Early experience with optimizing I/O performance using high-performance SSDs for in-memory cluster computing

This paper describes our experience with storage optimization that utilizes cost-effective PCIe solid-state drives (SSDs) to improve the overall performance of a Spark framework. A key problem we address is the limited memory system performance. In particular, we adopt high-performance SSDs to alleviate the saturated DRAM bandwidth and its limited capacity. We utilize SSDs to store shuffle data and persisted RDDs. As a result, the overall performance improves due to the larger capacity of SSDs and the increased bandwidth provided by SSDs while alleviating memory contentions. Our experiments show that we can improve the performance of data-intensive applications by 23.1% on average, compared to the performance of the memory-only approach. To our knowledge, this is the first work to demonstrate performance optimizations using PCIe SSDs on Spark.