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Zeppelin Installation

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19 November 2015


Zeppelin

Documentation: User Guide
Mailing List: User and Dev mailing list
Continuous Integration: Build Status
Contributing: Contribution Guide
License: Apache 2.0

Zeppelin, a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.

Core feature:

  • Web based notebook style editor.
  • Built-in Apache Spark support

To know more about Zeppelin, visit our web site http://zeppelin.incubator.apache.org

Requirements

  • Java 1.7
  • Tested on Mac OSX, Ubuntu 14.X, CentOS 6.X
  • Maven (if you want to build from the source code)
  • Node.js Package Manager

Getting Started

Before Build

If you don’t have requirements prepared, install it. (The installation method may vary according to your environment, example is for Ubuntu.)

sudo apt-get update
sudo apt-get install git
sudo apt-get install openjdk-7-jdk
sudo apt-get install npm
sudo apt-get install libfontconfig

# install maven
wget http://www.eu.apache.org/dist/maven/maven-3/3.3.3/binaries/apache-maven-3.3.3-bin.tar.gz
sudo tar -zxf apache-maven-3.3.3-bin.tar.gz -C /usr/local/
sudo ln -s /usr/local/apache-maven-3.3.3/bin/mvn /usr/local/bin/mvn

Notes:

  • Ensure node is installed by running node --version
  • Ensure maven is running version 3.1.x or higher with mvn -version

Build

If you want to build Zeppelin from the source, please first clone this repository, then:

mvn clean package -DskipTests

To build with a specific Spark version, Hadoop version or specific features, define one or more of the spark, pyspark, hadoop and yarn profiles, such as:

-Pspark-1.5   [Version to run in local spark mode]
-Ppyspark     [optional: enable PYTHON support in spark via the %pyspark interpreter]
-Pyarn        [optional: enable YARN support]
-Dhadoop.version=2.2.0  [hadoop distribution]
-Phadoop-2.2            [hadoop version]

Currently, final/full distributions run with:

mvn clean package -Pspark-1.5 -Phadoop-2.4 -Pyarn -Ppyspark

Spark 1.5.x

mvn clean package -Pspark-1.5 -Dhadoop.version=2.2.0 -Phadoop-2.2 -DskipTests

Spark 1.4.x

mvn clean package -Pspark-1.4 -Dhadoop.version=2.2.0 -Phadoop-2.2 -DskipTests

Spark 1.3.x

mvn clean package -Pspark-1.3 -Dhadoop.version=2.2.0 -Phadoop-2.2 -DskipTests

Spark 1.2.x

mvn clean package -Pspark-1.2 -Dhadoop.version=2.2.0 -Phadoop-2.2 -DskipTests 

Spark 1.1.x

mvn clean package -Pspark-1.1 -Dhadoop.version=2.2.0 -Phadoop-2.2 -DskipTests 

CDH 5.X

mvn clean package -Pspark-1.2 -Dhadoop.version=2.5.0-cdh5.3.0 -Phadoop-2.4 -DskipTests

For the MapR Hadoop Distribution, these profiles will handle the Hadoop version. As MapR allows different versions of Spark to be installed, you should specify which version of Spark is installed on the cluster by adding a Spark profile (-Pspark-1.2, -Pspark-1.3, etc.) as needed. For Hive, check the hive/pom.xml and adjust the version installed as well. The correct Maven artifacts can be found for every version of MapR at http://doc.mapr.com

MapR 3.x

mvn clean package -Pmapr3 -DskipTests

MapR 4.0.x

mvn clean package -Pmapr40 -DskipTests

MapR 4.1

mvn clean package -Pmapr41 -DskipTests

MapR 5.0

mvn clean package -Pmapr50 -DskipTests

Yarn (Hadoop 2.7.x)

mvn clean package -Pspark-1.4 -Dspark.version=1.4.1 -Dhadoop.version=2.7.0 -Phadoop-2.6 -Pyarn -DskipTests

Yarn (Hadoop 2.6.x)

mvn clean package -Pspark-1.1 -Dhadoop.version=2.6.0 -Phadoop-2.6 -Pyarn -DskipTests

Yarn (Hadoop 2.4.x)

mvn clean package -Pspark-1.1 -Dhadoop.version=2.4.0 -Phadoop-2.4 -Pyarn -DskipTests

Yarn (Hadoop 2.3.x)

mvn clean package -Pspark-1.1 -Dhadoop.version=2.3.0 -Phadoop-2.3 -Pyarn -DskipTests

Yarn (Hadoop 2.2.x)

mvn clean package -Pspark-1.1 -Dhadoop.version=2.2.0 -Phadoop-2.2 -Pyarn -DskipTests

Ignite (1.1.0-incubating and later)

mvn clean package -Dignite.version=1.1.0-incubating -DskipTests

Spark-Cassandra integration (Spark 1.1.x)

mvn clean package -Pcassandra-spark-1.1 -Dhadoop.version=2.6.0 -Phadoop-2.6 -DskipTests

Spark-Cassandra integration (Spark 1.2.x)

mvn clean package -Pcassandra-spark-1.2 -Dhadoop.version=2.6.0 -Phadoop-2.6 -DskipTests

Spark-Cassandra integration (Spark 1.3.x)

mvn clean package -Pcassandra-spark-1.3 -Dhadoop.version=2.6.0 -Phadoop-2.6 -DskipTests

Spark-Cassandra integration (Spark 1.4.x)

mvn clean package -Pcassandra-spark-1.4 -Dhadoop.version=2.6.0 -Phadoop-2.6 -DskipTests

Spark-Cassandra integration (Spark 1.5.x)

mvn clean package -Pcassandra-spark-1.5 -Dhadoop.version=2.6.0 -Phadoop-2.6 -DskipTests

Configure

If you wish to configure Zeppelin option (like port number), configure the following files:

./conf/zeppelin-env.sh
./conf/zeppelin-site.xml

(You can copy ./conf/zeppelin-env.sh.template into ./conf/zeppelin-env.sh. Same for zeppelin-site.xml.)

Setting SPARK_HOME and HADOOP_HOME

Without SPARK_HOME and HADOOP_HOME, Zeppelin uses embedded Spark and Hadoop binaries that you have specified with mvn build option. If you want to use system provided Spark and Hadoop, export SPARK_HOME and HADOOP_HOME in zeppelin-env.sh You can use any supported version of spark without rebuilding Zeppelin.

# ./conf/zeppelin-env.sh
export SPARK_HOME=...
export HADOOP_HOME=...

External cluster configuration

Mesos

# ./conf/zeppelin-env.sh
export MASTER=mesos://...
export ZEPPELIN_JAVA_OPTS="-Dspark.executor.uri=/path/to/spark-*.tgz" or SPARK_HOME="/path/to/spark_home"
export MESOS_NATIVE_LIBRARY=/path/to/libmesos.so

If you set SPARK_HOME, you should deploy spark binary on the same location to all worker nodes. And if you set spark.executor.uri, every worker can read that file on its node.

Yarn

# ./conf/zeppelin-env.sh
export SPARK_HOME=/path/to/spark_dir

Run

./bin/zeppelin-daemon.sh start

browse localhost:8080 in your browser.

For configuration details check ./conf subdirectory.

Package

To package the final distribution including the compressed archive, run:

  mvn clean package -Pbuild-distr

To build a distribution with specific profiles, run:

  mvn clean package -Pbuild-distr -Pspark-1.5 -Phadoop-2.4 -Pyarn -Ppyspark

The profiles -Pspark-1.5 -Phadoop-2.4 -Pyarn -Ppyspark can be adjusted if you wish to build to a specific spark versions, or omit support such as yarn.

The archive is generated under zeppelin-distribution/target directory

Run end-to-end tests

Zeppelin comes with a set of end-to-end acceptance tests driving headless selenium browser

  #assumes zeppelin-server running on localhost:8080 (use -Durl=.. to override)
  mvn verify

  #or take care of starting\stoping zeppelin-server from packaged _zeppelin-distribuion/target_
  mvn verify -P using-packaged-distr

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