postgresql/contrib/tablefunc

/*
 * tablefunc
 *
 * Sample to demonstrate C functions which return setof scalar
 * and setof composite.
 * Joe Conway <mail@joeconway.com>
 * And contributors:
 * Nabil Sayegh <postgresql@e-trolley.de>
 *
 * Copyright (c) 2002-2006, 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)
      - 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)
      - 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.

    crosstab(text sql, N int)
      - obsolete version of crosstab()
      - the argument N is now ignored, since the number of value columns
        is always determined by the calling query

    connectby(text relname, text keyid_fld, text parent_keyid_fld
                [, text orderby_fld], text start_with, int max_depth
								[, text branch_delim])
      - returns keyid, parent_keyid, level, and an optional branch string
        and an optional serial column for ordering siblings
      - requires anonymous composite type syntax in the FROM clause. See
        the instructions in the documentation below.

Documentation
==================================================================
Name

normal_rand(int, float8, float8) - returns a set of normally
       distributed float8 values

Synopsis

normal_rand(int numvals, float8 mean, float8 stddev)

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

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);
     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.  row_name and value must be of type text.

    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 TYPE tablefunc_crosstab_N AS (
        row_name TEXT,
        category_1 TEXT,
        category_2 TEXT,
            .
            .
            .
        category_N TEXT
    );

     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.  See below for
     details.


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) - returns a set of row_names plus category value columns

Synopsis

crosstab(text sql)

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

    Obsolete argument; ignored if supplied (formerly this had to match
    the number of category columns determined by the calling query)

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(sql) 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 by the column definition
     provided in the FROM clause.  The FROM clause must define one
     row_name column (of the same datatype as the first result column
     of the sql query) followed by N category columns (of the same
     datatype as the third result column of the sql query).  You can
     set up as many category columns as you wish.

  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. You can avoid always having to write out a FROM clause that defines the
     output columns by setting up a custom crosstab function that has
     the desired output row type wired into its definition.

     There are two ways you can set up a custom crosstab function:

     A. Create a composite type to define your return type, similar to the
     examples in the installation script. Then define a unique function
     name accepting one text parameter and returning setof your_type_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 TYPE my_crosstab_float8_5_cols AS (
          row_name TEXT,
          category_1 FLOAT8,
          category_2 FLOAT8,
          category_3 FLOAT8,
          category_4 FLOAT8,
          category_5 FLOAT8
      );

      CREATE OR REPLACE FUNCTION crosstab_float8_5_cols(text)
        RETURNS setof my_crosstab_float8_5_cols
        AS '$libdir/tablefunc','crosstab' LANGUAGE C STABLE STRICT;

      B. Use OUT parameters to define the return type implicitly.
      The same example could also be done this way:

      CREATE OR REPLACE FUNCTION crosstab_float8_5_cols(IN text,
          OUT row_name TEXT,
          OUT category_1 FLOAT8,
          OUT category_2 FLOAT8,
          OUT category_3 FLOAT8,
          OUT category_4 FLOAT8,
          OUT category_5 FLOAT8)
        RETURNS setof record
        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 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.

  6. You can create predefined functions to avoid having to write out
     the result column names/types in each query.  See the examples
     for crosstab(text).


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], text, text, int[, text]) - returns a set
    representing a hierarchy (tree structure)

Synopsis

connectby(text relname, text keyid_fld, text parent_keyid_fld
            [, text orderby_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

  orderby_fld

    If optional ordering of siblings is desired:
    Name of the field to order siblings

  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);
			
		- or -

    SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'pos', 'row2', 0, '~')
      AS t(keyid text, parent_keyid text, level int, branch text, pos int);

		- or -

    SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'pos', 'row2', 0)
      AS t(keyid text, parent_keyid text, level int, pos 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.

  6. If sorting of siblings is desired, the orderby_fld input parameter *and*
     a name for the resulting serial field (type INT32) in the query column
     definition must be given.

Example usage

CREATE TABLE connectby_tree(keyid text, parent_keyid text, pos int);

INSERT INTO connectby_tree VALUES('row1',NULL, 0);
INSERT INTO connectby_tree VALUES('row2','row1', 0);
INSERT INTO connectby_tree VALUES('row3','row1', 0);
INSERT INTO connectby_tree VALUES('row4','row2', 1);
INSERT INTO connectby_tree VALUES('row5','row2', 0);
INSERT INTO connectby_tree VALUES('row6','row4', 0);
INSERT INTO connectby_tree VALUES('row7','row3', 0);
INSERT INTO connectby_tree VALUES('row8','row6', 0);
INSERT INTO connectby_tree VALUES('row9','row5', 0);

-- with branch, without orderby_fld
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, without orderby_fld
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)

-- with branch, with orderby_fld (notice that row5 comes before row4)
SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'pos', 'row2', 0, '~')
 AS t(keyid text, parent_keyid text, level int, branch text, pos int) ORDER BY t.pos;
 keyid | parent_keyid | level |       branch        | pos 
-------+--------------+-------+---------------------+-----
 row2  |              |     0 | row2                |   1
 row5  | row2         |     1 | row2~row5           |   2
 row9  | row5         |     2 | row2~row5~row9      |   3
 row4  | row2         |     1 | row2~row4           |   4
 row6  | row4         |     2 | row2~row4~row6      |   5
 row8  | row6         |     3 | row2~row4~row6~row8 |   6
(6 rows)

-- without branch, with orderby_fld (notice that row5 comes before row4)
SELECT * FROM connectby('connectby_tree', 'keyid', 'parent_keyid', 'pos', 'row2', 0)
 AS t(keyid text, parent_keyid text, level int, pos int) ORDER BY t.pos;
 keyid | parent_keyid | level | pos
-------+--------------+-------+-----
 row2  |              |     0 |   1
 row5  | row2         |     1 |   2
 row9  | row5         |     2 |   3
 row4  | row2         |     1 |   4
 row6  | row4         |     2 |   5
 row8  | row6         |     3 |   6
(6 rows)

==================================================================
-- Joe Conway