Scala and spark Installation

                                       Scala & spark Installation

Step 1: Verifying Java Installation

Java installation is one of the mandatory things in installing Spark. Try the following command to verify the JAVA version.

$java -version 

If Java is already, installed on your system, you get to see the following response −

java version "1.7.0_71" 

Java(TM) SE Runtime Environment (build 1.7.0_71-b13) 

Java HotSpot(TM) Client VM (build 25.0-b02, mixed mode)

In case you do not have Java installed on your system, then Install Java before proceeding to next step.

Step 2: Verifying Scala installation

You should Scala language to implement Spark. So let us verify Scala installation using following command.

$scala -version

If Scala is already installed on your system, you get to see the following response −

Scala code runner version 2.11.6 -- Copyright 2002-2013, LAMP/EPFL

In case you don’t have Scala installed on your system, then proceed to next step for Scala installation.

Step 3: Downloading Scala

Download the latest version of Scala by visit the following link scala For this tutorial, we are using scala-2.11.6 version. After downloading, you will find the Scala tar file in the download folder.

Step 4: Installing Scala

Follow the below given steps for installing Scala.

Extract the Scala tar file

Type the following command for extracting the Scala tar file.

$ tar xvf scala-2.11.6.tgz

Move Scala software files

Use the following commands for moving the Scala software files, to respective directory (/usr/local/scala).

$ su – 

Password: 

# cd /home/Hadoop/Downloads/ 

# mv scala-2.11.6 /usr/local/scala 

# exit 

Set PATH for Scala

Use the following command for setting PATH for Scala.

$ export PATH=$PATH:/usr/local/scala/bin

Verifying Scala Installation

After installation, it is better to verify it. Use the following command for verifying Scala installation.

$scala -version

Step 5: Downloading Apache Spark

Download the latest version of Spark by visiting the following link  For this tutorial, we are using spark-1.3.1-bin-hadoop2.6 version. After downloading it, you will find the Spark tar file in the download folder.

Step 6: Installing Spark

Follow the steps given below for installing Spark.

Extracting Spark tar

The following command for extracting the spark tar file.

$ tar xvf spark-1.3.1-bin-hadoop2.6.tgz 

Moving Spark software files

The following commands for moving the Spark software files to respective directory (/usr/local/spark).

$ su – 

Password:  

# cd /home/Hadoop/Downloads/ 

# mv spark-1.3.1-bin-hadoop2.6 /usr/local/spark 

# exit 

Setting up the environment for Spark

Add the following line to ~/.bashrc file. It means adding the location, where the spark software file are located to the PATH variable.

export PATH = $PATH:/usr/local/spark/bin

Use the following command for sourcing the ~/.bashrc file.

$ source ~/.bashrc

Step 7: Verifying the Spark Installation

Write the following command for opening Spark shell.

$spark-shell

If spark is installed successfully then you will find the following output.

Spark assembly has been built with Hive, including Datanucleus jars on classpath 

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties 

15/06/04 15:25:22 INFO SecurityManager: Changing view acls to: hadoop 

15/06/04 15:25:22 INFO SecurityManager: Changing modify acls to: hadoop

15/06/04 15:25:22 INFO SecurityManager: SecurityManager: authentication disabled;

   ui acls disabled; users with view permissions: Set(hadoop); users with modify permissions: Set(hadoop) 

15/06/04 15:25:22 INFO HttpServer: Starting HTTP Server 

15/06/04 15:25:23 INFO Utils: Successfully started service 'HTTP class server' on port 43292. 

Welcome to 

      ____              __ 

     / __/__  ___ _____/ /__ 

    _\ \/ _ \/ _ `/ __/  '_/ 

   /___/ .__/\_,_/_/ /_/\_\   version 1.4.0 

      /_/  

                

Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_71) 

Type in expressions to have them evaluated. 

Spark context available as sc  

scala>