Generating Test Data

Here’s a quick way to generate dummy data for performing tests that require lots of record.

SQL> DROP   TABLE lots_o_data;

Table dropped.

SQL> CREATE TABLE lots_o_data
  2  (	 id	  NUMBER
  3    , name	  VARCHAR2(5)
  4    , category VARCHAR2(26)
  5  );

Table created.

SQL> INSERT INTO lots_o_data VALUES (1, 'Lotso', 'Wow this is a lot of data.');

1 row created.

SQL> INSERT INTO lots_o_data VALUES (2, 'More',  'Bunches and bunches.');

1 row created.

SQL> COMMIT;

Commit complete.

SQL> INSERT INTO lots_o_data
  2  	 SELECT a.id, a.name, b.category
  3  	 FROM lots_o_data a CROSS JOIN lots_o_data b;

4 rows created.

SQL> COMMIT;

Commit complete.

SQL> INSERT INTO lots_o_data
  2  	 SELECT a.id, a.name, b.category
  3  	 FROM lots_o_data a CROSS JOIN lots_o_data b;

36 rows created.

SQL> COMMIT;

Commit complete.

SQL> INSERT INTO lots_o_data
  2  	 SELECT a.id, a.name, b.category
  3  	 FROM lots_o_data a CROSS JOIN lots_o_data b;

1764 rows created.

SQL> COMMIT;

Commit complete.

SQL> INSERT INTO lots_o_data
  2  	 SELECT a.id, a.name, b.category
  3  	 FROM lots_o_data a CROSS JOIN lots_o_data b;

3261636 rows created.

SQL> COMMIT;

Commit complete.

SQL> SELECT COUNT(*)
  2  FROM   lots_o_data;
  COUNT(*)                                                               ----------                                                             3263442                                                                      
SQL> SPOOL OFF

Note the following

  • With only four INSERT … SELECT statements based on a Cartesian product, we were able to generate over 3 million rows of data.
  • A few more INSERT … SELECT statements could easily result in billions of rows of data.

If you need a lot of data for performance testing or capacity testing, this is an easy way to get however much you require.

I have been working on building a data lake environment in anticipation of a series of large data feeds I’m expecting soon and found this to be a useful approach to preparing the environment.