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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.

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.

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 below

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>)

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 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

Add 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 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.

  • 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 Java

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).

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.

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.

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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This open-source distributed computing platform offers more powerful advantages than any other proprietary solutions. The diverse advantages of Apache Spark make it a very attractive big data framework. Apache Spark has huge potential to contribute to the big data-related business in the industry. Let’s now have a look at some of the common benefits of Apache Spark:Benefits of Apache Spark:SpeedEase of UseAdvanced AnalyticsDynamic in NatureMultilingualApache Spark is powerfulIncreased access to Big dataDemand for Spark DevelopersOpen-source community1. Speed:When comes to Big Data, processing speed always matters. Apache Spark is wildly popular with data scientists because of its speed. Spark is 100x faster than Hadoop for large scale data processing. Apache Spark uses in-memory(RAM) computing system whereas Hadoop uses local memory space to store data. Spark can handle multiple petabytes of clustered data of more than 8000 nodes at a time. 2. Ease of Use:Apache Spark carries easy-to-use APIs for operating on large datasets. It offers over 80 high-level operators that make it easy to build parallel apps.The below pictorial representation will help you understand the importance of Apache Spark.3. Advanced Analytics:Spark not only supports ‘MAP’ and ‘reduce’. It also supports Machine learning (ML), Graph algorithms, Streaming data, SQL queries, etc.4. Dynamic in Nature:With Apache Spark, you can easily develop parallel applications. Spark offers you over 80 high-level operators.5. Multilingual:Apache Spark supports many languages for code writing such as Python, Java, Scala, etc.6. Apache Spark is powerful:Apache Spark can handle many analytics challenges because of its low-latency in-memory data processing capability. It has well-built libraries for graph analytics algorithms and machine learning.7. Increased access to Big data:Apache Spark is opening up various opportunities for big data and making As per the recent survey conducted by IBM’s announced that it will educate more than 1 million data engineers and data scientists on Apache Spark. 8. Demand for Spark Developers:Apache Spark not only benefits your organization but you as well. Spark developers are so in-demand that companies offering attractive benefits and providing flexible work timings just to hire experts skilled in Apache Spark. As per PayScale the average salary for  Data Engineer with Apache Spark skills is $100,362. For people who want to make a career in the big data, technology can learn Apache Spark. You will find various ways to bridge the skills gap for getting data-related jobs, but the best way is to take formal training which will provide you hands-on work experience and also learn through hands-on projects.9. 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