authorcamus / SparkRDMA

RDMA accelerated, high-performance, scalable and efficient ShuffleManager plugin for Apache Spark

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SparkRDMA ShuffleManager Plugin

SparkRDMA is a high performance ShuffleManager plugin for Apache Spark that uses RDMA (instead of TCP) when performing Shuffle data transfers in Spark jobs.

This open-source project is developed, maintained and supported by Mellanox Technologies.

Performance results

Example performance speedup for HiBench workloads:

TeraSort results

Running 175GB TeraSort workload with SparkRDMA is x1.53 faster than standard Spark (runtime in seconds)

ScalaSort results

Running 286GB ScalaSort with SparkRDMA is x1.28 faster than standard Spark (runtime in seconds)

Test environment:

16 Spark standalone workers, 2x Intel Xeon E5-2697 v3 @ 2.60GHz, 30 cores per Worker, 256GB RAM, non-flash storage (HDD)

Mellanox ConnectX-4 network adapter with 100GbE RoCE fabric, connected with a Mellanox Spectrum switch

Wiki pages

For more information on configuration, performance tuning and troubleshooting, please visit the SparkRDMA GitHub Wiki

Runtime requirements

  • Apache Spark 2.0.0/2.1.0/2.2.0/2.3.0
  • Java 8
  • An RDMA-supported network, e.g. RoCE or Infiniband

Installation

Obtain SparkRDMA and DiSNI binaries

Please use the "Releases" page to download pre-built binaries.
If you would like to build the project yourself, please refer to the "Build" section below.

The pre-built binaries are packed as an archive that contains the following files:

  • spark-rdma-2.0-for-spark-2.0.0-jar-with-dependencies.jar
  • spark-rdma-2.0-for-spark-2.1.0-jar-with-dependencies.jar
  • spark-rdma-2.0-for-spark-2.2.0-jar-with-dependencies.jar
  • spark-rdma-2.0-for-spark-2.3.0-jar-with-dependencies.jar
  • libdisni.so

libdisni.so must be in java.library.path on every Spark Master and Worker (usually in /usr/lib)

Configuration

Provide Spark the location of the SparkRDMA plugin jars by using the extraClassPath option. For standalone mode this can be added to either spark-defaults.conf or any runtime configuration file. For client mode this must be added to spark-defaults.conf. For Spark 2.0.0 (Replace with 2.1.0, 2.2.0 or 2.3.0 according to your Spark version):

spark.driver.extraClassPath   /path/to/SparkRDMA/target/spark-rdma-2.0-for-spark-2.0.0-jar-with-dependencies.jar
spark.executor.extraClassPath /path/to/SparkRDMA/target/spark-rdma-2.0-for-spark-2.0.0-jar-with-dependencies.jar

Running

To enable the SparkRDMA Shuffle Manager plugin, add the following line to either spark-defaults.conf or any runtime configuration file:

spark.shuffle.manager   org.apache.spark.shuffle.rdma.RdmaShuffleManager

Build

Building the SparkRDMA plugin requires Apache Maven and Java 8

  1. Obtain a clone of SparkRDMA

  2. Build the plugin for your Spark version (either 2.0.0, 2.1.0, 2.2.0 or 2.3.0), e.g. for Spark 2.0.0:

mvn -DskipTests clean package -Pspark-2.0.0
  1. Obtain a clone of DiSNI for building libdisni:
git clone https://github.com/zrlio/disni.git
cd disni
git checkout tags/v1.4 -b v1.4
  1. Compile and install only libdisni (the jars are already included in the SparkRDMA plugin):
cd libdisni
autoprepare.sh
./configure --with-jdk=/path/to/java8/jdk
make
make install

Community discussions and support

For any questions, issues or suggestions, please use our Google group: https://groups.google.com/forum/#!forum/sparkrdma

Contributions

Any PR submissions are welcome

About

RDMA accelerated, high-performance, scalable and efficient ShuffleManager plugin for Apache Spark

License:Apache License 2.0


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