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postgresql/contrib/tablefunc/README.tablefunc
Bruce Momjian 64d0b8b05f Attached is an update to contrib/tablefunc. It implements a new hashed 
version of crosstab. This fixes a major deficiency in real-world use of
the original version. Easiest to undestand with an illustration:

Data:
-------------------------------------------------------------------
select * from cth;
  id | rowid |        rowdt        |   attribute    |      val
----+-------+---------------------+----------------+---------------
   1 | test1 | 2003-03-01 00:00:00 | temperature    | 42
   2 | test1 | 2003-03-01 00:00:00 | test_result    | PASS
   3 | test1 | 2003-03-01 00:00:00 | volts          | 2.6987
   4 | test2 | 2003-03-02 00:00:00 | temperature    | 53
   5 | test2 | 2003-03-02 00:00:00 | test_result    | FAIL
   6 | test2 | 2003-03-02 00:00:00 | test_startdate | 01 March 2003
   7 | test2 | 2003-03-02 00:00:00 | volts          | 3.1234
(7 rows)

Original crosstab:
-------------------------------------------------------------------
SELECT * FROM crosstab(
   'SELECT rowid, attribute, val FROM cth ORDER BY 1,2',4)
AS c(rowid text, temperature text, test_result text, test_startdate
text, volts text);
  rowid | temperature | test_result | test_startdate | volts
-------+-------------+-------------+----------------+--------
  test1 | 42          | PASS        | 2.6987         |
  test2 | 53          | FAIL        | 01 March 2003  | 3.1234
(2 rows)

Hashed crosstab:
-------------------------------------------------------------------
SELECT * FROM crosstab(
   'SELECT rowid, attribute, val FROM cth ORDER BY 1',
   'SELECT DISTINCT attribute FROM cth ORDER BY 1')
AS c(rowid text, temperature int4, test_result text, test_startdate
timestamp, volts float8);
  rowid | temperature | test_result |   test_startdate    | volts
-------+-------------+-------------+---------------------+--------
  test1 |          42 | PASS        |                     | 2.6987
  test2 |          53 | FAIL        | 2003-03-01 00:00:00 | 3.1234
(2 rows)

Notice that the original crosstab slides data over to the left in the
result tuple when it encounters missing data. In order to work around
this you have to be make your source sql do all sorts of contortions
(cartesian join of distinct rowid with distinct attribute; left join
that back to the real source data). The new version avoids this by
building a hash table using a second distinct attribute query.

The new version also allows for "extra" columns (see the README) and
allows the result columns to be coerced into differing datatypes if they
are suitable (as shown above).

In testing a "real-world" data set (69 distinct rowid's, 27 distinct
categories/attributes, multiple missing data points) I saw about a
5-fold improvement in execution time (from about 2200 ms old, to 440 ms
new).

I left the original version intact because: 1) BC, 2) it is probably
slightly faster if you know that you have no missing attributes.

README and regression test adjustments included. If there are no
objections, please apply.

Joe Conway
2003-03-20 06:46:30 +00:00

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/*
* tablefunc
*
* Sample to demonstrate C functions which return setof scalar
* and setof composite.
* Joe Conway <mail@joeconway.com>
*
* Copyright 2002 by PostgreSQL Global Development Group
*
* Permission to use, copy, modify, and distribute this software and its
* documentation for any purpose, without fee, and without a written agreement
* is hereby granted, provided that the above copyright notice and this
* paragraph and the following two paragraphs appear in all copies.
*
* IN NO EVENT SHALL THE AUTHORS OR DISTRIBUTORS BE LIABLE TO ANY PARTY FOR
* DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING
* LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS
* DOCUMENTATION, EVEN IF THE AUTHOR OR DISTRIBUTORS HAVE BEEN ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* THE AUTHORS AND DISTRIBUTORS SPECIFICALLY DISCLAIM ANY WARRANTIES,
* INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY
* AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS
* ON AN "AS IS" BASIS, AND THE AUTHOR AND DISTRIBUTORS HAS NO OBLIGATIONS TO
* PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
*
*/
Version 0.1 (20 July, 2002):
First release
Release Notes:
Version 0.1
- initial release
Installation:
Place these files in a directory called 'tablefunc' under 'contrib' in the
PostgreSQL source tree. Then run:
make
make install
You can use tablefunc.sql to create the functions in your database of choice, e.g.
psql -U postgres template1 < tablefunc.sql
installs following functions into database template1:
normal_rand(int numvals, float8 mean, float8 stddev, int seed)
- returns a set of normally distributed float8 values
crosstabN(text sql)
- returns a set of row_name plus N category value columns
- crosstab2(), crosstab3(), and crosstab4() are defined for you,
but you can create additional crosstab functions per the instructions
in the documentation below.
crosstab(text sql, N int)
- returns a set of row_name plus N category value columns
- requires anonymous composite type syntax in the FROM clause. See
the instructions in the documentation below.
connectby(text relname, text keyid_fld, text parent_keyid_fld,
text start_with, int max_depth [, text branch_delim])
- returns keyid, parent_keyid, level, and an optional branch string
- requires anonymous composite type syntax in the FROM clause. See
the instructions in the documentation below.
Documentation
==================================================================
Name
normal_rand(int, float8, float8, int) - returns a set of normally
distributed float8 values
Synopsis
normal_rand(int numvals, float8 mean, float8 stddev, int seed)
Inputs
numvals
the number of random values to be returned from the function
mean
the mean of the normal distribution of values
stddev
the standard deviation of the normal distribution of values
seed
a seed value for the pseudo-random number generator
Outputs
Returns setof float8, where the returned set of random values are normally
distributed (Gaussian distribution)
Example usage
test=# SELECT * FROM
test=# normal_rand(1000, 5, 3, EXTRACT(SECONDS FROM CURRENT_TIME(0))::int);
normal_rand
----------------------
1.56556322244898
9.10040991424657
5.36957140345079
-0.369151492880995
0.283600703686639
.
.
.
4.82992125404908
9.71308014517282
2.49639286969028
(1000 rows)
Returns 1000 values with a mean of 5 and a standard deviation of 3.
==================================================================
Name
crosstabN(text) - returns a set of row_name plus N category value columns
Synopsis
crosstabN(text sql)
Inputs
sql
A SQL statement which produces the source set of data. The SQL statement
must return one row_name column, one category column, and one value
column.
e.g. provided sql must produce a set something like:
row_name cat value
----------+-------+-------
row1 cat1 val1
row1 cat2 val2
row1 cat3 val3
row1 cat4 val4
row2 cat1 val5
row2 cat2 val6
row2 cat3 val7
row2 cat4 val8
Outputs
Returns setof tablefunc_crosstab_N, which is defined by:
CREATE VIEW tablefunc_crosstab_N AS
SELECT
''::TEXT AS row_name,
''::TEXT AS category_1,
''::TEXT AS category_2,
.
.
.
''::TEXT AS category_N;
for the default installed functions, where N is 2, 3, or 4.
e.g. the provided crosstab2 function produces a set something like:
<== values columns ==>
row_name category_1 category_2
---------+------------+------------
row1 val1 val2
row2 val5 val6
Notes
1. The sql result must be ordered by 1,2.
2. The number of values columns depends on the tuple description
of the function's declared return type.
3. Missing values (i.e. not enough adjacent rows of same row_name to
fill the number of result values columns) are filled in with nulls.
4. Extra values (i.e. too many adjacent rows of same row_name to fill
the number of result values columns) are skipped.
5. Rows with all nulls in the values columns are skipped.
6. The installed defaults are for illustration purposes. You
can create your own return types and functions based on the
crosstab() function of the installed library.
The return type must have a first column that matches the data
type of the sql set used as its source. The subsequent category
columns must have the same data type as the value column of the
sql result set.
Create a VIEW to define your return type, similar to the VIEWS
in the provided installation script. Then define a unique function
name accepting one text parameter and returning setof your_view_name.
For example, if your source data produces row_names that are TEXT,
and values that are FLOAT8, and you want 5 category columns:
CREATE VIEW my_crosstab_float8_5_cols AS
SELECT
''::TEXT AS row_name,
0::FLOAT8 AS category_1,
0::FLOAT8 AS category_2,
0::FLOAT8 AS category_3,
0::FLOAT8 AS category_4,
0::FLOAT8 AS category_5;
CREATE OR REPLACE FUNCTION crosstab_float8_5_cols(text)
RETURNS setof my_crosstab_float8_5_cols
AS '$libdir/tablefunc','crosstab' LANGUAGE 'c' STABLE STRICT;
Example usage
create table ct(id serial, rowclass text, rowid text, attribute text, value text);
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att1','val1');
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att2','val2');
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att3','val3');
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att4','val4');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att1','val5');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att2','val6');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att3','val7');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att4','val8');
select * from crosstab3(
'select rowid, attribute, value
from ct
where rowclass = ''group1''
and (attribute = ''att2'' or attribute = ''att3'') order by 1,2;');
row_name | category_1 | category_2 | category_3
----------+------------+------------+------------
test1 | val2 | val3 |
test2 | val6 | val7 |
(2 rows)
==================================================================
Name
crosstab(text, int) - returns a set of row_name
plus N category value columns
Synopsis
crosstab(text sql, int N)
Inputs
sql
A SQL statement which produces the source set of data. The SQL statement
must return one row_name column, one category column, and one value
column.
e.g. provided sql must produce a set something like:
row_name cat value
----------+-------+-------
row1 cat1 val1
row1 cat2 val2
row1 cat3 val3
row1 cat4 val4
row2 cat1 val5
row2 cat2 val6
row2 cat3 val7
row2 cat4 val8
N
number of category value columns
Outputs
Returns setof record, which must defined with a column definition
in the FROM clause of the SELECT statement, e.g.:
SELECT *
FROM crosstab(sql, 2) AS ct(row_name text, category_1 text, category_2 text);
the example crosstab function produces a set something like:
<== values columns ==>
row_name category_1 category_2
---------+------------+------------
row1 val1 val2
row2 val5 val6
Notes
1. The sql result must be ordered by 1,2.
2. The number of values columns is determined at run-time. The
column definition provided in the FROM clause must provide for
N + 1 columns of the proper data types.
3. Missing values (i.e. not enough adjacent rows of same row_name to
fill the number of result values columns) are filled in with nulls.
4. Extra values (i.e. too many adjacent rows of same row_name to fill
the number of result values columns) are skipped.
5. Rows with all nulls in the values columns are skipped.
Example usage
create table ct(id serial, rowclass text, rowid text, attribute text, value text);
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att1','val1');
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att2','val2');
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att3','val3');
insert into ct(rowclass, rowid, attribute, value) values('group1','test1','att4','val4');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att1','val5');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att2','val6');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att3','val7');
insert into ct(rowclass, rowid, attribute, value) values('group1','test2','att4','val8');
SELECT *
FROM crosstab(
'select rowid, attribute, value
from ct
where rowclass = ''group1''
and (attribute = ''att2'' or attribute = ''att3'') order by 1,2;', 3)
AS ct(row_name text, category_1 text, category_2 text, category_3 text);
row_name | category_1 | category_2 | category_3
----------+------------+------------+------------
test1 | val2 | val3 |
test2 | val6 | val7 |
(2 rows)
==================================================================
Name
crosstab(text, text) - returns a set of row_name, extra, and
category value columns
Synopsis
crosstab(text source_sql, text category_sql)
Inputs
source_sql
A SQL statement which produces the source set of data. The SQL statement
must return one row_name column, one category column, and one value
column. It may also have one or more "extra" columns.
The row_name column must be first. The category and value columns
must be the last two columns, in that order. "extra" columns must be
columns 2 through (N - 2), where N is the total number of columns.
The "extra" columns are assumed to be the same for all rows with the
same row_name. The values returned are copied from the first row
with a given row_name and subsequent values of these columns are ignored
until row_name changes.
e.g. source_sql must produce a set something like:
SELECT row_name, extra_col, cat, value FROM foo;
row_name extra_col cat value
----------+------------+-----+---------
row1 extra1 cat1 val1
row1 extra1 cat2 val2
row1 extra1 cat4 val4
row2 extra2 cat1 val5
row2 extra2 cat2 val6
row2 extra2 cat3 val7
row2 extra2 cat4 val8
category_sql
A SQL statement which produces the distinct set of categories. The SQL
statement must return one category column only. category_sql must produce
at least one result row or an error will be generated. category_sql
must not produce duplicate categories or an error will be generated.
e.g. SELECT DISTINCT cat FROM foo;
cat
-------
cat1
cat2
cat3
cat4
Outputs
Returns setof record, which must be defined with a column definition
in the FROM clause of the SELECT statement, e.g.:
SELECT * FROM crosstab(source_sql, cat_sql)
AS ct(row_name text, extra text, cat1 text, cat2 text, cat3 text, cat4 text);
the example crosstab function produces a set something like:
<== values columns ==>
row_name extra cat1 cat2 cat3 cat4
---------+-------+------+------+------+------
row1 extra1 val1 val2 val4
row2 extra2 val5 val6 val7 val8
Notes
1. source_sql must be ordered by row_name (column 1).
2. The number of values columns is determined at run-time. The
column definition provided in the FROM clause must provide for
the correct number of columns of the proper data types.
3. Missing values (i.e. not enough adjacent rows of same row_name to
fill the number of result values columns) are filled in with nulls.
4. Extra values (i.e. source rows with category not found in category_sql
result) are skipped.
5. Rows with a null row_name column are skipped.
Example usage
create table cth(id serial, rowid text, rowdt timestamp, attribute text, val text);
insert into cth values(DEFAULT,'test1','01 March 2003','temperature','42');
insert into cth values(DEFAULT,'test1','01 March 2003','test_result','PASS');
insert into cth values(DEFAULT,'test1','01 March 2003','volts','2.6987');
insert into cth values(DEFAULT,'test2','02 March 2003','temperature','53');
insert into cth values(DEFAULT,'test2','02 March 2003','test_result','FAIL');
insert into cth values(DEFAULT,'test2','02 March 2003','test_startdate','01 March 2003');
insert into cth values(DEFAULT,'test2','02 March 2003','volts','3.1234');
SELECT * FROM crosstab
(
'SELECT rowid, rowdt, attribute, val FROM cth ORDER BY 1',
'SELECT DISTINCT attribute FROM cth ORDER BY 1'
)
AS
(
rowid text,
rowdt timestamp,
temperature int4,
test_result text,
test_startdate timestamp,
volts float8
);
rowid | rowdt | temperature | test_result | test_startdate | volts
-------+--------------------------+-------------+-------------+--------------------------+--------
test1 | Sat Mar 01 00:00:00 2003 | 42 | PASS | | 2.6987
test2 | Sun Mar 02 00:00:00 2003 | 53 | FAIL | Sat Mar 01 00:00:00 2003 | 3.1234
(2 rows)
==================================================================
Name
connectby(text, text, text, text, int[, text]) - returns a set
representing a hierarchy (tree structure)
Synopsis
connectby(text relname, text keyid_fld, text parent_keyid_fld,
text start_with, int max_depth [, text branch_delim])
Inputs
relname
Name of the source relation
keyid_fld
Name of the key field
parent_keyid_fld
Name of the key_parent field
start_with
root value of the tree input as a text value regardless of keyid_fld type
max_depth
zero (0) for unlimited depth, otherwise restrict level to this depth
branch_delim
If optional branch value is desired, this string is used as the delimiter.
When not provided, a default value of '~' is used for internal
recursion detection only, and no "branch" field is returned.
Outputs
Returns setof record, which must defined with a column definition
in the FROM clause of the SELECT statement, e.g.:
SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'row2', 0, '~')
AS t(keyid text, parent_keyid text, level int, branch text);
- or -
SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'row2', 0)
AS t(keyid text, parent_keyid text, level int);
Notes
1. keyid and parent_keyid must be the same data type
2. The column definition *must* include a third column of type INT4 for
the level value output
3. If the branch field is not desired, omit both the branch_delim input
parameter *and* the branch field in the query column definition. Note
that when branch_delim is not provided, a default value of '~' is used
for branch_delim for internal recursion detection, even though the branch
field is not returned.
4. If the branch field is desired, it must be the fourth column in the query
column definition, and it must be type TEXT.
5. The parameters representing table and field names must include double
quotes if the names are mixed-case or contain special characters.
Example usage
CREATE TABLE connectby_tree(keyid text, parent_keyid text);
INSERT INTO connectby_tree VALUES('row1',NULL);
INSERT INTO connectby_tree VALUES('row2','row1');
INSERT INTO connectby_tree VALUES('row3','row1');
INSERT INTO connectby_tree VALUES('row4','row2');
INSERT INTO connectby_tree VALUES('row5','row2');
INSERT INTO connectby_tree VALUES('row6','row4');
INSERT INTO connectby_tree VALUES('row7','row3');
INSERT INTO connectby_tree VALUES('row8','row6');
INSERT INTO connectby_tree VALUES('row9','row5');
-- with branch
SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'row2', 0, '~')
AS t(keyid text, parent_keyid text, level int, branch text);
keyid | parent_keyid | level | branch
-------+--------------+-------+---------------------
row2 | | 0 | row2
row4 | row2 | 1 | row2~row4
row6 | row4 | 2 | row2~row4~row6
row8 | row6 | 3 | row2~row4~row6~row8
row5 | row2 | 1 | row2~row5
row9 | row5 | 2 | row2~row5~row9
(6 rows)
-- without branch
SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'row2', 0)
AS t(keyid text, parent_keyid text, level int);
keyid | parent_keyid | level
-------+--------------+-------
row2 | | 0
row4 | row2 | 1
row6 | row4 | 2
row8 | row6 | 3
row5 | row2 | 1
row9 | row5 | 2
(6 rows)
==================================================================
-- Joe Conway
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