[SPARK-22229] SPIP: RDMA Accelerated Shuffle Engine

• Type: Improvement
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Affects Version/s: 3.1.0
• Component/s: Spark Core
• Assignee: Unassigned
• Reporter: Yuval Degani
• Created: 09/Oct/17 19:30
• Updated: 16/Mar/20 22:53

Description

An RDMA-accelerated shuffle engine can provide enormous performance benefits to shuffle-intensive Spark jobs, as demonstrated in the “SparkRDMA” plugin open-source project (https://github.com/Mellanox/SparkRDMA).
Using RDMA for shuffle improves CPU utilization significantly and reduces I/O processing overhead by bypassing the kernel and networking stack as well as avoiding memory copies entirely. Those valuable CPU cycles are then consumed directly by the actual Spark workloads, and help reducing the job runtime significantly.
This performance gain is demonstrated with both industry standard HiBench TeraSort (shows 1.5x speedup in sorting) as well as shuffle intensive customer applications.
SparkRDMA will be presented at Spark Summit 2017 in Dublin (https://spark-summit.org/eu-2017/events/accelerating-shuffle-a-tailor-made-rdma-solution-for-apache-spark/).

Please see attached proposal document for more information.

Issue Links

• links to: SparkRDMA main GitHub page
• links to: SparkRDMA session @ Spark Summit 2017 in Dublin on Oct. 26th