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).
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.
This charm is intended to be deployed via one of the
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
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
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
- Enable the
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.
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.
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-plugin, etc) into a single
directory and serve them all with a single
juju-resources serve instance.
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.
URL from which to fetch resources (e.g., Hadoop binaries) instead of Launchpad.