apache hadoop compute slave #9

Description

Hadoop is a software platform that lets one easily write and run applications that process vast amounts of data.
This charm manages the compute slave node (DataNode + NodeManager).

Overview

The Apache Hadoop software library is a framework that allows for the
distributed processing of large data sets across clusters of computers
using a simple programming model.

This charm deploys a compute / slave node running the NodeManager
and DataNode components of
Apache Hadoop 2.4.1,
which provides computation and storage resources to the platform.

Usage

This charm is intended to be deployed via one of the
apache bundles.
For example:

juju quickstart apache-analytics-sql

This will deploy the Apache Hadoop platform with Apache Hive available to
perform SQL-like queries against your data.

You can also manually load and run map-reduce jobs via the plugin charm
included in the bigdata bundles linked above:

juju scp my-job.jar plugin/0:
juju ssh plugin/0
hadoop jar my-job.jar

Scaling

The compute-slave node is the "workhorse" of the Apache Hadoop platform.
To scale your deployment's performance, you can simply add more compute-slave
units. For example, to add three mode units:

juju add-unit compute-slave -n 3

Monitoring

This charm supports monitoring via Ganglia. To enable monitoring, you must
do both of the following (the order does not matter):

  • Add a relation to the Ganglia charm via the :master relation
  • Enable the ganglia_metrics config option

You must also enable metrics on yarn-master and / or hdfs-master
to initiate the restart of the NodeManager and / or DataNode components for
them to begin collecting metrics.

For example:

juju add-relation compute-slave ganglia:master
juju add-relation yarn-master ganglia:master
juju set compute-slave ganglia_metrics=true
juju set yarn-master ganglia_metrics=true

Deploying in Network-Restricted Environments

The Apache Hadoop charms can be deployed in environments with limited network
access. To deploy in this environment, you will need a local mirror to serve
the packages and resources required by these charms.

Mirroring Packages

You can setup a local mirror for apt packages using squid-deb-proxy.
For instructions on configuring juju to use this, see the
Juju Proxy Documentation.

Mirroring Resources

In addition to apt packages, the Apache Hadoop charms require a few binary
resources, which are normally hosted on Launchpad. If access to Launchpad
is not available, the jujuresources library makes it easy to create a mirror
of these resources:

sudo pip install jujuresources
juju-resources fetch --all /path/to/resources.yaml -d /tmp/resources
juju-resources serve -d /tmp/resources

This will fetch all of the resources needed by this charm and serve them via a
simple HTTP server. The output from juju-resources serve will give you a
URL that you can set as the resources_mirror config option for this charm.
Setting this option will cause all resources required by this charm to be
downloaded from the configured URL.

You can fetch the resources for all of the Apache Hadoop charms
(apache-hadoop-hdfs-master, apache-hadoop-yarn-master,
apache-hadoop-hdfs-secondary, apache-hadoop-plugin, etc) into a single
directory and serve them all with a single juju-resources serve instance.

Contact Information

Hadoop

Configuration

ganglia_metrics
(boolean) Enable metrics using Ganglia. Note that enabling this option will have no effect if the service is not related to a ganglia service via the ganglia:master relation. Enabling this option also will *not* restart the DataNode nor NodeManager components, so it will also be necessary to enable metrics on one or more of the hdfs-master or yarn-master services. See the README for more information.
resources_mirror
(string) URL from which to fetch resources (e.g., Hadoop binaries) instead of Launchpad.