9.16. JSON Functions and Operators
This section describes:
- 
    functions and operators for processing and creating JSON data 
- 
    the SQL/JSON path language 
- 
    the SQL/JSON query functions 
To provide native support for JSON data types within the SQL environment, PostgreSQL implements the SQL/JSON data model . This model comprises sequences of items. Each item can hold SQL scalar values, with an additional SQL/JSON null value, and composite data structures that use JSON arrays and objects. The model is a formalization of the implied data model in the JSON specification RFC 7159 .
SQL/JSON allows you to handle JSON data alongside regular SQL data, with transaction support, including:
- 
    Uploading JSON data into the database and storing it in regular SQL columns as character or binary strings. 
- 
    Generating JSON objects and arrays from relational data. 
- 
    Querying JSON data using SQL/JSON query functions and SQL/JSON path language expressions. 
To learn more about the SQL/JSON standard, see [sqltr-19075-6] . For details on JSON types supported in PostgreSQL , see Section 8.14 .
9.16.1. Processing and Creating JSON Data #
   
    Table 9.45
   
   shows the operators that
   are available for use with JSON data types (see
   
    Section 8.14
   
   ).
   In addition, the usual comparison operators shown in
   
    Table 9.1
   
   are available for
   
    jsonb
   
   , though not for
   
    json
   
   .  The comparison
   operators follow the ordering rules for B-tree operations outlined in
   
    Section 8.14.4
   
   .
   See also
   
    Section 9.21
   
   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
   
   .
  
    
     Table 9.45. 
     
      json
     
     and
     
      jsonb
     
     Operators
    
   
| Operator Description Example(s) | 
|---|
| 
          
          
         Extracts
         
           
          
          | 
| 
          
          Extracts JSON object field with the given key. 
          | 
| 
          
          
         Extracts
         
           
          | 
| 
          
          
         Extracts JSON object field with the given key, as
          
          | 
| 
          
          Extracts JSON sub-object at the specified path, where path elements can be either field keys or array indexes. 
          | 
| 
          
          
         Extracts JSON sub-object at the specified path as
          
          | 
Note
The field/element/path extraction operators return NULL, rather than failing, if the JSON input does not have the right structure to match the request; for example if no such key or array element exists.
   Some further operators exist only for
   
    jsonb
   
   , as shown
   in
   
    Table 9.46
   
   .
   
    Section 8.14.4
   
   describes how these operators can be used to effectively search indexed
   
    jsonb
   
   data.
  
    
     Table 9.46. Additional
     
      jsonb
     
     Operators
    
   
| Operator Description Example(s) | 
|---|
| 
          Does the first JSON value contain the second? (See Section 8.14.3 for details about containment.) 
          | 
| 
          Is the first JSON value contained in the second? 
          | 
| 
          Does the text string exist as a top-level key or array element within the JSON value? 
          
          | 
| 
          Do any of the strings in the text array exist as top-level keys or array elements? 
          | 
| 
          Do all of the strings in the text array exist as top-level keys or array elements? 
          | 
| 
          
         Concatenates two
          
          
          
          
          To append an array to another array as a single entry, wrap it in an additional layer of array, for example: 
          | 
| 
          Deletes a key (and its value) from a JSON object, or matching string value(s) from a JSON array. 
          
          | 
| 
          Deletes all matching keys or array elements from the left operand. 
          | 
| 
          Deletes the array element with specified index (negative integers count from the end). Throws an error if JSON value is not an array. 
          | 
| 
          Deletes the field or array element at the specified path, where path elements can be either field keys or array indexes. 
          | 
| 
          Does JSON path return any item for the specified JSON value? (This is useful only with SQL-standard JSON path expressions, not predicate check expressions , since those always return a value.) 
          | 
| 
          
         Returns the result of a JSON path predicate check for the
        specified JSON value.
        (This is useful only
        with
         
          predicate
        check expressions
         
         , not SQL-standard JSON path expressions,
        since it will return
          
          | 
Note
    The
    
     jsonpath
    
    operators
    
     @?
    
    and
    
     @@
    
    suppress the following errors: missing object
    field or array element, unexpected JSON item type, datetime and numeric
    errors.  The
    
     jsonpath
    
    -related functions described below can
    also be told to suppress these types of errors.  This behavior might be
    helpful when searching JSON document collections of varying structure.
   
   
    Table 9.47
   
   shows the functions that are
   available for constructing
   
    json
   
   and
   
    jsonb
   
   values.
   Some functions in this table have a
   
    RETURNING
   
   clause,
   which specifies the data type returned.  It must be one of
   
    json
   
   ,
   
    jsonb
   
   ,
   
    bytea
   
   , a character string type (
   
    text
   
   ,
   
    char
   
   , or
   
    varchar
   
   ), or a type
   that can be cast to
   
    json
   
   .
   By default, the
   
    json
   
   type is returned.
  
Table 9.47. JSON Creation Functions
| Function Description Example(s) | 
|---|
| 
         
         
          
         Converts any SQL value to
          
          
          | 
| 
         
         
          
         Converts an SQL array to a JSON array.  The behavior is the same
        as
          
          | 
| 
         
         
          
          
         Constructs a JSON array from either a series of
         
           
          
          | 
| 
         
         
          
         Converts an SQL composite value to a JSON object.  The behavior is the
        same as
          
          | 
| 
         
         
          
         
         
          
         Builds a possibly-heterogeneously-typed JSON array out of a variadic
        argument list.  Each argument is converted as
        per
          
          | 
| 
         
         
          
         
         
          
         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
          
          | 
| 
         
         
          
         Constructs a JSON object of all the key/value pairs given,
         or an empty object if none are given.
         
           
          | 
| 
         
         
          Builds a JSON object out of a text array. The array must have either exactly one dimension with an even number of members, in which case they are taken as alternating key/value pairs, or two dimensions such that each inner array has exactly two elements, which are taken as a key/value pair. All values are converted to JSON strings. 
          
          | 
| 
          
          
         This form of
          
          | 
| 
         
         
          
         Converts a given expression specified as
          
          | 
| Converts a given SQL scalar value into a JSON scalar value. If the input is NULL, an SQL null is returned. If the input is number or a boolean value, a corresponding JSON number or boolean value is returned. For any other value, a JSON string is returned. 
          
          | 
| 
          
         Converts an SQL/JSON expression into a character or binary string. The
         
           
          | 
Table 9.48 details SQL/JSON facilities for testing JSON.
Table 9.48. SQL/JSON Testing Functions
   
    Table 9.49
   
   shows the functions that
   are available for processing
   
    json
   
   and
   
    jsonb
   
   values.
  
Table 9.49. JSON Processing Functions
| Function Description Example(s) | 
|---|
| 
         
         
          
         
         
          Expands the top-level JSON array into a set of JSON values. 
          value ----------- 1 true [2,false] 
 | 
| 
         
         
          
         
         
          
         Expands the top-level JSON array into a set of
          
          value ----------- foo bar 
 | 
| 
         
         
          
         
         
          Returns the number of elements in the top-level JSON array. 
          
          | 
| 
         
         
          
         
         
          Expands the top-level JSON object into a set of key/value pairs. 
          key | value -----+------- a | "foo" b | "bar" 
 | 
| 
         
         
          
         
         
          
         Expands the top-level JSON object into a set of key/value pairs.
        The returned
         
           
          key | value -----+------- a | foo b | bar 
 | 
| 
         
         
          
         
         
          
         Extracts JSON sub-object at the specified path.
        (This is functionally equivalent to the
          
          | 
| 
         
         
          
         
         
          
         Extracts JSON sub-object at the specified path as
          
          | 
| 
         
         
          
         
         
          Returns the set of keys in the top-level JSON object. 
          json_object_keys ------------------ f1 f2 
 | 
| 
         
         
          
         
         
          
         Expands the top-level JSON object to a row having the composite type
        of the
         
           To convert a JSON value to the SQL type of an output column, the following rules are applied in sequence: 
 
 
         While the example below uses a constant JSON value, typical use would
        be to reference a
          
          
          
 a |   b       |      c
---+-----------+-------------
 1 | {2,"a b"} | (4,"a b c")
 | 
| 
         
         
          
         Function for testing
          
          
          jsonb_populate_record_valid ----------------------------- f (1 row) 
          ERROR: value too long for type character(2) 
          jsonb_populate_record_valid ----------------------------- t (1 row) 
          a ---- aa (1 row) 
 | 
| 
         
         
          
         
         
          
         Expands the top-level JSON array of objects to a set of rows having
        the composite type of the
         
           
          
          a | b ---+--- 1 | 2 3 | 4 
 | 
| 
         
         
          
         
         
          
         Expands the top-level JSON object to a row having the composite type
        defined by an
          
          
          
 a |    b    |    c    | d |       r
---+---------+---------+---+---------------
 1 | [1,2,3] | {1,2,3} |   | (123,"a b c")
 | 
| 
         
         
          
         
         
          
         Expands the top-level JSON array of objects to a set of rows having
        the composite type defined by an
          
          a | b ---+----- 1 | foo 2 | 
 | 
| 
         
         
          
         Returns
         
           
          
          | 
| 
         
         
          
         If
         
           
          
          | 
| 
         
         
          
         Returns
         
           
          
          | 
| 
         
         
          
         
         
          Deletes all object fields that have null values from the given JSON value, recursively. Null values that are not object fields are untouched. 
          | 
| 
         
         
          
         Checks whether the JSON path returns any item for the specified JSON
        value.
        (This is useful only with SQL-standard JSON path expressions, not
         
          predicate check
        expressions
         
         , since those always return a value.)
        If the
         
           
          | 
| 
         
         
          
         Returns the SQL boolean result of a JSON path predicate check
        for the specified JSON value.
        (This is useful only
        with
         
          predicate
        check expressions
         
         , not SQL-standard JSON path expressions,
        since it will either fail or return
          
          | 
| 
         
         
          
         Returns all JSON items returned by the JSON path for the specified
        JSON value.
        For SQL-standard JSON path expressions it returns the JSON
        values selected from
         
           
          jsonb_path_query ------------------ 2 3 4 
 | 
| 
         
         
          
         Returns all JSON items returned by the JSON path for the specified
        JSON value, as a JSON array.
        The parameters are the same as
        for
          
          | 
| 
         
         
          
         Returns the first JSON item returned by the JSON path for the
        specified JSON value, or
          
          | 
| 
         
         
          
         
         
          
         
         
          
         
         
          
         
         
          
         These functions act like their counterparts described above without
        the
          
          | 
| Converts the given JSON value to pretty-printed, indented text. 
          
[
    {
        "f1": 1,
        "f2": null
    },
    2
]
 | 
| 
         Returns the type of the top-level JSON value as a text string.
        Possible types are
          
          
          
          | 
9.16.2. The SQL/JSON Path Language #
   SQL/JSON path expressions specify item(s) to be retrieved
   from a JSON value, similarly to XPath expressions used
   for access to XML content. In
   
    PostgreSQL
   
   ,
   path expressions are implemented as the
   
    jsonpath
   
   data type and can use any elements described in
   
    Section 8.14.7
   
   .
  
   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.
   If there is no match, the result will be
   
    NULL
   
   ,
   
    false
   
   , or an error, depending on the function.
   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. The first element of a path must always
   be
   
    $
   
   . 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 accessor operator acts on the
   result(s) of the previous evaluation step, producing zero, one, or more
   output items from each input item.
  
For example, suppose you have some JSON data from a GPS tracker that you would like to parse, such as:
SELECT '{
  "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
      }
    ]
  }
}' AS json \gset
  
   (The above example can be copied-and-pasted
   into
   
    psql
   
   to set things up for the following
   examples.  Then
   
    psql
   
   will
   expand
   
    :'json'
   
   into a suitably-quoted string
   constant containing the JSON value.)
  
   To retrieve the available track segments, you need to use the
   
    .
    
     
   accessor
   operator to descend through surrounding JSON objects, for example:
  
      key
     
    
   
=>select jsonb_path_query(:'json', '$.track.segments');jsonb_path_query ----------------------------------------------------------- ----------------------------------------------------------- --------------------------------------------- [{"HR": 73, "location": [47.763, 13.4034], "start time": "2018-10-14 10:05:14"}, {"HR": 135, "location": [47.706, 13.2635], "start time": "2018-10-14 10:39:21"}]
   To retrieve the contents of an array, you typically use the
   
    [*]
   
   operator.
   The following example will return the location coordinates for all
   the available track segments:
  
=>select jsonb_path_query(:'json', '$.track.segments[*].location');jsonb_path_query ------------------- [47.763, 13.4034] [47.706, 13.2635]
   Here we started with the whole JSON input value (
   
    $
   
   ),
   then the
   
    .track
   
   accessor selected the JSON object
   associated with the
   
    "track"
   
   object key, then
   the
   
    .segments
   
   accessor selected the JSON array
   associated with the
   
    "segments"
   
   key within that
   object, then the
   
    [*]
   
   accessor selected each element
   of that array (producing a series of items), then
   the
   
    .location
   
   accessor selected the JSON array
   associated with the
   
    "location"
   
   key within each of
   those objects.  In this example, each of those objects had
   a
   
    "location"
   
   key; but if any of them did not,
   the
   
    .location
   
   accessor would have simply produced no
   output for that input item.
  
   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:
  
=>select jsonb_path_query(:'json', '$.track.segments[0].location');jsonb_path_query ------------------- [47.763, 13.4034]
   The result of each path evaluation step can be processed
   by one or more of the
   
    jsonpath
   
   operators and methods
   listed in
   
    Section 9.16.2.3
   
   .
   Each method name must be preceded by a dot. For example,
   you can get the size of an array:
  
=>select jsonb_path_query(:'json', '$.track.segments.size()');jsonb_path_query ------------------ 2
   More examples of using
   
    jsonpath
   
   operators
   and methods within path expressions appear below in
   
    Section 9.16.2.3
   
   .
  
   A path can also contain
   
    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
   produce
   
    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 9.51
   
   .  Within a
   filter expression, the
   
    @
   
   variable denotes the value
   being considered (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 130. You can achieve this as follows:
=>select jsonb_path_query(:'json', '$.track.segments[*].HR ? (@ > 130)');jsonb_path_query ------------------ 135
To get the start times of segments with such values, you have to filter out irrelevant segments before selecting the start times, so the filter expression is applied to the previous step, and the path used in the condition is different:
=>select jsonb_path_query(:'json', '$.track.segments[*] ? (@.HR > 130)."start time"');jsonb_path_query ----------------------- "2018-10-14 10:39:21"
You can use several filter expressions in sequence, if required. The following example selects start times of all segments that contain locations with relevant coordinates and high heart rate values:
=>select jsonb_path_query(:'json', '$.track.segments[*] ? (@.location[1] < 13.4) ? (@.HR > 130)."start time"');jsonb_path_query ----------------------- "2018-10-14 10:39:21"
Using filter expressions at different nesting levels is also allowed. The following example first filters all segments by location, and then returns high heart rate values for these segments, if available:
=>select jsonb_path_query(:'json', '$.track.segments[*] ? (@.location[1] < 13.4).HR ? (@ > 130)');jsonb_path_query ------------------ 135
You can also nest filter expressions within each other. This example returns the size of the track if it contains any segments with high heart rate values, or an empty sequence otherwise:
=>select jsonb_path_query(:'json', '$.track ? (exists(@.segments[*] ? (@.HR > 130))).segments.size()');jsonb_path_query ------------------ 2
9.16.2.1. Deviations from the SQL Standard #
PostgreSQL 's implementation of the SQL/JSON path language has the following deviations from the SQL/JSON standard.
9.16.2.1.1. Boolean Predicate Check Expressions #
     As an extension to the SQL standard,
     a
     
      PostgreSQL
     
     path expression can be a
     Boolean predicate, whereas the SQL standard allows predicates only within
     filters. While SQL-standard path expressions return the relevant
     element(s) of the queried JSON value, predicate check expressions
     return the single three-valued
     
      jsonb
     
     result of the
     predicate:
     
      true
     
     ,
     
      false
     
     , or
     
      null
     
     .
     For example, we could write this SQL-standard filter expression:
    
=>select jsonb_path_query(:'json', '$.track.segments ?(@[*].HR > 130)');jsonb_path_query ----------------------------------------------------------- ---------------------- {"HR": 135, "location": [47.706, 13.2635], "start time": "2018-10-14 10:39:21"}
     The similar predicate check expression simply
     returns
     
      true
     
     , indicating that a match exists:
    
=>select jsonb_path_query(:'json', '$.track.segments[*].HR > 130');jsonb_path_query ------------------ true
Note
      Predicate check expressions are required in the
      
       @@
      
      operator (and the
      
       jsonb_path_match
      
      function), and should not be used
       with the
      
       @?
      
      operator (or the
      
       jsonb_path_exists
      
      function).
     
9.16.2.1.2. Regular Expression Interpretation #
     There are minor differences in the interpretation of regular
      expression patterns used in
     
      like_regex
     
     filters, as
      described in
     
      Section 9.16.2.4
     
     .
    
9.16.2.2. 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 is defined as 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 structural errors that cannot be fixed as described below are suppressed, producing no match. 
- 
      strict - if a structural error occurs, an error is raised. 
Lax mode facilitates matching of a JSON document and path expression when 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 the operation. Also, comparison operators automatically unwrap their operands in 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 when:
- 
      The path expression contains type()orsize()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 lax mode:
=>select jsonb_path_query(:'json', 'lax $.track.segments.location');jsonb_path_query ------------------- [47.763, 13.4034] [47.706, 13.2635]
In strict mode, the specified path must exactly match the structure of the queried JSON document, so using this path expression will cause an error:
=>select jsonb_path_query(:'json', 'strict $.track.segments.location');ERROR: jsonpath member accessor can only be applied to an object
    To get the same result as in lax mode, you have to explicitly unwrap the
    
     segments
    
    array:
   
=>select jsonb_path_query(:'json', 'strict $.track.segments[*].location');jsonb_path_query ------------------- [47.763, 13.4034] [47.706, 13.2635]
    The unwrapping behavior of lax mode can lead to surprising results. For
    instance, the following query using the
    
     .**
    
    accessor
    selects every
    
     HR
    
    value twice:
   
=>select jsonb_path_query(:'json', 'lax $.**.HR');jsonb_path_query ------------------ 73 135 73 135
    This happens because the
    
     .**
    
    accessor selects both
    the
    
     segments
    
    array and each of its elements, while
    the
    
     .HR
    
    accessor automatically unwraps arrays when
    using lax mode. To avoid surprising results, we recommend using
    the
    
     .**
    
    accessor only in strict mode. The
    following query selects each
    
     HR
    
    value just once:
   
=>select jsonb_path_query(:'json', 'strict $.**.HR');jsonb_path_query ------------------ 73 135
    The unwrapping of arrays can also lead to unexpected results. Consider this
    example, which selects all the
    
     location
    
    arrays:
   
=>select jsonb_path_query(:'json', 'lax $.track.segments[*].location');jsonb_path_query ------------------- [47.763, 13.4034] [47.706, 13.2635] (2 rows)
As expected it returns the full arrays. But applying a filter expression causes the arrays to be unwrapped to evaluate each item, returning only the items that match the expression:
=>select jsonb_path_query(:'json', 'lax $.track.segments[*].location ?(@[*] > 15)');jsonb_path_query ------------------ 47.763 47.706 (2 rows)
This despite the fact that the full arrays are selected by the path expression. Use strict mode to restore selecting the arrays:
=>select jsonb_path_query(:'json', 'strict $.track.segments[*].location ?(@[*] > 15)');jsonb_path_query ------------------- [47.763, 13.4034] [47.706, 13.2635] (2 rows)
9.16.2.3. SQL/JSON Path Operators and Methods #
    
     Table 9.50
    
    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.  In lax mode, methods applied to an array will be
    executed for each value in the array.  The exceptions are
    
     .type()
    
    and
    
     .size()
    
    , which apply to
    the array itself.
   
     
      Table 9.50. 
      
       jsonpath
      
      Operators and Methods
     
    
| Operator/Method Description Example(s) | 
|---|
| 
          
            Addition 
           | 
| 
           Unary plus (no operation); unlike addition, this can iterate over multiple values 
           | 
| 
          
            Subtraction 
           | 
| 
           Negation; unlike subtraction, this can iterate over multiple values 
           | 
| 
          
            Multiplication 
           | 
| 
          
            Division 
           | 
| 
          
            Modulo (remainder) 
           | 
| 
          
            
          Type of the JSON item (see
           
           | 
| 
          
            Size of the JSON item (number of array elements, or 1 if not an array) 
           | 
| 
          
            Boolean value converted from a JSON boolean, number, or string 
           | 
| 
          
            String value converted from a JSON boolean, number, string, or datetime 
           
           | 
| 
          
            Approximate floating-point number converted from a JSON number or string 
           | 
| 
          
            Nearest integer greater than or equal to the given number 
           | 
| 
          
            Nearest integer less than or equal to the given number 
           | 
| 
          
            Absolute value of the given number 
           | 
| 
          
            Big integer value converted from a JSON number or string 
           | 
| 
          
            
          Rounded decimal value converted from a JSON number or string
        (
           
           | 
| 
          
            Integer value converted from a JSON number or string 
           | 
| 
          
            Numeric value converted from a JSON number or string 
           | 
| 
          
            Date/time value converted from a string 
           | 
| 
          
            
          Date/time value converted from a string using the
        specified
           
           | 
| 
          
            Date value converted from a string 
           | 
| 
          
            Time without time zone value converted from a string 
           | 
| 
          
            Time without time zone value converted from a string, with fractional seconds adjusted to the given precision 
           | 
| 
          
            Time with time zone value converted from a string 
           | 
| 
          
            Time with time zone value converted from a string, with fractional seconds adjusted to the given precision 
           | 
| 
          
            Timestamp without time zone value converted from a string 
           | 
| 
          
            Timestamp without time zone value converted from a string, with fractional seconds adjusted to the given precision 
           | 
| 
          
            Timestamp with time zone value converted from a string 
           | 
| 
          
            Timestamp with time zone value converted from a string, with fractional seconds adjusted to the given precision 
           | 
| 
          
            
          The object's key-value pairs, represented as an array of objects
        containing three fields:
           
           | 
Note
     The result type of the
     
      datetime()
     
     and
     
      datetime(
      
       
     methods can be
     
        template
       
      
      )
     
      date
     
     ,
     
      timetz
     
     ,
     
      time
     
     ,
     
      timestamptz
     
     , or
     
      timestamp
     
     .
      Both methods determine their result type dynamically.
    
     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(
      
       
     method determines the result type according to the fields used in the
      provided template string.
    
        template
       
      
      )
     
     The
     
      datetime()
     
     and
     
      datetime(
      
       
     methods
      use the same parsing rules as the
     
        template
       
      
      )
     
      to_timestamp
     
     SQL
      function does (see
     
      Section 9.8
     
     ), 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
     
      TimeZone
     
     setting, and thus can only be performed
      within timezone-aware
     
      jsonpath
     
     functions.  Similarly, other
      date/time-related methods that convert strings to date/time types
      also do this casting, which may involve the current
     
      TimeZone
     
     setting. Therefore, these conversions can
      also only be performed within timezone-aware
     
      jsonpath
     
     functions.
    
Table 9.51 shows the available filter expression elements.
     
      Table 9.51. 
      
       jsonpath
      
      Filter Expression Elements
     
    
| Predicate/Value Description Example(s) | 
|---|
| 
          
            Equality comparison (this, and the other comparison operators, work on all JSON scalar values) 
           
           | 
| 
          
            
          
            Non-equality comparison 
           
           | 
| 
          
            Less-than comparison 
           | 
| 
          
            Less-than-or-equal-to comparison 
           | 
| 
          
            Greater-than comparison 
           | 
| 
          
            Greater-than-or-equal-to comparison 
           | 
| 
           
          JSON constant
           
           | 
| 
           
          JSON constant
           
           | 
| 
           
          JSON constant
           
           | 
| 
          
            Boolean AND 
           | 
| 
          
            Boolean OR 
           | 
| 
           Boolean NOT 
           | 
| 
          
            
          Tests whether a Boolean condition is
           
           | 
| 
          
            
          Tests whether the first operand matches the regular expression
        given by the second operand, optionally with modifications
        described by a string of
           
           
           | 
| 
          
            Tests whether the second operand is an initial substring of the first operand. 
           | 
| 
           
          Tests whether a path expression matches at least one SQL/JSON item.
        Returns
           
           
           | 
9.16.2.4. 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 9.7.3
    
    .  This leads to various minor
     discrepancies from standard SQL/JSON behavior, which are cataloged in
    
     Section 9.7.3.8
    
    .
     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 8.14.7
    
    .  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:
   
$.* ? (@ like_regex "^\\d+$")
9.16.3. SQL/JSON Query Functions #
   SQL/JSON functions
   
    JSON_EXISTS()
   
   ,
   
    JSON_QUERY()
   
   , and
   
    JSON_VALUE()
   
   described in
   
    Table 9.52
   
   can be used
   to query JSON documents.  Each of these functions apply a
   
    
     path_expression
    
   
   (an SQL/JSON path query) to a
   
    
     context_item
    
   
   (the document).  See
   
    Section 9.16.2
   
   for more details on what
   the
   
    
     path_expression
    
   
   can contain. The
   
    
     path_expression
    
   
   can also reference variables,
   whose values are specified with their respective names in the
   
    PASSING
   
   clause that is supported by each function.
   
    
     context_item
    
   
   can be a
   
    jsonb
   
   value
   or a character string that can be successfully cast to
   
    jsonb
   
   .
  
Table 9.52. SQL/JSON Query Functions
| Function signature Description Example(s) | 
|---|
| 
 
 
 Examples: 
          
          
          ERROR: jsonpath array subscript is out of bounds 
 | 
| 
 
 
 Examples: 
          
          
          ERROR: malformed array literal: "[1, 2]" DETAIL: Missing "]" after array dimensions. 
 | 
| 
 
 
 Examples: 
          
          
          
          | 
Note
    The
    
     
      context_item
     
    
    expression is converted to
    
     jsonb
    
    by an implicit cast if the expression is not already of
    type
    
     jsonb
    
    . Note, however, that any parsing errors that occur
    during that conversion are thrown unconditionally, that is, are not
    handled according to the (specified or implicit)
    
     ON ERROR
    
    clause.
   
Note
    
     JSON_VALUE()
    
    returns an SQL NULL if
    
     
      path_expression
     
    
    returns a JSON
    
     null
    
    , whereas
    
     JSON_QUERY()
    
    returns
    the JSON
    
     null
    
    as is.
   
9.16.4. JSON_TABLE #
   
    JSON_TABLE
   
   is an SQL/JSON function which
   queries
   
    JSON
   
   data
   and presents the results as a relational view, which can be accessed as a
   regular SQL table. You can use
   
    JSON_TABLE
   
   inside
   the
   
    FROM
   
   clause of a
   
    SELECT
   
   ,
   
    UPDATE
   
   , or
   
    DELETE
   
   and as data source
   in a
   
    MERGE
   
   statement.
  
   Taking JSON data as input,
   
    JSON_TABLE
   
   uses a JSON path
   expression to extract a part of the provided data to use as a
   
    row pattern
   
   for the constructed view.  Each SQL/JSON
   value given by the row pattern serves as source for a separate row in the
   constructed view.
  
   To split the row pattern into columns,
   
    JSON_TABLE
   
   provides the
   
    COLUMNS
   
   clause that defines the
   schema of the created view. For each column, a separate JSON path expression
   can be specified to be evaluated against the row pattern to get an SQL/JSON
   value that will become the value for the specified column in a given output
   row.
  
   JSON data stored at a nested level of the row pattern can be extracted using
   the
   
    NESTED PATH
   
   clause.  Each
   
    NESTED PATH
   
   clause can be used to generate one or more
   columns using the data from a nested level of the row pattern.  Those
   columns can be specified using a
   
    COLUMNS
   
   clause that
   looks similar to the top-level COLUMNS clause.  Rows constructed from
   NESTED COLUMNS are called
   
    child rows
   
   and are joined
   against the row constructed from the columns specified in the parent
   
    COLUMNS
   
   clause to get the row in the final view.  Child
   columns themselves may contain a
   
    NESTED PATH
   
   specification thus allowing to extract data located at arbitrary nesting
   levels.  Columns produced by multiple
   
    NESTED PATH
   
   s at the
   same level are considered to be
   
    siblings
   
   of each
   other and their rows after joining with the parent row are combined using
   UNION.
  
   The rows produced by
   
    JSON_TABLE
   
   are laterally
   joined to the row that generated them, so you do not have to explicitly join
   the constructed view with the original table holding
   
    JSON
   
   data.
  
The syntax is:
JSON_TABLE (
    context_item, path_expression [ AS json_path_name ] [ PASSING { value AS varname } [, ...] ]
    COLUMNS ( json_table_column [, ...] )
    [ { ERROR | EMPTY [ARRAY]} ON ERROR ]
)
where json_table_column is:
  name FOR ORDINALITY
  | name type
        [ FORMAT JSON [ENCODING UTF8]]
        [ PATH path_expression ]
        [ { WITHOUT | WITH { CONDITIONAL | [UNCONDITIONAL] } } [ ARRAY ] WRAPPER ]
        [ { KEEP | OMIT } QUOTES [ ON SCALAR STRING ] ]
        [ { ERROR | NULL | EMPTY { [ARRAY] | OBJECT } | DEFAULT expression } ON EMPTY ]
        [ { ERROR | NULL | EMPTY { [ARRAY] | OBJECT } | DEFAULT expression } ON ERROR ]
  | name type EXISTS [ PATH path_expression ]
        [ { ERROR | TRUE | FALSE | UNKNOWN } ON ERROR ]
  | NESTED [ PATH ] path_expression [ AS json_path_name ] COLUMNS ( json_table_column [, ...] )
  Each syntax element is described below in more detail.
- 
     
      context_item,path_expression[ASjson_path_name] [PASSING{valueASvarname} [ , ... ] ]
- 
     The context_itemspecifies the input document to query, thepath_expressionis an SQL/JSON path expression defining the query, andjson_path_nameis an optional name for thepath_expression. The optionalPASSINGclause provides data values for the variables mentioned in thepath_expression. The result of the input data evaluation using the aforementioned elements is called the row pattern , which is used as the source for row values in the constructed view.
- 
     
      COLUMNS(json_table_column[ , ... ] )
- 
     The COLUMNSclause defining the schema of the constructed view. In this clause, you can specify each column to be filled with an SQL/JSON value obtained by applying a JSON path expression against the row pattern.json_table_columnhas the following variants:- 
        
         
          nameFOR ORDINALITY
- 
        Adds an ordinality column that provides sequential row numbering starting from 1. Each NESTED PATH(see below) gets its own counter for any nested ordinality columns.
- 
        
         nametype[FORMAT JSON[ ENCODINGUTF8] ] [PATHpath_expression]
- 
        Inserts an SQL/JSON value obtained by applying path_expressionagainst the row pattern into the view's output row after coercing it to specifiedtype.Specifying FORMAT JSONmakes it explicit that you expect the value to be a validjsonobject. It only makes sense to specifyFORMAT JSONiftypeis one ofbpchar,bytea,character varying,name,json,jsonb,text, or a domain over these types.Optionally, you can specify WRAPPERandQUOTESclauses to format the output. Note that specifyingOMIT QUOTESoverridesFORMAT JSONif also specified, because unquoted literals do not constitute validjsonvalues.Optionally, you can use ON EMPTYandON ERRORclauses to specify whether to throw the error or return the specified value when the result of JSON path evaluation is empty and when an error occurs during JSON path evaluation or when coercing the SQL/JSON value to the specified type, respectively. The default for both is to return aNULLvalue.NoteThis clause is internally turned into and has the same semantics as JSON_VALUEorJSON_QUERY. The latter if the specified type is not a scalar type or if either ofFORMAT JSON,WRAPPER, orQUOTESclause is present.
- 
        
         
          nametypeEXISTS[PATHpath_expression]
- 
        Inserts a boolean value obtained by applying path_expressionagainst the row pattern into the view's output row after coercing it to specifiedtype.The value corresponds to whether applying the PATHexpression to the row pattern yields any values.The specified typeshould have a cast from thebooleantype.Optionally, you can use ON ERRORto specify whether to throw the error or return the specified value when an error occurs during JSON path evaluation or when coercing SQL/JSON value to the specified type. The default is to return a boolean valueFALSE.NoteThis clause is internally turned into and has the same semantics as JSON_EXISTS.
- 
        
         NESTED [ PATH ]path_expression[ASjson_path_name]COLUMNS(json_table_column[ , ... ] )
- 
        Extracts SQL/JSON values from nested levels of the row pattern, generates one or more columns as defined by the COLUMNSsubclause, and inserts the extracted SQL/JSON values into those columns. Thejson_table_columnexpression in theCOLUMNSsubclause uses the same syntax as in the parentCOLUMNSclause.The NESTED PATHsyntax is recursive, so you can go down multiple nested levels by specifying severalNESTED PATHsubclauses within each other. It allows to unnest the hierarchy of JSON objects and arrays in a single function invocation rather than chaining severalJSON_TABLEexpressions in an SQL statement.
 NoteIn each variant of json_table_columndescribed above, if thePATHclause is omitted, path expression$.is used, wherenamenameis the provided column name.
- 
        
         
          
- 
     
      ASjson_path_name
- 
     The optional json_path_nameserves as an identifier of the providedpath_expression. The name must be unique and distinct from the column names.
- 
     
      {
      ERROR|EMPTY}ON ERROR
- 
     The optional ON ERRORcan be used to specify how to handle errors when evaluating the top-levelpath_expression. UseERRORif you want the errors to be thrown andEMPTYto return an empty table, that is, a table containing 0 rows. Note that this clause does not affect the errors that occur when evaluating columns, for which the behavior depends on whether theON ERRORclause is specified against a given column.
Examples
In the examples that follow, the following table containing JSON data will be used:
CREATE TABLE my_films ( js jsonb );
INSERT INTO my_films VALUES (
'{ "favorites" : [
   { "kind" : "comedy", "films" : [
     { "title" : "Bananas",
       "director" : "Woody Allen"},
     { "title" : "The Dinner Game",
       "director" : "Francis Veber" } ] },
   { "kind" : "horror", "films" : [
     { "title" : "Psycho",
       "director" : "Alfred Hitchcock" } ] },
   { "kind" : "thriller", "films" : [
     { "title" : "Vertigo",
       "director" : "Alfred Hitchcock" } ] },
   { "kind" : "drama", "films" : [
     { "title" : "Yojimbo",
       "director" : "Akira Kurosawa" } ] }
  ] }');
  
   The following query shows how to use
   
    JSON_TABLE
   
   to
      turn the JSON objects in the
   
    my_films
   
   table
      to a view containing columns for the keys
   
    kind
   
   ,
   
    title
   
   , and
   
    director
   
   contained in
      the original JSON along with an ordinality column:
  
SELECT jt.* FROM my_films, JSON_TABLE (js, '$.favorites[*]' COLUMNS ( id FOR ORDINALITY, kind text PATH '$.kind', title text PATH '$.films[*].title' WITH WRAPPER, director text PATH '$.films[*].director' WITH WRAPPER)) AS jt;
id | kind | title | director ----+----------+--------------------------------+---------------------------------- 1 | comedy | ["Bananas", "The Dinner Game"] | ["Woody Allen", "Francis Veber"] 2 | horror | ["Psycho"] | ["Alfred Hitchcock"] 3 | thriller | ["Vertigo"] | ["Alfred Hitchcock"] 4 | drama | ["Yojimbo"] | ["Akira Kurosawa"] (4 rows)
   The following is a modified version of the above query to show the
      usage of
   
    PASSING
   
   arguments in the filter specified in
      the top-level JSON path expression and the various options for the
      individual columns:
  
SELECT jt.* FROM
 my_films,
 JSON_TABLE (js, '$.favorites[*] ? (@.films[*].director == $filter)'
   PASSING 'Alfred Hitchcock' AS filter
     COLUMNS (
     id FOR ORDINALITY,
     kind text PATH '$.kind',
     title text FORMAT JSON PATH '$.films[*].title' OMIT QUOTES,
     director text PATH '$.films[*].director' KEEP QUOTES)) AS jt;
  
id | kind | title | director ----+----------+---------+-------------------- 1 | horror | Psycho | "Alfred Hitchcock" 2 | thriller | Vertigo | "Alfred Hitchcock" (2 rows)
   The following is a modified version of the above query to show the usage
      of
   
    NESTED PATH
   
   for populating title and director
      columns, illustrating how they are joined to the parent columns id and
      kind:
  
SELECT jt.* FROM
 my_films,
 JSON_TABLE ( js, '$.favorites[*] ? (@.films[*].director == $filter)'
   PASSING 'Alfred Hitchcock' AS filter
   COLUMNS (
    id FOR ORDINALITY,
    kind text PATH '$.kind',
    NESTED PATH '$.films[*]' COLUMNS (
      title text FORMAT JSON PATH '$.title' OMIT QUOTES,
      director text PATH '$.director' KEEP QUOTES))) AS jt;
  
id | kind | title | director ----+----------+---------+-------------------- 1 | horror | Psycho | "Alfred Hitchcock" 2 | thriller | Vertigo | "Alfred Hitchcock" (2 rows)
The following is the same query but without the filter in the root path:
SELECT jt.* FROM
 my_films,
 JSON_TABLE ( js, '$.favorites[*]'
   COLUMNS (
    id FOR ORDINALITY,
    kind text PATH '$.kind',
    NESTED PATH '$.films[*]' COLUMNS (
      title text FORMAT JSON PATH '$.title' OMIT QUOTES,
      director text PATH '$.director' KEEP QUOTES))) AS jt;
  
id | kind | title | director ----+----------+-----------------+-------------------- 1 | comedy | Bananas | "Woody Allen" 1 | comedy | The Dinner Game | "Francis Veber" 2 | horror | Psycho | "Alfred Hitchcock" 3 | thriller | Vertigo | "Alfred Hitchcock" 4 | drama | Yojimbo | "Akira Kurosawa" (5 rows)
   The following shows another query using a different
   
    JSON
   
   object as input.  It shows the UNION "sibling join" between
   
    NESTED
   
   paths
   
    $.movies[*]
   
   and
   
    $.books[*]
   
   and also the usage of
   
    FOR ORDINALITY
   
   column at
   
    NESTED
   
   levels (columns
   
    movie_id
   
   ,
   
    book_id
   
   ,
      and
   
    author_id
   
   ):
  
SELECT * FROM JSON_TABLE (
'{"favorites":
    [{"movies":
      [{"name": "One", "director": "John Doe"},
       {"name": "Two", "director": "Don Joe"}],
     "books":
      [{"name": "Mystery", "authors": [{"name": "Brown Dan"}]},
       {"name": "Wonder", "authors": [{"name": "Jun Murakami"}, {"name":"Craig Doe"}]}]
}]}'::json, '$.favorites[*]'
COLUMNS (
  user_id FOR ORDINALITY,
  NESTED '$.movies[*]'
    COLUMNS (
    movie_id FOR ORDINALITY,
    mname text PATH '$.name',
    director text),
  NESTED '$.books[*]'
    COLUMNS (
      book_id FOR ORDINALITY,
      bname text PATH '$.name',
      NESTED '$.authors[*]'
        COLUMNS (
          author_id FOR ORDINALITY,
          author_name text PATH '$.name'))));
  
 user_id | movie_id | mname | director | book_id |  bname  | author_id | author_name
---------+----------+-------+----------+---------+---------+-----------+--------------
       1 |        1 | One   | John Doe |         |         |           |
       1 |        2 | Two   | Don Joe  |         |         |           |
       1 |          |       |          |       1 | Mystery |         1 | Brown Dan
       1 |          |       |          |       2 | Wonder  |         1 | Jun Murakami
       1 |          |       |          |       2 | Wonder  |         2 | Craig Doe
(5 rows)