DB2 pureScale - Insert Load & Replication

Published 21 July 2010 - by Clair Ross

Following on from James Gill’s recent blog post about the Coupling Facility today I’m sharing with you our experiences of working with Insert Load & Replication in DB2 pureScale. 

In order to test the load capacity of the IBM DB2 pureScale machine we needed some test data and lots of it!  Being somewhat familiar with the capabilities of the CF on z/OS I knew that a few thousand records would not be enough.

After some checking about, I decided to “stand on the shoulders of giants” and use the EMPLOYEE table from the DB2 SAMPLE database.  Simple, elegant and to the point.  The only problem was that with the current “out of the box” table definition, there would only be 999,999 records that could be produced.

14 record(s) selected.

With a little transformation, we changed the EMPNO to be CHAR(12).  This would allow for the increase of data.  (a possible 999,999,999,999 records)

14 record(s) selected. 

We exported the data into a text delimited file (all 41 records), created a table “LIKE” the employee table, then altered the definition.

I wrote a Q&D Perl script to iterate through the delimited data file and reassign the new EMPNO value.  After a little testing, I just started the program and then turned my attention to items.

After a period of time, I checked the progress and we had approximately 8.5 million records.  I then set up a db2batch script to load the data from the single file.

Other loading strategies attempted were made by splitting the 8.5 million records into multiple files and loading from a single member, then from multiple members.   Autocommit was initially on for the first run, but was switched off and commits were performed at every 10K records.  For the multiple member loads the commit count was at every 500 records.

After the initial load, James suggested that the data file be partitioned three ways for the three data members and to test for contention on the single table.

This was set up quickly and we were good to go.