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How to install Apache Spark on Windows?

Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.In this document, we will cover the installation procedure of Apache Spark on Windows 10 operating systemPrerequisitesThis guide assumes that you are using Windows 10 and the user had admin permissions.System requirements:Windows 10 OSAt least 4 GB RAMFree space of at least 20 GBInstallation ProcedureStep 1: Go to the below official download page of Apache Spark and choose the latest release. For the package type, choose ‘Pre-built for Apache Hadoop’.The page will look like below.Step 2:  Once the download is completed unzip the file, to unzip the file using WinZip or WinRAR or 7-ZIP.Step 3: Create a folder called Spark under your user Directory like below and copy paste the content from the unzipped file.C:\Users\<USER>\SparkIt looks like below after copy-pasting into the Spark directory.Step 4: Go to the conf folder and open log file called, log4j.properties. template. Change INFO to WARN (It can be ERROR to reduce the log). This and next steps are optional.Remove. template so that Spark can read the file.Before removing. template all files look like below.After removing. template extension, files will look like belowStep 5: Now we need to configure path.Go to Control Panel -> System and Security -> System -> Advanced Settings -> Environment VariablesAdd below new user variable (or System variable) (To add new user variable click on New button under User variable for <USER>)Click OK.Add %SPARK_HOME%\bin to the path variable.Click OK.Step 6: Spark needs a piece of Hadoop to run. For Hadoop 2.7, you need to install winutils.exe.You can find winutils.exe from below pageDownload it.Step 7: Create a folder called winutils in C drive and create a folder called bin inside. Then, move the downloaded winutils file to the bin folder.C:\winutils\binAdd the user (or system) variable %HADOOP_HOME% like SPARK_HOME.Click OK.Step 8: To install Apache Spark, Java should be installed on your computer. If you don’t have java installed in your system. Please follow the below processJava Installation Steps:Go to the official Java site mentioned below  the page.Accept Licence Agreement for Java SE Development Kit 8u201Download jdk-8u201-windows-x64.exe fileDouble Click on Downloaded .exe file, you will the window shown below.Click Next.Then below window will be displayed.Click Next.Below window will be displayed after some process.Click Close.Test Java Installation:Open Command Line and type java -version, then it should display installed version of JavaYou should also check JAVA_HOME and path of %JAVA_HOME%\bin included in user variables (or system variables)1. In the end, the environment variables have 3 new paths (if you need to add Java path, otherwise SPARK_HOME and HADOOP_HOME).2. Create c:\tmp\hive directory. This step is not necessary for later versions of Spark. When you first start Spark, it creates the folder by itself. However, it is the best practice to create a folder.C:\tmp\hiveTest Installation:Open command line and type spark-shell, you get the result as below.We have completed spark installation on Windows system. Let’s create RDD and     Data frameWe create one RDD and Data frame then will end up.1. We can create RDD in 3 ways, we will use one way to create RDD.Define any list then parallelize it. It will create RDD. Below is code and copy paste it one by one on the command line.val list = Array(1,2,3,4,5) val rdd = sc.parallelize(list)Above will create RDD.2. Now we will create a Data frame from RDD. Follow the below steps to create Dataframe.import spark.implicits._ val df = rdd.toDF("id")Above code will create Dataframe with id as a column.To display the data in Dataframe use below command.Df.show()It will display the below output.How to uninstall Spark from Windows 10 System: Please follow below steps to uninstall spark on Windows 10.Remove below System/User variables from the system.SPARK_HOMEHADOOP_HOMETo remove System/User variables please follow below steps:Go to Control Panel -> System and Security -> System -> Advanced Settings -> Environment Variables, then find SPARK_HOME and HADOOP_HOME then select them, and press DELETE button.Find Path variable Edit -> Select %SPARK_HOME%\bin -> Press DELETE ButtonSelect % HADOOP_HOME%\bin -> Press DELETE Button -> OK ButtonOpen Command Prompt the type spark-shell then enter, now we get an error. Now we can confirm that Spark is successfully uninstalled from the System.
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How to install Apache Spark on Windows?

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How to install Apache Spark on Windows?

Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.

In this document, we will cover the installation procedure of Apache Spark on Windows 10 operating system

Prerequisites

This guide assumes that you are using Windows 10 and the user had admin permissions.

System requirements:

  • Windows 10 OS
  • At least 4 GB RAM
  • Free space of at least 20 GB

Installation Procedure

Step 1: Go to the below official download page of Apache Spark and choose the latest release. For the package type, choose ‘Pre-built for Apache Hadoop’.

The page will look like below.

Apache Spark installation Process

Step 2:  Once the download is completed unzip the file, to unzip the file using WinZip or WinRAR or 7-ZIP.

Step 3: Create a folder called Spark under your user Directory like below and copy paste the content from the unzipped file.

C:\Users\<USER>\Spark

It looks like below after copy-pasting into the Spark directory.

Apache Spark installation Process

Step 4: Go to the conf folder and open log file called, log4j.properties. template. Change INFO to WARN (It can be ERROR to reduce the log). This and next steps are optional.

Remove. template so that Spark can read the file.

Before removing. template all files look like below.

Apache Spark installation Process

After removing. template extension, files will look like below

Apache Spark installation Process

Step 5: Now we need to configure path.

Go to Control Panel -> System and Security -> System -> Advanced Settings -> Environment Variables

Add below new user variable (or System variable) (To add new user variable click on New button under User variable for <USER>)

Apache Spark installation Process

Click OK.

Add %SPARK_HOME%\bin to the path variable.

Apache Spark installation Process

Click OK.

Step 6: Spark needs a piece of Hadoop to run. For Hadoop 2.7, you need to install winutils.exe.

You can find winutils.exe from below page

Download it.

Step 7: Create a folder called winutils in C drive and create a folder called bin inside. Then, move the downloaded winutils file to the bin folder.

C:\winutils\bin

Apache Spark installation Process

Add the user (or system) variable %HADOOP_HOME% like SPARK_HOME.

Apache Spark installation Process

Apache Spark installation Process

Click OK.

Step 8: To install Apache Spark, Java should be installed on your computer. If you don’t have java installed in your system. Please follow the below process

Java Installation Steps:

  • Go to the official Java site mentioned below  the page.

Accept Licence Agreement for Java SE Development Kit 8u201

  • Download jdk-8u201-windows-x64.exe file
  • Double Click on Downloaded .exe file, you will the window shown below.

Java Installation Steps

  • Click Next.
  • Then below window will be displayed.

Java Installation Steps

  • Click Next.
  • Below window will be displayed after some process.

Java Installation Steps

  • Click Close.

Test Java Installation:

Open Command Line and type java -version, then it should display installed version of Java

Java Installation Steps

You should also check JAVA_HOME and path of %JAVA_HOME%\bin included in user variables (or system variables)

1. In the end, the environment variables have 3 new paths (if you need to add Java path, otherwise SPARK_HOME and HADOOP_HOME).

Java Installation Steps

2. Create c:\tmp\hive directory. This step is not necessary for later versions of Spark. When you first start Spark, it creates the folder by itself. However, it is the best practice to create a folder.

C:\tmp\hive

Test Installation:

Open command line and type spark-shell, you get the result as below.

Test Installation in Apache Spark

We have completed spark installation on Windows system. Let’s create RDD and     Data frame

We create one RDD and Data frame then will end up.

1. We can create RDD in 3 ways, we will use one way to create RDD.

Define any list then parallelize it. It will create RDD. Below is code and copy paste it one by one on the command line.

val list = Array(1,2,3,4,5)
val rdd = sc.parallelize(list)

Above will create RDD.

2. Now we will create a Data frame from RDD. Follow the below steps to create Dataframe.

import spark.implicits._
val df = rdd.toDF("id")

Above code will create Dataframe with id as a column.

To display the data in Dataframe use below command.

Df.show()

It will display the below output.

Test Installation in Apache Spark

How to uninstall Spark from Windows 10 System: 

Please follow below steps to uninstall spark on Windows 10.

  1. Remove below System/User variables from the system.
  2. SPARK_HOME
  3. HADOOP_HOME

To remove System/User variables please follow below steps:

Go to Control Panel -> System and Security -> System -> Advanced Settings -> Environment Variables, then find SPARK_HOME and HADOOP_HOME then select them, and press DELETE button.

Find Path variable Edit -> Select %SPARK_HOME%\bin -> Press DELETE Button

Select % HADOOP_HOME%\bin -> Press DELETE Button -> OK Button

Open Command Prompt the type spark-shell then enter, now we get an error. Now we can confirm that Spark is successfully uninstalled from the System.

Ravichandra

Ravichandra Reddy Maramreddy

Blog Author

Ravichandra is a developer and specialized in Spark and Hadoop Ecosystems, HDFS and MapReduce which includes estimations, requirement analysis, design development, coordination, validation in-depth understanding of game design practices. Having extensive experience in Spark, Spark Streaming, Pyspark, Scala, Shell, Oozie, Hive, HBase, Hue, Java, SparkSQL, Kafka, WSO2. Having extensive experience in using Data structures and algorithms.

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1 comments

shweta 13 May 2019

complete guidance about Apache Spark that how to installed... thanks a lot for that.....very helpful.......

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Apache Kafka Vs Apache Spark: Know the Differences

A new breed of ‘Fast Data’ architectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. - Dean Wampler (Renowned author of many big data technology-related books)Dean Wampler makes an important point in one of his webinars. The demand for stream processing is increasing every day in today’s era. 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If transaction data is stream-processed, fraudulent transactions can be identified and stopped before they are even complete.Real-time Processing: If event time is very relevant and latencies in the second's range are completely unacceptable then it’s called Real-time (Rear real-time) processing. For ex. flight control system for space programsComplex Event Processing (CEP): CEP utilizes event-by-event processing and aggregation (for example, on potentially out-of-order events from a variety of sources, often with large numbers of rules or business logic).We have multiple tools available to accomplish above-mentioned Stream, Realtime or Complex event Processing. Spark Streaming, Kafka Stream, Flink, Storm, Akka, Structured streaming are to name a few. We will try to understand Spark streaming and Kafka stream in depth further in this article. 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Following data flow diagram explains the working of Spark streaming. Spark Streaming provides a high-level abstraction called discretized stream or DStream, which represents a continuous stream of data. DStreams can be created either from input data streams from sources such as Kafka, Flume, and Kinesis, or by applying high-level operations on other DStreams. Internally, a DStream is represented as a sequence of RDDs. Think about RDD as the underlying concept for distributing data over a cluster of computers. Why one will love using Apache Spark Streaming?It makes it very easy for developers to use a single framework to satisfy all the processing needs. They can use MLib (Spark's machine learning library) to train models offline and directly use them online for scoring live data in Spark Streaming. 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Why a Career in Big Data Is the Right Choice for Y...

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