Article
Rubén Larenas · Nov 22 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/zeppelin-daemon.sh 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.