.4 .

Some further operators also exist only for jsonb , as shown in Table 9.45 . Many of these operators can be indexed by jsonb operator classes. For a full description of jsonb containment and existence semantics, see Section 8.14.3 . Section 8.14.4 describes how these operators can be used to effectively index jsonb data.

Table 9.46 shows the functions that are available for creating json and jsonb values. (There are no equivalent functions for jsonb , of the row_to_json and array_to_json functions. However, the to_jsonb function supplies much the same functionality as these functions would.)

Table 9.47 shows the functions that are available for processing json and jsonb values.

 key | value
-----+-------
 a   | "foo"
 b   | "bar"

 key | value
-----+-------
 a   | foo
 b   | bar

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

 a |   b       |      c
---+-----------+-------------
 1 | {2,"a b"} | (4,"a b c")

 a | b
---+---
 1 | 2
 3 | 4

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

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

 a |    b    |    c    | d |       r
---+---------+---------+---+---------------
 1 | [1,2,3] | {1,2,3} |   | (123,"a b c")

 a |  b
---+-----
 1 | foo
 2 |

[
    {
        "f1": 1,
        "f2": null
    },
    2,
    null,
    3
]

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

See also Section 9.20 for the aggregate function json_agg which aggregates record values as JSON, and 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 .

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 PostgreSQL , path expressions are implemented as the jsonpath data type and can use any elements described in Section 8.14.6 .

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 SQL/JSON item is returned. Path expressions are written in the SQL/JSON path language and can also include arithmetic expressions and functions. Query functions treat the provided expression as a text string, so it must be enclosed in single quotes.

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

To refer to the JSON data to be queried (the context item ), use the $ sign 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 the content of 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 for all the preceding JSON objects:

'$.track.segments'

If the item to retrieve is an element of an array, you have to unnest this array using the [*] operator. For example, the following path will return 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. Note that the SQL/JSON arrays 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 9.15.2.3 . Each method name must be preceded by a dot. For example, you can get an array size:

'$.track.segments.size()'

For more examples of using jsonpath operators and methods within path expressions, see Section 9.15.2.3 .

When defining the path, you can also use one or more filter expressions that work similar 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 specified right after the path evaluation step to which they are applied. The result of this 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 filter expressions return true .

Functions and operators that can be used in filter expressions are listed in Table 9.49 . The path evaluation result to be filtered is denoted by the @ variable. To refer to a JSON element stored at a lower nesting level, add one or more accessor operators after @ .

Suppose you would like to retrieve all heart rate values higher than 130. You can achieve this using the following expression:

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

To get the start time of segments with such values instead, you have to filter out irrelevant segments before returning the start time, 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 on the same nesting level, if required. For example, the following expression selects 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.

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

'lax $.track.segments.location'

'strict $.track.segments[*].location'

lax $.**.HR

strict $.**.HR

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

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