For additional help or useful information, we recommend you to check the official Apache Spark Documentation. Thanks for using this tutorial for installing Apache Spark on Ubuntu 18.04 LTS (Bionic Beaver) system. Open your favorite browser and navigate to or and complete the required the steps to finish the installation.Ĭongratulation’s! You have successfully installed Apache Spark. spark/bin/spark-shellĪpache Spark will be available on HTTP port 4040 by default. To activate these changes, run the following command for bashrc file: source ~/.bashrc bashrc file so that path can contain the Spark executable file path: I downloaded the Spark 3.0.0-preview () pre-built for Apache Hadoop 3. Well install this in a similar manner to how we installed Hadoop, above. Install Apache Spark using following command: wget Installing Spark The last bit of software we want to install is Apache Spark. Installing Apache Spark on Ubuntu 18.04 LTS. Verify the Java version by running the following command: java -version
Add the Oracle Java PPA to Apt with the following command: add-apt-repository ppa:webupd8team/java By default, Java is not available in Ubuntu’s repository. First make sure that all your system packages are up-to-date sudo apt-get updateĪpache Spark requires Java to be installed on your server. I will show you through the step by step installation Apache Spark on a 18.04 LTS (Bionic Beaver) server. The installation is quite simple and assumes you are running in the root account, if not you may need to add ‘sudo’ to the commands to get root privileges.
INSTALL APACHE SPARK UBUNTU 18.04 HOW TO
This article assumes you have at least basic knowledge of linux, know how to use the shell, and most importantly, you host your site on your own VPS. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured information processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala and Python, and also an optimized engine which supports overall execution charts.
Apache Spark is a fast and general-purpose cluster computing system.
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