Dynamically convert hstore keys into columns for an unknown set of keys
This can be done, very efficiently, too. Not in a single statement, though, since SQL demands to know the return type at call time. So you need two steps. The solution involves a number of advanced techniques ...
Assuming the same table as @Denver in his answer:
CREATE TABLE hstore_test (
id serial PRIMARY KEY
, hstore_col hstore
);
Solution 1: Simple SELECT
After I wrote the crosstab solution below it struck me that a simple "brute force" solution is probably faster. Basically, the query @Denver already posted, built dynamically:
Step 1a: Generate query
SELECT format(
'SELECT id, h->%s
FROM (SELECT id, hstore_col AS h FROM hstore_test) t;'
, string_agg(quote_literal(key) || ' AS ' || quote_ident(key), ', h->')
) AS sql
FROM (
SELECT DISTINCT key
FROM hstore_test, skeys(hstore_col) key
ORDER BY 1
) sub;
The subquery (SELECT id, hstore_col AS h FROM hstore_test)
is just to get in the column alias h
for your hstore
column.
Step 1b: Execute query
This generates a query of the form:
SELECT id, h->'key1' AS key1, h->'key2' AS key2, h->'key3' AS key3
FROM (SELECT id, hstore_col AS h FROM hstore_test) t;
Result:
id | key1 | key2 | key3
----+-------+-------+-------
1 | val11 | val12 | val13
2 | val21 | val22 |
3 | | | -- for a row where hstore_col IS NULL
Solution 2: crosstab()
For lots of keys this may perform better. Probably not. You'll have to test. Result is the same as for solution 1.
You need the additional extension tablefunc
which provides the crosstab()
function. Read this first if you are not familiar:
- PostgreSQL Crosstab Query
Step 2a: Generate query
SELECT format(
$s$SELECT * FROM crosstab(
$$SELECT h.id, kv.*
FROM hstore_test h, each(hstore_col) kv
ORDER BY 1, 2$$
, $$SELECT unnest(%L::text[])$$
) AS t(id int, %s text);
$s$
, array_agg(key) -- escapes strings automatically
, string_agg(quote_ident(key), ' text, ') -- needs escaping!
) AS sql
FROM (
SELECT DISTINCT key
FROM hstore_test, skeys(hstore_col) key
ORDER BY 1
) sub;
Note the nested levels of dollar-quoting.
I use this explicit form in the main query instead of the short CROSS JOIN
in the auxiliary query to preserve rows with empty or NULL hstore
values:
LEFT JOIN LATERAL each(hstore_col) kv ON TRUE
- What is the difference between LATERAL and a subquery in PostgreSQL?
Related:
- Dynamic alternative to pivot with CASE and GROUP BY
Step 2b: Execute query
This generates a query of the form:
SELECT * FROM crosstab(
$$SELECT h.id, kv.*
FROM hstore_test h
LEFT JOIN LATERAL each(hstore_col) kv ON TRUE
ORDER BY 1, 2$$
, $$SELECT unnest('{key1,key2,key3}'::text[])$$
) AS t(id int, key1 text, key2 text, key3 text);
You may want to inspect it for plausibility before running the first time. This should deliver optimized performance.
Notes
Both solutions work for any number of keys up to the physical limit of ~ 1600 columns in a Postgres table.
Both also work for keys of any shape or form up to the maximum length for identifiers, which is 63 bytes per default.
Besides the hstore function
each()
that was already mentioned by s.m., I also use the related functionskeys()
to identify keys.Be sure to quote column names correctly to avoid possible SQL injection attacks by way of maliciously formed key names. I take care of that with
quote_literal()
andquote_ident()
.
I realize I'm a bit late—and by now you sure have it figured out—but, seeing the comment you left on Denver Timothy's answer, I thought I would leave an answer for everybody else:
select (each(hstore_col)).key from hstore_test;
This will create a row for each key
contained in hstore_col
, so you won't need to know what the keys are beforehand.
You'll want to use the ->
operator on the column (see here).
Records without the same key in other records will show as NULL.
create table hstore_test (id serial, hstore_col hstore);
insert into hstore_test (hstore_col) values ('key1=>val11, key2=>val12, key3=>val13'), ('key1=>val21, key2=>val22');
select hstore_col->'key1' as key1, hstore_col->'key2' as key2, hstore_col->'key3' as key3 from hstore_test;
┌───────┬───────┬───────┐
│ key1 │ key2 │ key3 │
├───────┼───────┼───────┤
│ val11 │ val12 │ val13 │
│ val21 │ val22 │ NULL │
└───────┴───────┴───────┘
(2 rows)
Here is a similar answer.