Apache Zeppelin is a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive, and collaborative documents with SQL, Scala and more. This charm provides version 0.7.2 of the Zeppelin application from Apache Bigtop.
Apache Zeppelin is a web-based notebook that enables interactive data analytics. It allows for beautiful data-driven, interactive, and collaborative documents with SQL, Scala and more. Learn more at zeppelin.apache.org.
This charm deploys version 0.7.2 of the Zeppelin component from Apache Bigtop.
This charm requires Juju 2.0 or greater. If Juju is not yet set up, please follow the getting-started instructions prior to deploying this charm.
Zeppelin can be deployed by itself as a stand-alone web notebook. Deployment is simple:
juju deploy zeppelin
To access the web interface, find the
Public address of the
application and expose it:
juju status zeppelin juju expose zeppelin
The web interface will be available at the following URL:
This charm also supports more complex integration scenarios as described below.
This charm may be deployed alongside any of the Apache Bigtop bundles. For example:
juju deploy hadoop-processing
This will deploy a basic Bigtop Hadoop cluster. More information about this deployment can be found in the bundle readme.
Now relate the previously deployed
zeppelin charm to the Hadoop plugin. This
enables communication between Zeppelin and Hadoop:
juju add-relation zeppelin plugin
Once deployment is complete, Zeppelin notebooks will have access to the
Hadoop Distributed File System (HDFS). Additionally, the local Spark driver
will be reconfigured in YARN mode. Any notebooks that submit Spark jobs will
leverage the Hadoop compute resources deployed by the
Zeppelin includes a local Spark driver by default. This allows notebooks to use a SparkContext without needing external Spark resources. This driver can process jobs using local machine resources or compute resources from a Hadoop cluster as mentioned above.
Zeppelin's Spark driver can also use external Spark cluster resources. For example, the following will deploy a 3-unit Spark cluster that Zeppelin will use when submitting jobs:
juju deploy spark -n 3 juju relate zeppelin spark
Once deployment is complete, the local Spark driver will be reconfigured to
use the external cluster as the Spark Master. Any notebooks that submit Spark
jobs will leverage the newly deployed
Charms can be deployed in environments with limited network access. To deploy in this environment, configure a Juju model with appropriate proxy and/or mirror options. See Configuring Models for more information.
Apache Bigtop charms provide extended status reporting to indicate when they are ready:
This is particularly useful when combined with
watch to track the on-going
progress of the deployment:
watch -n 2 juju status
The message column will provide information about a given unit's state. This charm is ready for use once the status message indicates that it is ready.
This charm provides a
smoke-test action that can be used to verify the
application is functioning as expected. Run the action as follows:
juju run-action zeppelin/0 smoke-test
Watch the progress of the smoke test actions with:
watch -n 2 juju show-action-status
Eventually, the action should settle to
status: completed. If it
status: failed, the application is not working as expected. Get
more information about a specific smoke test with:
juju show-action-output <action-id>
When related to Spark, Zeppelin requires a
URL for the Spark Master. This is only available when the
spark charm is
standalone mode --
yarn modes are not supported.
Apache Bigtop tracks issues using JIRA (Apache account required). File an issue for this charm at:
Bigtop is selected as the project. Typically, charm issues are filed
deployment component with the latest stable release selected as the
affected version. Any uncertain fields may be left blank.
- (string) Apache Bigtop release version. The default, '1.2.1' will use the current GA release, Bigtop 1.2.1, for all hiera data, puppet recipes, and installable packages. Set this to 'master' to use the latest upstream bits.
- (string) Version of the cuda-repo deb to install. Valid options can be found at: http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64
- (boolean) Install the CUDA binaries if capable hardware is present (True by default). Set to False to disable CUDA installation regardless of capable hardware.