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.

As a Multi-purpose Notebook, Apache Zeppelin is the place for interactive:

• Data Ingestion
• Data Discovery
• Data Analytics
• Data Visualization & Collaboration

This is a subordinate charm that requires the apache-spark interface. This means that you will need to deploy a base Apache Spark cluster to use Zeppelin. An easy way to deploy the recommended environment is to use the apache-hadoop-spark-zeppelin bundle. This will deploy the Apache Hadoop platform with an Apache Spark + Zeppelin unit that communicates with the cluster by relating to the apache-hadoop-plugin subordinate charm:

juju-quickstart apache-hadoop-spark-zeppelin

Alternatively, you may manually deploy the recommended environment as follows:

juju deploy apache-hadoop-hdfs-master hdfs-master
juju deploy apache-hadoop-yarn-master yarn-master
juju deploy apache-hadoop-compute-slave compute-slave
juju deploy apache-hadoop-plugin plugin
juju deploy apache-spark spark
juju deploy apache-zeppelin zeppelin

juju add-relation yarn-master hdfs-master
juju add-relation compute-slave yarn-master
juju add-relation compute-slave hdfs-master
juju add-relation plugin yarn-master
juju add-relation plugin hdfs-master
juju add-relation spark plugin
juju add-relation zeppelin spark

Once deployment is complete, expose the zeppelin service:

juju expose zeppelin

You may now access the web interface at http://{spark_unit_ip_address}:9090. The ip address can be found by running juju status spark | grep public-address.

By default, this deployment uses Spark in YARN mode and supports storing job data in HDFS. To test this, access the Zeppelin web interface at http://{spark_unit_ip_address}:9090. The ip address can be found by running juju status spark | grep public-address.

• Verify there is a green icon in the upper-right corner that says "Connected"
• Click the Zeppelin HDFS Tutorial link
• Click the Save button to bind the tutorial to our supported interpreters
• Click the Play button (arrow at the top of the page)
• Click OK when prompted to run all paragraphs

The tutorial may take 5-10 minutes to run as it retrieves sample data, processes jobs, and stores results in HDFS. When successful, each paragraph will report FINISHED in their respective upper-right corners

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