Public | Automated Build

Last pushed: 2 years ago
Short Description
Container, equipped with all necessary tools to Build Apache Spark and generate RPMs.
Full Description

Deprecated in favor of a generic and standard approach: [https://github.com/tzolov/bigtop-centos]. For more info read the How-To Guide.

Apache Spark Build Pipeline

Docker container, equipped with all necessary tools to Build Apache Spark and generate RPMs.
Tools installed include: CentOS6, Java7, Maven3, Git, Alien).

1. Installation

  • Install Docker.
  • Configure Docker Host - Spark build requires at least 4GB of memory. (For boot2docker host set 8GB of memory: boot2docker delete; boot2docker init -m 8192; boot2docker up; export DOCKER_HOST=tcp://<Docker Host IP>:2375)
  • Download trusted build from public Docker Registry: docker pull tzolov/apache-spark-build-pipeline (alternatively, you can build an image from Dockerfile: docker build -t="tzolov/my-apache-spark-build-pipeline:1.0.0" github.com/tzolov/apache-spark-build-pipeline.git)
  • Start a container with the latest image: docker run --rm -t -i -v /rpm:/rpm tzolov/apache-spark-build-pipeline /bin/bash

2. Create Spark RPM

The build_rpm.sh utility simplifies the rpm creation process.
Alternatively you can build the rpm by hand follwoing the step by step instructions in the Build Spark RPM by hand section.

2.1 Use Spark build_rpm.sh script

The build_rpm.sh <Hadoop Version> <Spark Branch or Tag> creates a new Spark rpm for the specified Spark and Hadoop versions (only Hadoop Yarn distros are supported). The build process applies a spark_rpm.patch to allows no-root users to run spark and to include the spark examples into the rpm.
Created RPMs are stored into /rpm/<Hadoop Version> folder.
(Note: When run the buld_rpm.sh script deletes the /spark folder and clones a fresh copy form the spark github repository!)

Example usages:

# Build Spark 1.2.0 rpm for Apache Hadoop 2.2.0
/build_rpm.sh 2.2.0 tags/v1.2.0 

# Build Spark 1.2.0 rpm for PivotalHD2.0 (Hadoop2.2.0 complient)
/build_rpm.sh 2.2.0-gphd-3.1.0.0 tags/v1.2.0

# Build Spark master (last snapshot) rpm for PivotalHD2.1 (Hadoop2.2.0 complient)
/build_rpm.sh 2.2.0-gphd-3.1.0.0 master

You can copy the /rpm folder over SSH to the Docker host or another server: scp -rp /rpm docker@<Docker Host IP>: .. In turn you can copy from the Docker Host into local folder: scp -rp docker@<Docker Host IP>:rpm <Your Local Folder>.

2.2 Build Spark RPM by hand

Detail instructions how to synch the Spark git repository, apply optional patch, build the project and generate RPM. Inside a running apache-spark-build-pipeline container perform the following steps:

# Update the local Git repository with the remote master
cd /spark
git pull --rebase

# Pick a branch/tag to generate RPM for. 
# Use `git  branch -a` or `git tag` to list the available branches/tags
git checkout tags/v1.2.0

# Patch to allows no-root user to run spark 
# and to include the spark examples into the rpm
git am < /spark_assembly.patch

# Build SPARK and generate DEB packages
mvn -Pyarn -Phadoop-2.2 -Pdeb -Dhadoop.version=2.2.0 -DskipTests -Ddeb.bin.filemode=755 clean package

# Check the Deb package and convert it into RPM
# dpkg-deb --info '/spark/assembly/target/spark_*.deb'
alien -v -r /spark/assembly/target/spark_*.deb 

Generated spark RPM is saved in the folder where the alien is run.

3. Build Spark tar.gz (excluding Deb or Rpm)

If you only need a pre-build tar.gz (excluding deb or rpm) package like the those officially distributed or Spark website Then you can use the make-distribution.sh script.

/spark/make-distribution.sh --with-hive --with-yarn --tgz --skip-java-test --hadoop 2.2.0 --name hadoop22

4. Use Spark RPMs

Prerequisites: Installed Hadoop2/Yarn cluster. For testing the Spark rpm you can easily install a single-node Hadoop cluster: PivotalHD 2.0 Single Node VM

4.1 Install Spark RPM

Pre-build Spark RPMs for:

On your Hadoop master node Install the rpm from a remote url: sudo yum -y install <use one of the RPM urls above> or from the local filesystem sudo yum install ./spark-XXX.noarch.rpm

4.2 Run Spark Shell

Set the HADOOP_CONF_DIR to the location of hadoop-conf directory. For PivotalHD HADOOP_CONF_DIR defaults to /etc/gphd/hadoop/conf. For CDH it may default to /etc/hadoop/conf
Add spark-assembly jar to the SPARK_SUBMIT_CLASSPATH. The spark-assembly-xxx.jar located in /usr/share/spark/jars/ folder.

export HADOOP_CONF_DIR=/etc/gphd/hadoop/conf
# export SPARK_SUBMIT_CLASSPATH=/usr/share/spark/jars/spark-assembly-1.1.0-hadoop2.2.0.jar
/usr/share/spark/bin/spark-shell --master yarn-client

4.3 Submit Sample Spark application: SparkPi

export HADOOP_CONF_DIR=/etc/gphd/hadoop/conf
# export SPARK_SUBMIT_CLASSPATH=/usr/share/spark/jars/spark-assembly-1.1.0-hadoop2.2.0.jar:/usr/share/spark/jars/spark-assembly-1.1.0-hadoop2.2.0.jar:

/usr/share/spark/bin/spark-submit \
  --num-executors 10  \
  --master yarn-cluster \
  --class org.apache.spark.examples.SparkPi \
  /usr/share/spark/jars/spark-examples-1.1.0-hadoop2.2.0.jar 10
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