Zeppelin
- By bigdata-charmers
- Big Data
juju deploy zeppelin
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Overview
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.
Deploying
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:
http://ZEPPELIN_PUBLIC_IP:9080
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.
Verifying
Status
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>
Limitations
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.
Issues
Apache Bigtop tracks issues using JIRA (Apache account required). File an issue for this charm at:
https://issues.apache.org/jira/secure/CreateIssue!default.jspa
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.