Analysis of Database Workloads on Modern Processors

1. Analysis of Database Workloads on Modern Processors Advisor: Prof. Shan Wang P.h.D student: Dawei Liu Key Laboratory of Data Engineering and Knowledge Engineering MOE School of Information Renmin University of China

2. Outlines • 1.Background • 2. Motivation • 3. Our research work • 4. Future works

3. Background • LAMA Project • LaMa • rgle Scale Data nagement • Joint research with HP Lab China • Goal • Advanced issues of Massively Parallel Processing (MPP) databases • Architecture and design aspects; • Next generation memory oriented DB My Focus

4. Outlines • 1.Background • 3. Our research • 4. Future works 2. Motivation

5. Motivation • Continued evolution of hardware • Processor

6. Motivation(cont.) • Memory Larger and Larger Flash Memory

7. Cont. • Traditional research • Dedicate to I/O optimization • Fail to utilize processor resources efficiently

8. Cont. • Modern processors (Itanium II) • multi-level memory hierarchies; • superscalar out-of-order execution; • multi-threading; • multi-cores; Create opportunity for database performance improve.

9. Cont. • Object • Accurately characterizing workload behavior on modern processor • Find out the bottleneck; • Benefit • Identify a set of characteristics; • performance optimization Detailed issues ?

10. My P.h. D Track • (1) Accurately characterize the database workloads on modern processors; • (2) Investigating the MMDB workloads on modern processor; • (3) Developing a specialized benchmark for MMDB

11. (1) Processor Issue • Previous research[*] • Conlusion • DBMSs achieve low IPC (instructions-per-cycle) • Processors are inefficiently used • Platform • Intel Pentium II / Pentium Pro ---------------------------------------------------------------------------------------------------------------------------------------- * A. Ailamaki, D. J. DeWitt, M. D. Hill, D. A. Wood. DBMSs on a Modern Processor: Where Does Time Go? In Proc. VLDB, 1999.

12. Cont. • We are interested in • DBMS on today’s processors • Itanium II • AMD Opteron (tm) Where does 8 years go ?

13. (2) Main Memory DB Issue • Previous research • DB: Disk Resident Databases (DRDB) • Workload: TPC-C Larger and larger on-chip and off-chip caches ; Steady increased RAM; The “moved up” on the memory hierarchy ; • Current problems • DB: Main Memory Databases (MMDB) • Workload: TPC-H (compute intensive)

14. (3) MMDB-Oriented Benchmark • Performance evaluation • OO1-Benchmark • OO7-Benchmark obsolete • Industrial standards OLTP OLAP TPC Benchmark H TPC Benchmark C We found they are not approprite to benchmark MMDB How to benchmark memory database ?

15. Outlines • 1.Background • 2. Motivation • 4. Future works 3. Our research

16. Methodology • Analysis framework • Experiment study

17. Pipeline of modern processors

18. Query Execution Time Breakdown • TQ = TC + TM + TB + TR − TOV L [*] • TC: Useful computation time; • TM: Stall time because of memory stalls; • TB: Branch misprediction overhead; • TR: Resource-related stalls; • TOVL: Stall time can be overlapped * A. Ailamaki, D. J. DeWitt, M. D. Hill, D. A. Wood. DBMSs on a Modern Processor: Where Does Time Go? In Proc. VLDB, 1999.

19. Execution time components on Itanium II platform

20. Experimental setup • Platform-specific hardware • Software • Experimental methodology

21. The Hardware Platform • HP Integrity rx2620-2 server • Itanium II based server • Cache

22. Cache characteristics

23. Software and Methodology • Calibrator (CWI *) • cache access and miss latency; • main memory access latency; • number of TLB levels ; • each level’s TLB miss latency * Centrum voor Wiskunde en Informatica National research institute for mathematics and computer science in the Netherlands

24. Cont. • Perfsuite (NSCA *) Control hardware counters Measure 60 event types for the results Hardware counters * National Center for Supercomputing Applications (NCSA)

25. Stall time components on Itanium II

26. Results analysis • Part one: DRDB • Characterization workload on Itanium II • OLTP • OLAP • Part two: MMDB issue • Characterization of MMDB TPC-H workload --------------------------------------------------------------------------------------------------------- • Dawei liu, Shan Wang, Biao Qin, Weiwei Gong: Characterizing DSS Workloads from the Processor Perspective. The International Workshop on Database Management and Application over Network DBMAN 2007: 235-240 • DaweiDawei Liu, Shan Wang, Qiming Chen, Yun Tian, Weiwei Gong “Main Memory Database TPC-H Workload Characterization on Modern Processor,” Renmin University of China., TR-01, 2007, http://deke.ruc.edu.cn/tr/TR 2007-01.

27. Memory stall time breakdown TPC-H Workload on a DRDB

28. Index Influence TPC-H Workload on a DRDB

29. Branch Instruction Misprediction TPC-H Workload on a DRDB

30. DRDB vs. MMDB

31. Storage Architecture Influence

32. Summary • Characterized workload on Itanium II based platform; • Characterized MMDB read optimized workload on modern processors; • Compare the workload breakdown of DRDB and MMDB; • Explored the difference of column-oriented and row-oriented storage models in CPU and cache utilization; • Investigated the index influence at low level

33. Outlines • 1.Background • 2. Motivation • 3. Our research 4. Future works

34. Future works • In-depth analysis of the results • Develop new parallel techniques • Instruction level parallelism • MMDB benchmark issue • The results expected to benefit • The performance optimization of DBMS; • The architecture of next-generation memory-oriented databases.

35. The End Thanks! Welcome to visit RUC. Key Laboratory of Data Engineering and Knowledge Engineering MOE | liudawei@ruc.edu.cn | | http://deke.ruc.edu.cn | | Tel.: +86 (10) 62513934 | | Dawei Liu | School of Information| Renmin University of China