hstore
PostgreSQL 9.6.9 Documentation | |||
---|---|---|---|
Prev | Up | Appendix F. Additional Supplied Modules | Next |
This module implements the hstore data type for storing sets of key/value pairs within a single PostgreSQL value. This can be useful in various scenarios, such as rows with many attributes that are rarely examined, or semi-structured data. Keys and values are simply text strings.
F.16.1. hstore External Representation
The text representation of an hstore , used for input and output, includes zero or more key => value pairs separated by commas. Some examples:
k => v foo => bar, baz => whatever "1-a" => "anything at all"
The order of the pairs is not significant (and may not be reproduced on output). Whitespace between pairs or around the => sign is ignored. Double-quote keys and values that include whitespace, commas, = s or > s. To include a double quote or a backslash in a key or value, escape it with a backslash.
Each key in an hstore is unique. If you declare an hstore with duplicate keys, only one will be stored in the hstore and there is no guarantee as to which will be kept:
SELECT 'a=>1,a=>2'::hstore; hstore ---------- "a"=>"1"
A value (but not a key) can be an SQL NULL . For example:
key => NULL
The NULL keyword is case-insensitive. Double-quote the NULL to treat it as the ordinary string "NULL" .
Note: Keep in mind that the hstore text format, when used for input, applies before any required quoting or escaping. If you are passing an hstore literal via a parameter, then no additional processing is needed. But if you're passing it as a quoted literal constant, then any single-quote characters and (depending on the setting of the standard_conforming_strings configuration parameter) backslash characters need to be escaped correctly. See Section 4.1.2.1 for more on the handling of string constants.
On output, double quotes always surround keys and values, even when it's not strictly necessary.
F.16.2. hstore Operators and Functions
The operators provided by the hstore module are shown in Table F-8 , the functions in Table F-9 .
Table F-8. hstore Operators
Operator | Description | Example | Result |
---|---|---|---|
hstore -> text | get value for key ( NULL if not present) | 'a=>x, b=>y'::hstore -> 'a' | x |
hstore -> text[] | get values for keys ( NULL if not present) | 'a=>x, b=>y, c=>z'::hstore -> ARRAY['c','a'] | {"z","x"} |
hstore || hstore | concatenate hstore s | 'a=>b, c=>d'::hstore || 'c=>x, d=>q'::hstore | "a"=>"b", "c"=>"x", "d"=>"q" |
hstore ? text | does hstore contain key? | 'a=>1'::hstore ? 'a' | t |
hstore ?& text[] | does hstore contain all specified keys? | 'a=>1,b=>2'::hstore ?& ARRAY['a','b'] | t |
hstore ?| text[] | does hstore contain any of the specified keys? | 'a=>1,b=>2'::hstore ?| ARRAY['b','c'] | t |
hstore @> hstore | does left operand contain right? | 'a=>b, b=>1, c=>NULL'::hstore @> 'b=>1' | t |
hstore <@ hstore | is left operand contained in right? | 'a=>c'::hstore <@ 'a=>b, b=>1, c=>NULL' | f |
hstore - text | delete key from left operand | 'a=>1, b=>2, c=>3'::hstore - 'b'::text | "a"=>"1", "c"=>"3" |
hstore - text[] | delete keys from left operand | 'a=>1, b=>2, c=>3'::hstore - ARRAY['a','b'] | "c"=>"3" |
hstore - hstore | delete matching pairs from left operand | 'a=>1, b=>2, c=>3'::hstore - 'a=>4, b=>2'::hstore | "a"=>"1", "c"=>"3" |
record #= hstore | replace fields in record with matching values from hstore | see Examples section | |
%% hstore | convert hstore to array of alternating keys and values | %% 'a=>foo, b=>bar'::hstore | {a,foo,b,bar} |
%# hstore | convert hstore to two-dimensional key/value array | %# 'a=>foo, b=>bar'::hstore | {{a,foo},{b,bar}} |
Note: Prior to PostgreSQL 8.2, the containment operators @> and <@ were called @ and ~ , respectively. These names are still available, but are deprecated and will eventually be removed. Notice that the old names are reversed from the convention formerly followed by the core geometric data types!
Table F-9. hstore Functions
Function | Return Type | Description | Example | Result |
---|---|---|---|---|
hstore(record)
|
hstore | construct an hstore from a record or row | hstore(ROW(1,2)) | f1=>1,f2=>2 |
hstore(text[])
|
hstore | construct an hstore from an array, which may be either a key/value array, or a two-dimensional array | hstore(ARRAY['a','1','b','2']) || hstore(ARRAY[['c','3'],['d','4']]) | a=>1, b=>2, c=>3, d=>4 |
hstore(text[], text[])
|
hstore | construct an hstore from separate key and value arrays | hstore(ARRAY['a','b'], ARRAY['1','2']) | "a"=>"1","b"=>"2" |
hstore(text, text)
|
hstore | make single-item hstore | hstore('a', 'b') | "a"=>"b" |
akeys(hstore)
|
text[] | get hstore 's keys as an array | akeys('a=>1,b=>2') | {a,b} |
skeys(hstore)
|
setof text | get hstore 's keys as a set | skeys('a=>1,b=>2') |
a b |
avals(hstore)
|
text[] | get hstore 's values as an array | avals('a=>1,b=>2') | {1,2} |
svals(hstore)
|
setof text | get hstore 's values as a set | svals('a=>1,b=>2') |
1 2 |
hstore_to_array(hstore)
|
text[] | get hstore 's keys and values as an array of alternating keys and values | hstore_to_array('a=>1,b=>2') | {a,1,b,2} |
hstore_to_matrix(hstore)
|
text[] | get hstore 's keys and values as a two-dimensional array | hstore_to_matrix('a=>1,b=>2') | {{a,1},{b,2}} |
hstore_to_json(hstore)
|
json | get hstore as a json value, converting all non-null values to JSON strings | hstore_to_json('"a key"=>1, b=>t, c=>null, d=>12345, e=>012345, f=>1.234, g=>2.345e+4') | {"a key": "1", "b": "t", "c": null, "d": "12345", "e": "012345", "f": "1.234", "g": "2.345e+4"} |
hstore_to_jsonb(hstore)
|
jsonb | get hstore as a jsonb value, converting all non-null values to JSON strings | hstore_to_jsonb('"a key"=>1, b=>t, c=>null, d=>12345, e=>012345, f=>1.234, g=>2.345e+4') | {"a key": "1", "b": "t", "c": null, "d": "12345", "e": "012345", "f": "1.234", "g": "2.345e+4"} |
hstore_to_json_loose(hstore)
|
json | get hstore as a json value, but attempt to distinguish numerical and Boolean values so they are unquoted in the JSON | hstore_to_json_loose('"a key"=>1, b=>t, c=>null, d=>12345, e=>012345, f=>1.234, g=>2.345e+4') | {"a key": 1, "b": true, "c": null, "d": 12345, "e": "012345", "f": 1.234, "g": 2.345e+4} |
hstore_to_jsonb_loose(hstore)
|
jsonb | get hstore as a jsonb value, but attempt to distinguish numerical and Boolean values so they are unquoted in the JSON | hstore_to_jsonb_loose('"a key"=>1, b=>t, c=>null, d=>12345, e=>012345, f=>1.234, g=>2.345e+4') | {"a key": 1, "b": true, "c": null, "d": 12345, "e": "012345", "f": 1.234, "g": 2.345e+4} |
slice(hstore, text[])
|
hstore | extract a subset of an hstore | slice('a=>1,b=>2,c=>3'::hstore, ARRAY['b','c','x']) | "b"=>"2", "c"=>"3" |
each(hstore)
|
setof(key text, value text) | get hstore 's keys and values as a set | select * from each('a=>1,b=>2') |
key | value -----+------- a | 1 b | 2 |
exist(hstore,text)
|
boolean | does hstore contain key? | exist('a=>1','a') | t |
defined(hstore,text)
|
boolean | does hstore contain non- NULL value for key? | defined('a=>NULL','a') | f |
delete(hstore,text)
|
hstore | delete pair with matching key | delete('a=>1,b=>2','b') | "a"=>"1" |
delete(hstore,text[])
|
hstore | delete pairs with matching keys | delete('a=>1,b=>2,c=>3',ARRAY['a','b']) | "c"=>"3" |
delete(hstore,hstore)
|
hstore | delete pairs matching those in the second argument | delete('a=>1,b=>2','a=>4,b=>2'::hstore) | "a"=>"1" |
populate_record(record,hstore)
|
record | replace fields in record with matching values from hstore | see Examples section |
Note: The function
hstore_to_json
is used when an hstore value is cast to json . Likewise,hstore_to_jsonb
is used when an hstore value is cast to jsonb .
Note: The function
populate_record
is actually declared with anyelement , not record , as its first argument, but it will reject non-record types with a run-time error.
F.16.3. Indexes
hstore has GiST and GIN index support for the @> , ? , ?& and ?| operators. For example:
CREATE INDEX hidx ON testhstore USING GIST (h); CREATE INDEX hidx ON testhstore USING GIN (h);
hstore also supports btree or hash indexes for the = operator. This allows hstore columns to be declared UNIQUE , or to be used in GROUP BY , ORDER BY or DISTINCT expressions. The sort ordering for hstore values is not particularly useful, but these indexes may be useful for equivalence lookups. Create indexes for = comparisons as follows:
CREATE INDEX hidx ON testhstore USING BTREE (h); CREATE INDEX hidx ON testhstore USING HASH (h);
F.16.4. Examples
Add a key, or update an existing key with a new value:
UPDATE tab SET h = h || hstore('c', '3');
Delete a key:
UPDATE tab SET h = delete(h, 'k1');
Convert a record to an hstore :
CREATE TABLE test (col1 integer, col2 text, col3 text); INSERT INTO test VALUES (123, 'foo', 'bar'); SELECT hstore(t) FROM test AS t; hstore --------------------------------------------- "col1"=>"123", "col2"=>"foo", "col3"=>"bar" (1 row)
Convert an hstore to a predefined record type:
CREATE TABLE test (col1 integer, col2 text, col3 text); SELECT * FROM populate_record(null::test, '"col1"=>"456", "col2"=>"zzz"'); col1 | col2 | col3 ------+------+------ 456 | zzz | (1 row)
Modify an existing record using the values from an hstore :
CREATE TABLE test (col1 integer, col2 text, col3 text); INSERT INTO test VALUES (123, 'foo', 'bar'); SELECT (r).* FROM (SELECT t #= '"col3"=>"baz"' AS r FROM test t) s; col1 | col2 | col3 ------+------+------ 123 | foo | baz (1 row)
F.16.5. Statistics
The hstore type, because of its intrinsic liberality, could contain a lot of different keys. Checking for valid keys is the task of the application. The following examples demonstrate several techniques for checking keys and obtaining statistics.
Simple example:
SELECT * FROM each('aaa=>bq, b=>NULL, ""=>1');
Using a table:
SELECT (each(h)).key, (each(h)).value INTO stat FROM testhstore;
Online statistics:
SELECT key, count(*) FROM (SELECT (each(h)).key FROM testhstore) AS stat GROUP BY key ORDER BY count DESC, key; key | count -----------+------- line | 883 query | 207 pos | 203 node | 202 space | 197 status | 195 public | 194 title | 190 org | 189 ...................
F.16.6. Compatibility
As of PostgreSQL 9.0, hstore uses a different internal representation than previous versions. This presents no obstacle for dump/restore upgrades since the text representation (used in the dump) is unchanged.
In the event of a binary upgrade, upward compatibility is maintained by having the new code recognize old-format data. This will entail a slight performance penalty when processing data that has not yet been modified by the new code. It is possible to force an upgrade of all values in a table column by doing an UPDATE statement as follows:
UPDATE tablename SET hstorecol = hstorecol || '';
Another way to do it is:
ALTER TABLE tablename ALTER hstorecol TYPE hstore USING hstorecol || '';
The ALTER TABLE method requires an exclusive lock on the table, but does not result in bloating the table with old row versions.
F.16.7. Transforms
Additional extensions are available that implement transforms for the hstore type for the languages PL/Perl and PL/Python. The extensions for PL/Perl are called hstore_plperl and hstore_plperlu , for trusted and untrusted PL/Perl. If you install these transforms and specify them when creating a function, hstore values are mapped to Perl hashes. The extensions for PL/Python are called hstore_plpythonu , hstore_plpython2u , and hstore_plpython3u (see Section 44.1 for the PL/Python naming convention). If you use them, hstore values are mapped to Python dictionaries.
F.16.8. Authors
Oleg Bartunov
<
oleg@sai.msu.su
>
, Moscow, Moscow University, Russia
Teodor Sigaev
<
teodor@sigaev.ru
>
, Moscow, Delta-Soft Ltd., Russia
Additional enhancements by Andrew Gierth
<
andrew@tao11.riddles.org.uk
>
,
United Kingdom