tablefunc extension
This page documents the preview version (v2.23). Preview includes features under active development and is for development and testing only. For production, use the stable version (v2024.1). To learn more, see Versioning.
The tablefunc module includes various functions that return tables (that is, multiple rows).
CREATE EXTENSION tablefunc;
CREATE TABLE t(k int primary key, v double precision);
PREPARE insert_k_v_pairs(int) AS
INSERT INTO t(k, v)
SELECT
generate_series(1, $1),
normal_rand($1, 1000.0, 10.0);
Test it as follows:
DELETE FROM t;
EXECUTE insert_k_v_pairs(10);
SELECT k, to_char(v, '9999.99') AS v
FROM t
ORDER BY k;
You'll see results similar to the following:
k | v
----+----------
1 | 988.53
2 | 1005.18
3 | 1014.30
4 | 1000.92
5 | 999.51
6 | 1000.94
7 | 1007.45
8 | 991.22
9 | 987.95
10 | 996.57
(10 rows)
Every time you repeat the test, you'll see different generated values for v
.
For another example that uses normal_rand()
, refer to Analyzing a normal distribution with percent_rank(), cume_dist() and ntile(). It populates a table with a large number (say 100,000) of rows and displays the outcome as a histogram that clearly shows the familiar bell-curve shape.
tablefunc
also provides the connectby()
, crosstab()
, and crosstabN()
functions.
The connectby()
function displays a hierarchy of the kind that you see in an "employees" table with a reflexive foreign key constraint where "manager_id" refers to "employee_id". Each next deeper level in the tree is indented from its parent following the well-known pattern.
The crosstab()
and crosstabN()
functions produce "pivot" displays. The "N" in crosstabN() indicates the fact that a few, crosstab1()
, crosstab2()
, crosstab3()
, are provided natively by the extension and that you can follow documented steps to create more.