tablefunc tablefunc provides functions to convert query rows into fields. Function Returns Comments 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. normal_rand(int numvals, float8 mean, float8 stddev) RETURNS SETOF float8 Where numvals is the number of values to be returned from the function. mean is the mean of the normal distribution of values and stddev is the standard deviation of the normal distribution of values. Returns a float8 set of random values normally distributed (Gaussian distribution). Example: 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. crosstabN(text sql) The sql parameter is 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. The function returns a set of row_name plus N category value columns. 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 The returned value is a SETOF table_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 The sql result must be ordered by 1,2. The number of values columns depends on the tuple description of the function's declared return type. 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. Extra values (i.e. too many adjacent rows of same row_name to fill the number of result values columns) are skipped. Rows with all nulls in the values columns are skipped. 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: 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) crosstab(text sql) crosstab(text sql, int N) The sql parameter is 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. N is an obsolete argument; ignored if supplied (formerly this had to match the number of category columns determined by the calling query). 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 Returns a 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 Note that it follows these rules: The sql result must be ordered by 1,2. 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. 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. Extra values (i.e. too many adjacent rows of same row_name to fill the number of result values columns) are skipped. Rows with all nulls in the values columns are skipped. 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: 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 '$libdir/tablefunc','crosstab' LANGUAGE C STABLE STRICT; Use OUT parameters to define the return type implicitly. The same example could also be done this way: CREATE OR REPLACE FUNCTION crosstab_float8_5_cols(IN text, OUT row_name TEXT, OUT category_1 FLOAT8, OUT category_2 FLOAT8, OUT category_3 FLOAT8, OUT category_4 FLOAT8, OUT category_5 FLOAT8) RETURNS setof record AS '$libdir/tablefunc','crosstab' LANGUAGE C STABLE STRICT; Example: 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) crosstab(text source_sql, text category_sql) Where source_sql is 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 has to be 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 The function 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 Note that it follows these rules: source_sql must be ordered by row_name (column 1). 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. 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. Extra values (i.e. source rows with category not found in category_sql result) are skipped. Rows with a null row_name column are skipped. 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). 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) connectby(text relname, text keyid_fld, text parent_keyid_fld [, text orderby_fld], text start_with, int max_depth [, text branch_delim]) Parameter Description 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 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. The function 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); Note that it follows these rules: keyid and parent_keyid must be the same data type The column definition *must* include a third column of type INT4 for the level value output 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. If the branch field is desired, it must be the fourth column in the query column definition, and it must be type TEXT. The parameters representing table and field names must include double quotes if the names are mixed-case or contain special characters. 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: 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