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IBM zEnterprise System®: Performance Report on Exploiting Large Memory for DB2 Buffer Pools with SAP®



Document Author:
Additional Author(s):

Brenda Beane
Seewah Chan, Paul Lekkas


Document ID:

WP102461


Doc. Organization:

Systems and Technology Group


Document Revised:

06/26/2014


Product(s) covered:

DB2 for z/OS and OS/390; IBM System z; SAP







Abstract: It is reasonable to assume that using more memory will improve overall system performance. One obvious way to make use of more memory is to allocate more memory to DB2 buffer pools. Reducing I/O by caching more data in buffer pools should reduce response time, increase throughput, and provide CPU savings.

The IBM zEnterprise 196 and EC12 systems can support up to 3 TB of real memory per server and 1 TB per LPAR. DB2 10 and 11 for z/OS allow up to 1 TB of memory to be used for all buffer pools in a given member.

The IBM SAP on System z Performance Team, located in Poughkeepsie, NY, conducted a number of experiments to evaluate the performance effects of using large amounts of memory for DB2 buffer pools. We systematically increased the sizes of DB2 buffer pools and measured the effects on system performance. We used the SAP Banking Services (SBS) Day Posting workload, which is a good representation of a customer online transaction processing (OLTP) workload. It is memory intensive, accesses a large number of tables, and exhibits random I/O behavior.

We ran with DB2 11 for z/OS in both single system and data sharing environments. In data sharing, the group buffer pools on the coupling facility (CF) provide an extra layer of caching. We explored the effects of adding memory to both the local buffer pools and the group buffer pools.

We also experimented with reducing the number of buffer pools used. Although isolating or separating objects into their own buffer pools can provide essential monitoring capabilities and performance optimizations, it can also produce a large number of buffer pools over time which can be labor intensive and time consuming to maintain and tune. We conducted a set of experiments to evaluate the performance impact of reducing the number of buffer pools with hopes of simplifying buffer pool management without adversely affecting performance.

Large_Memory_withSAP.pdfLarge_Memory_withSAP.pdf



Classification:

Hardware; Software; Solutions

Category:

Performance

Solution(s):

Enterprise Application Solutions (EAS/ERP); ISV Applications

ISV(s):

SAP

Platform(s):

IBM System z Family

S/W Pillar(s):

Information Management; IBM System z Software

O/S:

z/OS

Keywords:

DB2 11 for z/OS, SAP, SAP Banking, Performance, Parallel Sysplex, Memory


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