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Setup and manage a Apache Spark cluster in EC2

Project description

The CGCloud Spark project lets you setup a functioning Apache Spark cluster in EC2 in just minutes, regardless of the number of nodes. It is a plugin to CGCloud. While Apache Spark already comes with a script called spark-ec2 that lets you build a cluster in EC2, CGCloud Spark differs from spark-ec2 in the following ways (bad news first):

  • Tachyon and Yarn are not yet supported.

  • Setup time does not scale linearly with the number of nodes. Setting up a 100 node cluster takes just as long as setting up a 10 node cluster (2-3 min, as opposed to 45min with spark-ec2). This is made possible by baking all required software into a single AMI. All slave nodes boot up concurrently and autonomously in just a few minutes.

  • Unlike with spark-ec2, the cluster can be stopped and started via the EC2 API or the EC2 console, without involvement of cgcloud.

  • The Spark services (master and worker) run as an unprivileged user, not root as with spark-ec2. Ditto for the HDFS services (namenode, datanode and secondarynamenode).

  • The Spark and Hadoop services are started automatically as the instance boots up, via a regular init script.

  • Nodes can be added easily, simply by booting up new instances from the AMI. They will join the cluster automatically. HDFS may have to be rebalanced after that.

  • You can customize the AMI that cluster nodes boot from by subclassing the SparkMaster and SparkSlave classes.

  • CGCloud Spark uses the CGCLoud Agent which takes care of maintaining a list of authorized keypairs on each node.

  • CGCloud Spark is based on the official Ubuntu Trusty 14.04 LTS, not the Amazon Linux AMI.

Prerequisites

The cgcloud-spark package requires that the cgcloud-core package and its prerequisites are present.

Installation

Read the entire section before pasting any commands and ensure that all prerequisites are installed. It is recommended to install cgcloud into a virtualenv. Create a virtualenv and use pip to install cgcloud-spark:

virtualenv cgcloud
source cgcloud/bin/activate
pip install cgcloud-spark

On OS X systems with a Python that was installed via HomeBrew, you should omit sudo. You can find out if that applies to your system by running which python. If it prints /usr/local/bin/python you are most likely using a HomeBrew Python and should therefore omit sudo. If it prints /usr/bin/python you need to run pip with sudo.

Be sure to configure cgcloud-core before proceeding.

Configuration

Modify your .profile or .bash_profile by adding the following line:

export CGCLOUD_PLUGINS=cgcloud.spark

Login and out (or, on OS X, start a new Terminal tab/window).

Verify the installation by running:

cgcloud list-roles

The output should include the spark-box role.

Usage

Create a single t2.micro box to serve as the template for the cluster nodes:

cgcloud create spark-box -I -T

The -I switch stops the box once it is fully set up and takes an AMI of it. The -T switch terminates it after that.

Create a cluster by booting a master and the slaves from that AMI:

cgcloud create-spark-cluster -s 2 -t m3.large

This will launch a master and two slaves using the m3.large instance type.

SSH into the master:

cgcloud ssh spark-master

… or the first slave:

cgcloud ssh spark-slave -o 0

… or the second slave:

cgcloud ssh spark-slave -o 1

Interactions with Spark and HDFS should be done as the sparkbox user:

cgcloud ssh spark-master -l sparkbox
hdfs dfs -ls /
spark-shell

Otherwise you are likely to run into permission problems.

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