Apache Spark and In-Memory Computing

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"Apache Spark and In-Memory Computing"

Optimizing Apache Spark™ with Memory1™

Optimizing Apache Spark™ with Memory1™

White Paper: Inspur Group Co. Ltd

Apache Spark is a fast and general engine for large-scale data processing. To handle increasing data rates and demanding user expectations, big data processing platforms like Apache Spark have emerged and quickly gained popularity.

This whitepaper on “Optimizing Apache Spark with Memory1”demonstrates that by leveraging Memory1 to maximize the available memory, the servers can do more work (75% efficiency improvement in Spark performance), unleashing the full potential of real-time, big data processing.

This Technology Whitepaper Covers:

  • How Spark works?

  • What are the issues that subvert the full potential of Apache Spark’s disaggregated approach?

  • How to simulate the critical demands of a typical Spark operations workload?

  • How to eliminate the hardware cost concerns traditionally faced in multi-server Spark deployments?

  • What efficiency metrics are involved in the Spark operations?

  • Key issues faced by Spark in traditional, DRAM-only deployments

  • How to Avoid the high cost of DRAM-only implementations in Apache Spark architects

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