Effect of skew on join performance in parallel architectures
DPDS '88 Proceedings of the first international symposium on Databases in parallel and distributed systems
A relational model of data for large shared data banks
Communications of the ACM
New TPC benchmarks for decision support and web commerce
ACM SIGMOD Record
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
A Taxonomy and Performance Model of Data Skew Effects in Parallel Joins
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Generating thousand benchmark queries in seconds
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
The Star Schema Benchmark and Augmented Fact Table Indexing
Performance Evaluation and Benchmarking
A data generator for cloud-scale benchmarking
TPCTC'10 Proceedings of the Second TPC technology conference on Performance evaluation, measurement and characterization of complex systems
Efficient update data generation for DBMS benchmarks
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Introducing skew into the TPC-H benchmark
TPCTC'11 Proceedings of the Third TPC Technology conference on Topics in Performance Evaluation, Measurement and Characterization
A PDGF implementation for TPC-H
TPCTC'11 Proceedings of the Third TPC Technology conference on Topics in Performance Evaluation, Measurement and Characterization
Rapid development of data generators using meta generators in PDGF
Proceedings of the Sixth International Workshop on Testing Database Systems
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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.