1. A Self-tuning Page Cleaner for the DB2 Buffer Pool Wenguang Wang Rick Bunt Department of Computer Science University of Saskatchewan

2. MASCOTS 2002 2 What is the Buffer Pool The buffer pool is an in-memory buffer which caches disk pages of the database Buffer Pool Database on Disks WritesReads Applications Upper layer of DBMS DBMS

3. MASCOTS 2002 3 Changed Pages FF I/O Activities of Buffer Pool Agent Fix page A Buffer Pool Disks A Agent Fix page C Read C Sync Write F Clean Pages Read B Agent Fix page B E Page Cleaner Page Cleaner BC Async Write Clean Pages

4. MASCOTS 2002 4 Tuning for Performance Buffer pool performance is crucial to system performance Page cleaning is one of the key components of buffer pool performance Performance tuning is often difficult on large systems Self-tuning can make the tuning task much easier

5. MASCOTS 2002 5 Methodology Find the most important parameters that need to be tuned –Measurement and trace-driven simulation Design the self-tuning algorithm to tune these parameters automatically Evaluate the proposed self-tuning algorithm by trace-driven simulation

6. MASCOTS 2002 6 Methodology DBMS: IBM DB2 7.1.0 for Windows Workload: TPC-C benchmark Validation of simulation results with measurements

7. MASCOTS 2002 7 Effect of the # of Page Cleaners Proportion of sync writes is a useful control variable

8. MASCOTS 2002 8 Approach Page cleaning speed is affected by the number of page cleaners Automatically adjust the page cleaning speed Force the observed proportion of sync writes to the desired proportion w d which is close to 0 (say 5%) wdwd

9. MASCOTS 2002 9 The Self-tuning Algorithm Check the observed proportion of sync writes periodically If the observed proportion of sync writes > w d, increase the page cleaning speed If the observed proportion of sync writes < w d, decrease the page cleaning speed

10. MASCOTS 2002 10 Results Manually tuning can improve system throughput

11. MASCOTS 2002 11 Results Throughput of the self-tuning algorithm is comparable to that of the manually tuned system

12. MASCOTS 2002 12 Robustness Works well under different hardware configurations –Achieves throughput within 0.2-4.6% of the manually tuned system The achieved throughput is insensitive to the parameters of the algorithm –Under a wide range of parameter values, the throughput change is within 1%

13. MASCOTS 2002 13 Summary Identified parameters that need to be tuned in a large commercial DBMS (IBM DB2) Proposed and evaluated a self-tuning algorithm for page cleaning in the buffer pool that –can achieve performance comparable to a manually-tuned system, and –is robust

14. MASCOTS 2002 14

15. MASCOTS 2002 15 I/O Activities of Untuned Configuration Effective page cleaning reduces need for sync writes