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Evaluating Database Performance Overhead in Virtual Machines: A Comparative Study

This article by Minhas, Yadav, Aboulnaga, and Salem, presented at the IEEE 24th International Conference on Data Engineering, examines the performance trade-offs of running databases on virtual machines (VMs), specifically PostgreSQL 8.1.3 on SUSE Linux using Xen VMM. Through "warm" and "cold" experiments involving TPC-H queries, the authors investigate overhead sources such as system calls and page faults. Results show a moderate slowdown (average 9.8% for warm, 6.2% for cold), revealing that the advantages of VMs do not significantly compromise performance, suggesting future research directions with alternative DBMS and VM technologies.

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Evaluating Database Performance Overhead in Virtual Machines: A Comparative Study

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  1. Database Systems on Virtual Machines: How Much Do We Lose? Kristin Travis March 2, 2011

  2. Article Information • Authors: Minhas, Yadav, Aboulnaga, Salem • University of Waterloo • Conference: IEEE 24th International Conference on Data Engineering • Date: April 2008

  3. Background • Obvious benefits with using virtual machines • Decreased costs, flexibility, etc. • Virtual machines add performance overhead • Question: is it worth it? • Personal interest

  4. Setup • DBMS: PostgreSQL 8.1.3 • Base System: SUSE Linux 10.1 • VM system uses VMM Xen 3.1 • VM also runs SUSE Linux • 3 GB memory, 1 virtual CPU • Test DB is 2 GB in size, ensuring that the entire DB can fit in memory • 22 TPC-H queries are run in identical settings on both machines

  5. First Experiment • “Warm” Experiment • Run the 22 queries to “warm” up the buffer, then measure performance in the 2nd run • Queries experience a fairly large overhead • Slowdown in system time is much larger than slowdown in user time

  6. Overhead Causes • System Call Time • System calls are usually handled by OS, but in the VM most go through the Xen VMM • Negligible in this case • Page Fault Handling Time • Page faults in Xen are more than twice as expensive as they are in the base system • The average relative slowdown of all 22 queries is only 9.8%

  7. Second Experiment • “Cold” Experiment • Restart PostgreSQL and flush the file system caches before running each query • Interesting results: the relative slowdown is not high, and some queries actually run faster • Slowdown is caused by disk I/O, having to read from the disk every query • Some queries run faster because Xen VMM aggressively prefetches data for the VM • The average relative slowdown of all 22 queries is only 6.2% (better than “warm” experiment)

  8. Conclusions • The many advantages to running a DBMS in a VM does not come at a high cost in performance • Future work: • Different VM environments (Hyper-V) • Different DBMS (MySQL, Oracle, etc.) • Using multiple VMs on one physical machine

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