Fast and Accurate Database Workload Representation on Modern Microarchitecture
Tuesday October 11, 2005
Hamerschlag Hall D-210
This is a practice talk for the International Conference of
Computer Science and Software Engineering.
Carnegie Mellon University
With the proliferation of database workloads on servers, much recent
research on server architecture has focused on database system benchmarks.
The TPC benchmarks for the two most common server workloads, OLTP
and DSS, have been used extensively in the database community to
evaluate the database system functionality and performance. Unfortunately,
these benchmarks fall short of being effective in microarchitecture
and memory system research due to several key shortcomings. First,
setting up the experimental environment and tuning these benchmarks
to match the workload behavior of interest involves extremely complex
procedures. Second, the benchmarks themselves are complex and preclude
accurate correlation of microarchitecture- and memory-level bottlenecks
to dominant workload characteristics. Finally, industrial-grade
configurations of such benchmarks are too large and preclude their
use in detailed but slow microarchitectural simulation studies of
future servers. In this paper, we first present an analysis of the
dominant behavior in DSS and OLTP workloads, and highlight their
key processor and memory performance characteristics. We then introduce
a systematic scaling framework to scale down the TPC benchmarks.
Finally, we propose the DBmbench consisting of two substantially
scaled-down benchmarks: mTPC-H and mTPC-C that accurately (>
95%) capture the processor and memory performance behavior of DSS
and OLTP workloads.
Minglong Shao is a Ph.D. candidate in Carnegie Mellon University,
working with Professor Anastassia Ailamaki. She received her Bachelor's
degree in Computer Science from Tsinghua University at Beijing,
China. Her research interests are Database performance characterization
and new data organization on modern CPUs and disks.