Postgresql 中文操作指南

9.16. JSON Functions and Operators #

本部分介绍:

This section describes:

为了在 SQL 环境中提供对 JSON 数据类型的原生支持,PostgreSQL 实现了 SQL/JSON data model。此模型包含多个项的序列。每个项可以保存 SQL 标量值,而另附加 SQL/JSON null 值,以及使用 JSON 数组和对象复合数据结构。此模型是 JSON 规范 RFC 7159 中隐含数据模型的形式化表达。

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.

使用 SQL/JSON,你可以处理 JSON 数据和常规 SQL 数据,同时支持事务,包括:

SQL/JSON allows you to handle JSON data alongside regular SQL data, with transaction support, including:

要详细了解 SQL/JSON 标准,请参见 [id="sqltr-19075-6",role="bare"]biblio.html#SQLTR-19075-6[id="sqltr-19075-6"]。有关 PostgreSQL 中支持的 JSON 类型的详细信息,请参见 Section 8.14

To learn more about the SQL/JSON standard, see biblio.html#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 显示了可用于 JSON 数据类型的运算符(请参见 Section 8.14)。此外, Table 9.1 中显示的常见比较运算符可用于 jsonb,但不能用于 json。比较运算符遵循 Section 8.14.4 中概述的 B 树操作排序规则。另请参见 Section 9.21,其中包含聚集函数 json_agg,该函数将记录值聚集为 JSON,聚集函数 json_object_agg,该函数将对值对聚集到一个 JSON 对象,以及其 jsonb 等价函数 jsonb_aggjsonb_object_agg

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

Table 9.45. 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

Note

如果 JSON 输入没有与请求匹配的正确结构,则字段/元素/路径提取运算符将返回 NULL,而不是失败;例如,如果不存在这样的键或数组元素。

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.

一些其他运算符仅用于 jsonb,如 Table 9.46中所示。 Section 8.14.4描述了如何使用这些运算符有效搜索索引后 _jsonb_数据。

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

Table 9.46. Additional jsonb Operators

Operator

Description

Example(s)

jsonb @> jsonbboolean

Does the first JSON value contain the second? (See Section 8.14.3 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", {}]

jsonb @? jsonpathboolean

Does JSON path return any item for the specified JSON value?

'{"a":[1,2,3,4,5]}'::jsonb @? '$.a[*] ? (@ > 2)'t

jsonb @@ jsonpathboolean

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.

'{"a":[1,2,3,4,5]}'::jsonb @@ '$.a[*] > 2't

Note

jsonpath 运算符 @?@@ 抑制以下错误:缺少对象字段或数组元素,意外的 JSON 项类型,日期时间和数字错误。下面描述的 jsonpath 相关函数还可以抑制这些类型的错误。在搜索结构各异的 JSON 文档集合时,此行为可能会有所帮助。

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显示用于构建 json_和 _jsonb_值的函数。此表中的部分函数具有 _RETURNING_子句,该子句指定了返回的数据类型。它必须是 _jsonjsonbbytea、字符字符串类型 (textchar_或 _varchar)或存在从 _json_到该类型的转换的类型。默认情况下,返回 _json_类型。

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)

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;#ftn.id-1.5.8.22.8.9.2.2.1.1.3.4 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.\""}

array_to_json ( anyarray [, boolean ] ) → json

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

array_to_json('{{1,5},{99,100}}'::int[])[[1,5],[99,100]]

json_array ( [ { value_expression [ FORMAT JSON ] } [, …​] ] [ { NULL

ABSENT } ON NULL ] [ RETURNING data_type [ FORMAT JSON [ ENCODING UTF8 ] ] ])

json_array ( [ query_expression ] [ RETURNING data_type [ FORMAT JSON [ ENCODING UTF8 ] ] ])

Constructs a JSON array from either a series of value_expression parameters or from the results of query_expression, which must be a SELECT query returning a single column. If ABSENT ON NULL is specified, NULL values are ignored. This is always the case if a query_expression is used.

json_array(1,true,json '{"a":null}')[1, true, {"a":null}]

json_array(SELECT * FROM (VALUES(1),(2)) t)[1, 2]

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 ( [ { key_expression { VALUE

':' } value_expression [ FORMAT JSON [ ENCODING UTF8 ] ] }[, …​] ] [ { NULL

ABSENT } ON NULL ] [ { WITH

WITHOUT } UNIQUE [ KEYS ] ] [ RETURNING data_type [ FORMAT JSON [ ENCODING UTF8 ] ] ])

Constructs a JSON object of all the key/value pairs given, or an empty object if none are given. key_expression is a scalar expression defining the JSON key, which is converted to the text type. It cannot be NULL nor can it belong to a type that has a cast to the json type. If WITH UNIQUE KEYS is specified, there must not be any duplicate key_expression. Any pair for which the value_expression evaluates to NULL is omitted from the output if ABSENT ON NULL is specified; if NULL ON NULL is specified or the clause omitted, the key is included with value NULL.

json_object('code' VALUE 'P123', 'title': 'Jaws'){"code" : "P123", "title" : "Jaws"}

json_object ( text[] ) → json

jsonb_object ( text[] ) → jsonb

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.

json_object('{a, 1, b, "def", c, 3.5}'){"a" : "1", "b" : "def", "c" : "3.5"}

json_object('{{a, 1}, {b, "def"}, {c, 3.5}}'){"a" : "1", "b" : "def", "c" : "3.5"}

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"}

#id-1.5.8.22.8.9.2.2.1.1.3.4 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.

[id="a",role="bare"]#id-1.5.8.22.8.9.2.2.1.1.3.4 [id="a"] 例如, hstore 扩展从 hstorejson ,以便通过 JSON 创建函数转换的 hstore 值将表示为 JSON 对象,而不是原始字符串值。

#id-1.5.8.22.8.9.2.2.1.1.3.4 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 9.48详细介绍用于测试 JSON 的 SQL/JSON 功能。

Table 9.48 details SQL/JSON facilities for testing JSON.

Table 9.48. SQL/JSON Testing Functions

Function signature

Description

Example(s)

expression IS [ NOT ] JSON [ { VALUE

SCALAR

ARRAY

OBJECT } ] [ { WITH

WITHOUT } UNIQUE [ KEYS ] ]

This predicate tests whether expression can be parsed as JSON, possibly of a specified type. If SCALAR or ARRAY or OBJECT is specified, the test is whether or not the JSON is of that particular type. If WITH UNIQUE KEYS is specified, then any object in the expression is also tested to see if it has duplicate keys. SELECT js, js IS JSON "json?", js IS JSON SCALAR "scalar?", js IS JSON OBJECT "object?", js IS JSON ARRAY "array?" FROM (VALUES ('123'), ('"abc"'), ('{"a": "b"}'), ('[1,2]'),('abc')) foo(js); js

json?

scalar?

object?

array? --------------------------------------------- 123

t

t

f

f "abc"

t

t

f

f {"a": "b"}

t

f

t

f [1,2]

t

f

f

t abc

f

f

f

f SELECT js, js IS JSON OBJECT "object?", js IS JSON ARRAY "array?", js IS JSON ARRAY WITH UNIQUE KEYS "array w. UK?", js IS JSON ARRAY WITHOUT UNIQUE KEYS "array w/o UK?" FROM (VALUES ('[{"a":"1"}, {"b":"2","b":"3"}]')) foo(js); -[ RECORD 1 ]-+-------------------- js

[{"a":"1"},

{"b":"2","b":"3"}] object?

f array?

t array w. UK?

f array w/o UK?

t

Table 9.49显示用于处理 _json_和 _jsonb_值的函数。

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)

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

jsonb_array_length('[]')0

json_each ( json ) → setof record ( key text, value json )

jsonb_each ( jsonb ) → setof record ( key text, value jsonb )

Expands the top-level JSON object into a set of key/value pairs.

select * from json_each('{"a":"foo", "b":"bar"}') → key

value -----+------- a

"foo" b

"bar"

json_each_text ( json ) → setof record ( key text, value text )

jsonb_each_text ( jsonb ) → setof record ( key text, value text )

Expands the top-level JSON object into a set of key/value pairs. The returned value_s will be of type _text.

select * from json_each_text('{"a":"foo", "b":"bar"}') → key

value -----+------- a

foo b

bar

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

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

Extracts JSON sub-object at the specified path as text. (This is functionally equivalent to the #>> operator.)

json_extract_path_text('{"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

json_populate_record ( base anyelement, from_json json ) → anyelement

jsonb_populate_record ( base anyelement, from_json jsonb ) → anyelement

Expands the top-level JSON object to a row having the composite type of the base argument. The JSON object is scanned for fields whose names match column names of the output row type, and their values are inserted into those columns of the output. (Fields that do not correspond to any output column name are ignored.) In typical use, the value of base is just NULL, which means that any output columns that do not match any object field will be filled with nulls. However, if base isn’t NULL then the values it contains will be used for unmatched columns.

To convert a JSON value to the SQL type of an output column, the following rules are applied in sequence:

A JSON null value is converted to an SQL null in all cases.

If the output column is of type json or jsonb, the JSON value is just reproduced exactly.

If the output column is a composite (row) type, and the JSON value is a JSON object, the fields of the object are converted to columns of the output row type by recursive application of these rules.

Likewise, if the output column is an array type and the JSON value is a JSON array, the elements of the JSON array are converted to elements of the output array by recursive application of these rules.

Otherwise, if the JSON value is a string, the contents of the string are fed to the input conversion function for the column’s data type.

Otherwise, the ordinary text representation of the JSON value is fed to the input conversion function for the column’s data type.

While the example below uses a constant JSON value, typical use would be to reference a json or jsonb column laterally from another table in the query’s FROM clause. Writing json_populate_record in the FROM clause is good practice, since all of the extracted columns are available for use without duplicate function calls.

create type subrowtype as (d int, e text); create type myrowtype as (a int, b text[], c subrowtype);

select * from json_populate_record(null::myrowtype, '{"a": 1, "b": ["2", "a b"], "c": {"d": 4, "e": "a b c"}, "x": "foo"}') → a

b

c --------------------------- 1

{2,"a b"}

(4,"a b c")

json_populate_recordset ( base anyelement, from_json json ) → setof anyelement

jsonb_populate_recordset ( base anyelement, from_json jsonb ) → setof anyelement

Expands the top-level JSON array of objects to a set of rows having the composite type of the base argument. Each element of the JSON array is processed as described above for json[b]_populate_record.

create type twoints as (a int, b int);

select * from json_populate_recordset(null::twoints, '[{"a":1,"b":2}, {"a":3,"b":4}]') → a

b ---+--- 1

2 3

4

json_to_record ( json ) → record

jsonb_to_record ( jsonb ) → record

Expands the top-level JSON object to a row having the composite type defined by an AS clause. (As with all functions returning record, the calling query must explicitly define the structure of the record with an AS clause.) The output record is filled from fields of the JSON object, in the same way as described above for json[b]_populate_record. Since there is no input record value, unmatched columns are always filled with nulls.

create type myrowtype as (a int, b text);

select * from json_to_record('{"a":1,"b":[1,2,3],"c":[1,2,3],"e":"bar","r": {"a": 123, "b": "a b c"}}') as x(a int, b text, c int[], d text, r myrowtype) → a

b

c

d

r --------------------------------------- 1

[1,2,3]

{1,2,3}

(123,"a b c")

json_to_recordset ( json ) → setof record

jsonb_to_recordset ( jsonb ) → setof record

Expands the top-level JSON array of objects to a set of rows having the composite type defined by an AS clause. (As with all functions returning record, the calling query must explicitly define the structure of the record with an AS clause.) Each element of the JSON array is processed as described above for json[b]_populate_record.

select * from json_to_recordset('[{"a":1,"b":"foo"}, {"a":"2","c":"bar"}]') as x(a int, b text) → a

b ---+----- 1

foo 2

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

If new_value is not NULL, behaves identically to jsonb_set. Otherwise behaves according to the value of null_value_treatment which must be one of 'raise_exception', 'use_json_null', 'delete_key', or 'return_target'. The default is 'use_json_null'.

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

jsonb_set_lax('[{"f1":99,"f2":null},2]', '{0,f3}', null, true, 'return_target')[{"f1": 99, "f2": null}, 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_path_query_first ( target jsonb, path jsonpath [, vars jsonb [, silent boolean ]] ) → jsonb

Returns the first JSON item returned by the JSON path for the specified JSON value. Returns NULL if there are no results. The optional vars and silent arguments act the same as for jsonb_path_exists.

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

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

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

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

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

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

These functions act like their counterparts described above without the _tz suffix, except that these functions support comparisons of date/time values that require timezone-aware conversions. The example below requires interpretation of the date-only value 2015-08-02 as a timestamp with time zone, so the result depends on the current TimeZone setting. Due to this dependency, these functions are marked as stable, which means these functions cannot be used in indexes. Their counterparts are immutable, and so can be used in indexes; but they will throw errors if asked to make such comparisons.

jsonb_path_exists_tz('["2015-08-01 12:00:00-05"]', '$[*] ? (@.datetime() < "2015-08-02".datetime())')t

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

9.16.2. The SQL/JSON Path Language #

SQL/JSON 路径表达式指定要从 JSON 数据中检索的项目,类似于 SQL 访问 XML 时使用的 XPath 表达式。在 PostgreSQL 中,路径表达式实现为 jsonpath 数据类型,并且可以使用 Section 8.14.7 中所述的任何元素。

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 查询函数和运算符将提供的路径表达式传递到 path engine 以进行评估。如果表达式与查询的 JSON 数据匹配,则返回相应的 JSON 项或一组项。路径表达式是用 SQL/JSON 路径语言编写的,可以包括算术表达式和函数。

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.

路径表达式由 jsonpath 数据类型允许的一序列元素组成。路径表达式通常是从左到右求值的,但可以使用括号来更改操作顺序。如果求值成功,则生成一系列 JSON 项,并将求值结果返回给 JSON 查询函数以完成指定的计算。

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.

若要引用正在查询的 JSON 值(即 context item),请在路径表达式中使用 $ 变量。其后可以跟随一个或多个 accessor operators,它们逐层进入 JSON 结构以检索上下文项目子项目。随后的每个运算符都处理前一个评估步骤的结果。

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.

例如,假设您有一些来自 GPS 跟踪器的 JSON 数据,您想要对它们进行解析,例如:

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
      }
    ]
  }
}

要检索可用音轨段,您需要使用 ._key_ 访问符运算符来向下导航周围的 JSON 对象:

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

$.track.segments

若要检索数组的内容,您通常会使用 [*] 运算符。例如,以下路径将返回所有可用跟踪段的位置坐标:

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

若仅返回第一段的坐标,您可以在 [] 访问运算符中指定对应的下标。回想一下,JSON 数组的索引是从 0 开始的:

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

可以通过 Section 9.16.2.2 中列出的一个或多个 jsonpath 运算符和方法来处理每个路径评估步骤的结果。每个方法名前面都必须加一个句点。例如,您可以获取一个数组的大小:

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()

以下 Section 9.16.2.2 中显示了在路径表达式内使用 jsonpath 运算符和方法的更多示例。

More examples of using jsonpath operators and methods within path expressions appear below in Section 9.16.2.2.

在定义路径时,您还可以使用一个或多个 filter expressions,它们与 SQL 中的 WHERE 从句类似。筛选表达式以问号开头,并在括号中提供条件:

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)

筛选表达式必须在应用它的路径计算步骤之后立即编写。该步骤的结果将经过筛选,仅包括那些满足提供的条件的项。SQL/JSON 定义了三值逻辑,因此条件可以是 truefalseunknownunknown 值与 SQL NULL 扮演相同的角色,可以使用 is unknown 谓词对它进行测试。进一步的路径计算步骤仅使用筛选表达式返回 true 的那些项。

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.

可在筛选表达式中使用的函数和运算符列在 Table 9.51 中。在筛选表达式内,@ 变量表示正在筛选的值(即前一个路径步骤的一个结果)。您可以在 @ 后面编写访问运算符来检索组件项。

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.

例如,假设您想要检索所有高于 130 的心率值。您可以使用以下表达式来实现:

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)

要获取具有此类值段的开始时间,您需要在返回开始时间之前过滤出不相关的段,因此筛选表达式应用于前一步,并且条件中使用的路径不同:

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"

如果需要,您可以按顺序使用多个筛选表达式。例如,以下表达式选择所有轨迹段中的开始时间,这些轨迹段包含具有相关坐标和高心率值的位置:

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"

还允许在不同嵌套级别使用筛选表达式。以下示例首先按位置筛选所有段,然后为这些段返回较高的最高心率值(如果可用):

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)

您还可以在彼此内部嵌套筛选表达式:

You can also nest filter expressions within each other:

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

此表达式返回轨迹的大小,如果它包含具有高心率值的任何段,否则返回一个空序列。

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

PostgreSQL 对 SQL/JSON 路径语言的实现与 SQL/JSON 标准有以下差异:

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

9.16.2.1. Strict and Lax Modes #

当您查询 JSON 数据时,路径表达式可能与实际 JSON 数据结构不匹配。尝试访问对象的不存在的成员或数组的元素会导致结构错误。SQL/JSON 路径表达式有两种处理结构错误的方式:

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:

如果 JSON 数据不符合预期的模式,宽松模式有助于匹配 JSON 文档结构和路径表达式。如果运算数不满足特定操作的要求,则它可以自动包装为 SQL/JSON 数组或解包,方法是在执行此操作之前将其实例转换为 SQL/JSON 序列。此外,在宽松模式中,比较运算符会自动解包它们的运算数,因此您可以直接比较 SQL/JSON 数组。大小为 1 的数组被认为等于其唯一元素。只有在以下情况下才不执行自动解包:

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:

例如,在查询上述 GPS 数据时,在使用宽松模式时,您可以忽略它存储段的数组这一事实:

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

在严格模式下,指定路径必须与查询的 JSON 文档的结构完全匹配,才能返回 SQL/JSON 项,因此使用此路径表达式会导致错误。要获得与宽松模式相同的结果,必须明确解包 segments 数组:

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

在使用宽松模式时,.** 访问器可能会导致令人惊讶的结果。例如,以下查询选择每个 HR 值两次:

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

lax $.**.HR

这是因为 .* 访问器同时选择了 segments 数组及其每个元素,而 .HR 访问器在使用宽松模式时自动解包数组。为避免令人惊讶的结果,我们建议仅在严格模式下使用 .* 访问器。以下查询仅选择每个 HR 值一次:

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

9.16.2.2. SQL/JSON Path Operators and Methods #

Table 9.50 显示了 jsonpath 中可用的运算符和方法。请注意,虽然一元运算符和方法可以应用于由前一个路径步骤产生的多个值,但二元运算符(加法等)只能应用于单个值。

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

Table 9.50. jsonpath Operators and Methods

Operator/Method

Description

Example(s)

number + numbernumber

Addition

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

+ numbernumber

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 - numbernumber

Subtraction

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

- numbernumber

Negation; unlike subtraction, this can iterate over multiple values

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

number * numbernumber

Multiplication

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

number / numbernumber

Division

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

number % numbernumber

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}]

Note

datetime()datetime(_template)_ 方法的结果类型可以是 datetimetztimetimestamptztimestamp。两种方法都动态地确定其结果类型。

The result type of the datetime() and datetime(_template)_ methods can be date, timetz, time, timestamptz, or timestamp. Both methods determine their result type dynamically.

datetime() 方法循序渐进地尝试匹配其输入字符串与 datetimetztimetimestamptztimestamp 的 ISO 格式。它在第一个匹配的格式上停止并发出相应的数据类型。

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.

datetime(_template)_ 方法根据提供模板字符串中使用的字段确定结果类型。

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

datetime()_和 _datetime(_template)_) 方法使用与 _to_timestamp_SQL 函数相同的解析规则(参见 Section 9.8),但有三个例外。第一,这些方法不允许不匹配的模板模式。第二,模板字符串中只允许使用以下分隔符:减号、句点、斜杠(反斜杠)、逗号、撇号、分号、冒号和空格。第三,模板字符串中的分隔符必须与输入字符串完全匹配。

The datetime() and datetime(_template)_ methods use the same parsing rules as the 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.

如果需要比较不同的日期/时间类型,则会应用隐式强制转换。date_值可以强制转换为 _timestamp_或 _timestamptztimestamp_可以强制转换为 _timestamptz,而 time_可以强制转换为 _timetz。但是,除了第一个转换之外,其他所有转换都依赖于当前 TimeZone设置,因此只能在支持时区的 _jsonpath_函数中执行。

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显示了可用的筛选器表达式元素。

Table 9.51 shows the available filter expression elements.

Table 9.51. jsonpath Filter Expression Elements

Table 9.51. 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}

nullvalue

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 9.16.2.3).

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')[]

9.16.2.3. SQL/JSON Regular Expressions #

SQL/JSON 路径表达式允许使用 like_regex 过滤器将文本与正则表达式进行匹配。例如, 以下 SQL/JSON 路径查询将不区分大小写地匹配数组中以英语元音开头的所有字符串:

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")

可选的 flag 字符串可以包含一个或多个用于不区分大小写匹配的字符 i,用于允许 ^$ 换行匹配的 m,用于允许 . 换行匹配的 s 以及用于引用整个模式(将行为简化为简单的子字符串匹配)的 q

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).

SQL/JSON 标准借用其对于 LIKE_REGEX 操作符的正则表达式的定义,而该操作符又使用 XQuery 标准。PostgreSQL 目前不支持 LIKE_REGEX 操作符。因此, like_regex 过滤器是使用 Section 9.7.3 中描述的 POSIX 正则表达式引擎实现的。这会产生各种小偏差,使其偏离标准 SQL/JSON 行为,这些偏差已在 Section 9.7.3.8 中编入目录。但是请注意,此处描述的标记字母不兼容不适用于 SQL/JSON,因为它将 XQuery 标记字母转换为匹配 POSIX 引擎的字母。

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.

请记住, like_regex 的模式参数是 JSON 路径字符串文本,根据 Section 8.14.7 中给出的规则编写。这意味着,正则表达式中想要使用的任何反斜杠都必须加倍。例如,要匹配仅包含数字的根文档的字符串值:

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:

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