Cost Modelling for Optimal Data Placement in Heterogeneous Main Memory

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Abstract

The cost of DRAM contributes significantly to the operating costs of in-memory database management systems (IMDBMS). Persistent memory (PMEM) is an alternative type of byte-addressable memory that offers — in addition to persistence — higher capacities than DRAM at a lower price with the disadvantage of increased latencies and reduced bandwidth. This paper evaluates PMEM as a cheaper alternative to DRAM for storing table base data, which can make up a significant fraction of an IMDBMS’ total memory footprint. Using a prototype implementation in the SAP HANA IMDBMS, we find that placing all table data in PMEM can reduce query performance in analytical benchmarks by more than a factor of two, while transactional workloads are less affected. To quantify the performance impact of placing individual data structures in PMEM, we propose a cost model based on a lightweight workload characterization. Using this model, we show how to place data pareto–optimally in the heterogeneous memory. Our evaluation demonstrates the accuracy of the model and shows that it is possible to place more than 75 % of table data in PMEM while keeping performance within 10 % of the DRAM baseline for two analytical benchmarks.