This section describes:
functions and operators for processing and creating JSON data
the SQL/JSON path language
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.
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
|
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?
|
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
|
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 for which there is a cast from json
to that type. 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
|
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") |
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. If the
|
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
|
Returns all JSON items returned by the JSON path for the specified JSON value. The optional
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 optional
|
Returns the first JSON item returned by the JSON path for the specified JSON value. Returns
|
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
|
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 8.14.7.
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. 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 .
accessor operator to descend through surrounding JSON objects:key
$.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 9.16.2.2. 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 9.16.2.2.
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 9.51. 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 130. 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.
PostgreSQL'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 PostgreSQL:
$.track.segments[*].HR < 70
There are minor differences in the interpretation of regular expression patterns used in like_regex
filters, as described in Section 9.16.2.3.
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
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.
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)
|
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
|
Date/time value converted from a string
|
Date/time value converted from a string using the specified
|
The object's key-value pairs, represented as an array of objects containing three fields:
|
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.
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
|
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:
$.* ? (@ like_regex "^\\d+$")
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