zeppelin #48

Supports: xenial
Add to new model


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 zeppelin 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.

Hadoop Integration

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 hadoop-processing bundle.

Spark Integration

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 spark units.

Network-Restricted Environments

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:

juju status

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.

Smoke Test

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 reports 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 spark://xxx.xxx.xxx.xxx:7077 URL for the Spark Master. This is only available when the spark charm is in standalone mode -- local and yarn modes are not supported.


Apache Bigtop tracks issues using JIRA (Apache account required). File an issue for this charm at:


Ensure Bigtop is selected as the project. Typically, charm issues are filed in the deployment component with the latest stable release selected as the affected version. Any uncertain fields may be left blank.

Contact Information



(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.