Rubén Larenas · Nov 22, 2021 2m read

Apache Zeppelin + IRIS Quick Start

Apache Zeppelin it's a Multi-purpose notebook that allow you:

  •     Data Ingestion
  •     Data Discovery
  •     Data Analytics
  •     Data Visualization and Collaboration.

Apache Zeppelin interpreter concept allows any language/data-processing-backend to be plugged into Zeppelin. Currently Apache Zeppelin supports many interpreters such as Apache Spark, Apache Flink, Python, R, JDBC, Markdown and Shell.

It provides you a safe environment to get insigth of your data. You can take avantage of Zeppelin's higligths using both , JDBC and Spark IRIS native connectors.

This is a Quick Start Guide just to put you on the track.


1.- Donwload and save Zeppellin from the official web site  --> (Here)

2.- Unpackage the distro in the installation folder (your election)

3.- You will need install a JDK (if you don't have it)

4.- When JDK is Installed you can run Zeppelin #bash> sudo ./<zeppelin_path>/bin/ start   (This is a Linux / Unix based install ... but there is a bash file for the Windows based systems.)

5.- Once it's running you can use it through the browser http://[server_ip]:8080

6.- If everything was OK you should see this screen

7.- Now it's necessary to setup the interpreters


8.- Let's config Spark Connector (for using the full potencial of IRIS + Zeppelin i.e. with Scala or R)

8.1 In the "Artifacts" section include routes to jdbc and IRIS spark connector

9.- Now let's configure the JDBC Interpreter , in defaul_url you must set jdbc:IRIS://<your_iris_server>:<port>/<namespace>, also your default user and default password, finally default.driver is com.intersystems.jdbc.IRISDriver

9.1 We continue configuring the JDBC IRIS dependencies

10.- It's Done! now we can use Zeppelin + IRIS

Let's use JDBC interpreter as a quick example

1.- Back in to the Zeppelin's landing page. and create a new notebook

2.-  in the new Notebook create a new Paragraph, in the case of using the jdbc interpreter, the sentence must start as % jdbc

You will get your data as a table by default, but quickly you can toggle to a graph just changing and setting the view

You can combine different queries , views and layouts to easily get really powerfull dashboards


I really hope that information was useful and feel free to share it or improve it.

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can it be used on older version of Cache like 2020?

Hi Sandeep

JDBC driver and Spark Connector are available since 2018 versions (Here  and Here

Hope it helps.

nice article, thank you for sharing.

Small note - Download is misspelled in the first step of your directions