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Analyzing Data Relevance and Access Patterns of Live Production Database Systems

Published:24 October 2016Publication History

ABSTRACT

Access to real-world database systems and their workloads is an invaluable source of information for database researchers. However, usually such full access is not possible due to tracing overheads, data protection, or legal reasons. In this paper, we present a tool set to analyze and compare synthetic and real-world database workloads, their characteristics, and access patterns. This tool set processes SQL workload traces and collects fine-grained access information without requiring direct read access to the production system. To gain insights into large real-world systems, we traced a live production enterprise system of a Global 2000 company and compare it with the synthetic benchmarks TPC-C and TPC-E.

References

  1. F. Funke, A. Kemper, and T. Neumann. Compacting transactional data in hybrid OLTP & OLAP databases. PVLDB, 5(11):1424--1435, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. Krueger et al. Fast updates on read-optimized databases using multi-core CPUs. PVLDB, 5(1):61--72, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Lee et al. High-performance transaction processing in SAP HANA. IEEE Data Eng. Bull., 36(2):28--33, 2013.Google ScholarGoogle Scholar
  4. H. Plattner. The impact of columnar in-memory databases on enterprise systems. PVLDB, 7(13):1722--1729, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. V. Raman et al. DB2 with BLU acceleration: So much more than just a column store. PVLDB, 6(11):1080--1091, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. L. Sun et al. Fine-grained partitioning for aggressive data skipping. In Proc. ACM SIGMOD, pages 1115--1126, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. E. Zamanian et al. Locality-aware partitioning in parallel database systems. In Proc. ACM SIGMOD, pages 17--30, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Analyzing Data Relevance and Access Patterns of Live Production Database Systems

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