Abstract
With today’s data explosion, databases have kept pace with the ever increasing demands of businesses by growing in size to accommodate peta-bytes and exa-bytes of data. This growth in data sizes is met by an equally impressive platform hardware engineering. These large enterprise systems are characterized by very large memory, I/O footprints and number of processors. These systems offer a good hardware consolidation platform, allowing traditional smaller databases to be consolidated on to larger and fewer x86 servers. In pursuit of efficient resource utilization, we have seen database implementations leverage technologies like virtualization and containerization to improve resource utilization rates, while providing best possible isolation of workloads. Oracle database 12cR1 is an offering that enables high server resource utilization rates for database workloads using the “Multitenant” feature. While scaling multi-tenant database workloads from 1 to 4 sockets could be considered a modestly challenging task, scaling these workloads beyond 4 sockets (such as 8 or 16 sockets) presents new challenges that have to be addressed to make the deployments more efficient. One of the main challenges to deal with on such highly NUMA (Non-Uniform Memory Access) architectures is the associated performance penalties in memory intensive workloads. Database software is primarily memory intensive, so the need for optimizing both the hardware and the software stack for best performance becomes very apparent. While many of the hardware optimizations are done via platform tunings in the BIOS (aka system firmware), an equal amount of tuning options are available to be explored and applied on the OS and the application side. In this paper, we focus primarily on the software based tunings available to users in the OS and the database. The information presented in this paper are an accumulation of learnings and observations made when trying to solve NUMA challenges during OLTP benchmarking with Oracle multitenant database deployed on a 16 socket HPE Integrity Superdome X under a Linux environment.
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Acknowledgments
We would like to thank Long, Wai Man for his help in setup of perf, c2c tool along with analysis of perf data collected during the database workload runs.
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Sahasranamam, S.V., Cao, P., Tadakamadla, R., Norton, S. (2017). Lessons from OLTP Workload on Multi-socket HPE Integrity Superdome X System. In: Nambiar, R., Poess, M. (eds) Performance Evaluation and Benchmarking. Traditional - Big Data - Internet of Things. TPCTC 2016. Lecture Notes in Computer Science(), vol 10080. Springer, Cham. https://doi.org/10.1007/978-3-319-54334-5_6
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DOI: https://doi.org/10.1007/978-3-319-54334-5_6
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