TY - GEN
T1 - Variations of the star schema benchmark to test the effects of data skew on query performance
AU - Rabl, Tilmann
AU - Poess, Meikel
AU - Jacobsen, Hans Arno
AU - O'Neil, Patrick
AU - O'Neil, Elizabeth
PY - 2013
Y1 - 2013
N2 - The Star Schema Benchmark (SSB), now in its third revision, has been widely used to evaluate the performance of database management systems when executing star schema queries. SSB, based on the well known industry standard benchmark TPC-H, shares some of its drawbacks, most notably, its uniform data distributions. Today's systems rely heavily on sophisticated cost-based query optimizers to generate the most efficient query execution plans. A benchmark that evaluates optimizer's capability to generate optimal execution plans under all circumstances must provide the rich data set details on which optimizers rely (uniform and non-uniform distributions, data sparsity, etc.). This is also true for other database system parts, such as indices and operators, and ultimately holds for an end-to-end benchmark as well. SSB's data generator, based on TPC-H's dbgen, is not easy to adapt to different data distributions as its meta data and actual data generation implementations are not separated. In this paper, we motivate the need for a new revision of SSB that includes non-uniform data distributions. We list what specific modifications are required to SSB to implement non-uniform data sets and we demonstrate how to implement these modifications in the Parallel Data Generator Framework to generate both the data and query sets.
AB - The Star Schema Benchmark (SSB), now in its third revision, has been widely used to evaluate the performance of database management systems when executing star schema queries. SSB, based on the well known industry standard benchmark TPC-H, shares some of its drawbacks, most notably, its uniform data distributions. Today's systems rely heavily on sophisticated cost-based query optimizers to generate the most efficient query execution plans. A benchmark that evaluates optimizer's capability to generate optimal execution plans under all circumstances must provide the rich data set details on which optimizers rely (uniform and non-uniform distributions, data sparsity, etc.). This is also true for other database system parts, such as indices and operators, and ultimately holds for an end-to-end benchmark as well. SSB's data generator, based on TPC-H's dbgen, is not easy to adapt to different data distributions as its meta data and actual data generation implementations are not separated. In this paper, we motivate the need for a new revision of SSB that includes non-uniform data distributions. We list what specific modifications are required to SSB to implement non-uniform data sets and we demonstrate how to implement these modifications in the Parallel Data Generator Framework to generate both the data and query sets.
KW - data generation
KW - data skew
KW - parallel data generation framework
KW - pdgf
KW - star schema benchmark
KW - tpc-h
UR - http://www.scopus.com/inward/record.url?scp=84878203215&partnerID=8YFLogxK
U2 - 10.1145/2479871.2479927
DO - 10.1145/2479871.2479927
M3 - Conference contribution
AN - SCOPUS:84878203215
SN - 9781450316361
T3 - ICPE 2013 - Proceedings of the 2013 ACM/SPEC International Conference on Performance Engineering
SP - 361
EP - 372
BT - ICPE 2013 - Proceedings of the 2013 ACM/SPEC International Conference on Performance Engineering
T2 - 2013 4th ACM/SPEC International Conference on Performance Engineering, ICPE 2013
Y2 - 21 April 2013 through 24 April 2013
ER -