How Does GaussDB(DWS) Implement Row-to-Column and Column-to-Row Conversion?

This section describes how to use SQL statements to convert rows to columns and convert columns to rows in GaussDB(DWS).

Scenario

Use a student score table as an example:

Teachers record the score of each subject of each student in a table, but students care only bout their own scores. A student needs to use row-to-column conversion to view their scores of all subjects. If the teacher of a subject wants to view the sores of all students of that subject, the teacher needs to use the column-to-row conversion.

The following figure shows the row-to-column and column-to-row conversion.

Figure 1 Diagram

Rows-to-column conversion
Convert multiple rows of data into one row, or convert one column of data into multiple columns.
Column-to-row conversion
Convert a row of data into multiple rows, or convert multiple columns of data into one column.

Example

Create a row-store table students_info, and insert data into the table.

CREATE TABLE students_info(name varchar(20),subject varchar(100),score bigint) distribute by hash(name);
INSERT INTO students_info VALUES('lily','math',95);
INSERT INTO students_info VALUES('lily','physics',80);
INSERT INTO students_info VALUES('lily','literature',92);
INSERT INTO students_info VALUES('matu','math',75);
INSERT INTO students_info VALUES('matu','physics',90);
INSERT INTO students_info VALUES('matu','literature',85);
INSERT INTO students_info VALUES('jack','math',90);
INSERT INTO students_info VALUES('jack','physics',95);
INSERT INTO students_info VALUES('jack','literature',95);

View information about the students_info table.

SELECT * FROM students_info;
 name |  subject   | score
------+------------+-------
 matu | math       |    75
 matu | physics    |    90
 matu | literature |    85
 lily | math       |    95
 lily | physics    |    80
 lily | literature |    92
 jack | math       |    90
 jack | physics    |    95
 jack | literature |    95

Create a column-store table students_info1, and insert data into the table.

CREATE TABLE students_info1(name varchar(20), math bigint, physics bigint, literature bigint) with (orientation = column) distribute by hash(name);
INSERT INTO students_info1 VALUES('lily',95,80,92);
INSERT INTO students_info1 VALUES('matu',75,90,85);
INSERT INTO students_info1 VALUES('jack',90,95,95);

View information about table students_info1.

SELECT * FROM students_info1;
 name | math | physics | literature
------+------+---------+------------
 matu |   75 |      90 |         85
 lily |   95 |      80 |         92
 jack |   90 |      95 |         95
(3 rows)

Static row-to-column conversion

Static row-to-column conversion requires you to manually specify the column names using the given values. If no value is given to a column, the default value 0 is assigned to the column.

SELECT name,
sum(case when subject='math' then score else 0 end) as math,
sum(case when subject='physics' then score else 0 end) as physics,
sum(case when subject='literature' then score else 0 end) as literature FROM students_info GROUP BY name;
 name | math | physics | literature
------+------+---------+------------
 matu |   75 |      90 |         85
 lily |   95 |      80 |         92
 jack |   90 |      95 |         95
(3 rows)

Dynamic row-to-column conversion

For clusters of 8.1.2 or later, you can use GROUP_CONCAT to generate column-store statements.

SELECT group_concat(concat('sum(IF(subject = ''', subject, ''', score, 0)) AS "', name, '"'))FROM students_info;
      group_concat

-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------
 sum(IF(subject = 'literature', score, 0)) AS "jack",sum(IF(subject = 'literature', score, 0)) AS "lily",sum(IF(subject = 'literature', score, 0)) AS "matu",sum(IF(subject = 'math', score, 0)) AS "jack",sum(IF
(subject = 'math', score, 0)) AS "lily",sum(IF(subject = 'math', score, 0)) AS "matu",sum(IF(subject = 'physics', score, 0)) AS "jack",sum(IF(subject = 'physics', score, 0)) AS "lily",sum(IF(subject = 'physics
', score, 0)) AS "matu"
(1 row)

In 8.1.1 and earlier versions, you can use LISTAGG to generate column-store statements.

SELECT listagg(concat('sum(case when subject = ''', subject, ''' then score else 0 end) AS "', subject, '"'),',') within GROUP(ORDER BY 1)FROM (select distinct subject from students_info);
                                                                                                      listagg

-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
--
 sum(case when subject = 'literature' then score else 0 end) AS "literature",sum(case when subject = 'physics' then score else 0 end) AS "physics",sum(case when subject = 'math' then score else 0 end) AS "math
"
(1 row)

Dynamically rebuild the view:

CREATE OR REPLACE FUNCTION build_view()
RETURNS VOID
LANGUAGE plpgsql
AS $$ DECLARE
sql text;
rec record;
BEGIN
sql := 'select LISTAGG(
	CONCAT( ''sum(case when subject = '''''', subject, '''''' then score else 0 end) AS "'', subject, ''"'' )
	,'','' ) within group(order by 1) from (select distinct subject from students_info);';
	EXECUTE sql INTO rec;
	sql := 'drop view if exists get_score';
	EXECUTE sql;
	sql := 'create view get_score as select name, ' || rec.LISTAGG || ' from students_info group by name';
	EXECUTE sql;
END$$;

Rebuild the database:

CALL build_view();

Query view:

SELECT * FROM get_score;
 name | literature | physics | math
------+------------+---------+------
 matu |         85 |      90 |   75
 lily |         92 |      80 |   95
 jack |         95 |      95 |   90
(3 rows)

Column-to-Row Conversion

Use UNION ALL to merge subjects (math, physics, and literature) into one column. The following is an example:

SELECT * FROM 
(
SELECT name, 'math' AS subject, math AS score FROM students_info1
union all
SELECT name, 'physics' AS subject, physics AS score FROM students_info1
union all
SELECT name, 'literature' AS subject, literature AS score FROM students_info1
) 
order by name;
 name |  subject   | score
------+------------+-------
 jack | math       |    90
 jack | physics    |    95
 jack | literature |    95
 lily | math       |    95
 lily | physics    |    80
 lily | literature |    92
 matu | math       |    75
 matu | physics    |    90
 matu | literature |    85
(9 rows)

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