Skip to main content

Setup and manage a Apache Spark cluster in EC2

Project description

The CGCloud plugin for Spark lets you setup a fully configured Apache Spark cluster in EC2 in just minutes, regardless of the number of nodes. 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:

  • Tachyon or Yarn are not included

  • 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 join the cluster 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 this plugin into the virtualenv you created for CGCloud:

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

If you get DistributionNotFound: No distributions matching the version for cgcloud-spark, try running pip install --pre cgcloud-spark.

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:$CGCLOUD_PLUGINS"

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 -IT spark-box

The I option stops the box once it is fully set up and takes an image (AMI) of it. The T option terminates the box after that.

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

cgcloud create-cluster spark -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 -o 0 spark-slave

… or the second slave:

cgcloud ssh -o 1 spark-slave

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cgcloud-spark-1.6.0.tar.gz (10.0 kB view details)

Uploaded Source

Built Distribution

cgcloud_spark-1.6.0-py2.7.egg (22.3 kB view details)

Uploaded Source

File details

Details for the file cgcloud-spark-1.6.0.tar.gz.

File metadata

File hashes

Hashes for cgcloud-spark-1.6.0.tar.gz
Algorithm Hash digest
SHA256 9fa7bd71a1d8083de1146439826cb8a0bef60726fc4a9e1e4f5374faf30d0eb9
MD5 ffc970ce94e4590cecb00634d44f8f54
BLAKE2b-256 9cbc0b0c98bd7af80ae9a7fd26c09892781e940a4afe7c11b36574d915804e2e

See more details on using hashes here.

File details

Details for the file cgcloud_spark-1.6.0-py2.7.egg.

File metadata

File hashes

Hashes for cgcloud_spark-1.6.0-py2.7.egg
Algorithm Hash digest
SHA256 8c6bb0748d4fe5e498d6eb6c556c2543480b35ad5a3b011194f4d0dfad0b1890
MD5 96bf1642bc03685540726dbb1fcae38a
BLAKE2b-256 f9ab92694ce6d36a0d6ed8862685a687fbf44dc5897bec09f605383253aac9e3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page