Install Hadoop with Spark and the Scala Programming Language
Introduction to Hadoop, Spark, and Scala
The open-source Apache Hadoop framework is used to process huge datasets across cluster nodes. Its distributed file system called HDFS is at the heart of Hadoop. Because Hadoop is Java-built, it seamlessly harmonizes with simplistic programming models and this results in providing a vast amount of scaling capabilities.
Apache Spark is the analytics engine that powers Hadoop. Large dataset processing requires a reliable way to handle and distribute heavy workloads fast and easy application building.
Object-oriented Scalable Language or Scala is a functional, statically typed programming language that runs on the Java Virtual Machine (JVM). Apache Spark, which is written on Scala, has high-performance large dataset processing proficiency.
This tutorial will explain the steps on how to setup the big three essentials for large dataset processing: Hadoop Spark Scala.
NOTE: Proceed with this tutorial if your operating system is UNIX-based. For example, if you use Linux or a macOS X or similar, these instructions will work for you. However, the steps given here for setting up Hadoop Spark Scala don’t apply to Windows OS systems.
Scala, Java, and the Spark framework
There are benefits to using Scala’s framework. With Scala, functionality is preferred over all paradigms in coding that are object-oriented. This direction enables it to outperform Java. The framework for Spark uses Scala and Hadoop is based on it.
Open JDK is another perk of Scala. Unlike Oracle JDK, Scala is free. Developers bypass the added expense of paying fees for subscriptions or licenses.
Prerequisites to using Spark
Install Visual Studio Code for your environment for developing.
Scala Syntaxextension from Visual Studio Code to install Scala.
Install Eclipse or another type of IDE.
NOTE: If you opt to select a different IDE other than Eclipse, make sure it supports both Scala and Java syntaxes.
Install Java before using Spark
Install and run Java.
Verify the installation with this command:
NOTE: Linux users, the package manager and repository for your distro is the best way to install Java, the
Installing Java on macOS with Homebrew
- Use Homebrew with this command
brew cask install javaif you’re installing Java on a macOS X.
Install the Hadoop cluster
Perform a primary node Hadoop cluster installation prior to installing Scala or Spark.
Install Hadoop on macOS X using Homebrew
- MacOS users, install Hadoop with the Homebrew with the command
Install Hadoop on Linux
- Linux users, Apache has archived version of Hadoop for your type of OS. Use the
wgetcommand. Next, input the command
tar -xvfand then the path of the archive you downloaded along with the filename. You’re performing a file extraction. Here’s the code:
tar xzf hadoop-3.2.1.tar.gz
When you’re finished with the
tarextraction process, change the name of the folder.
sudoprivileges with the command
mvto put the folder in the directory
For macOS, use the sbt compiler open-source build tool.
sudo mv hadoop /usr/local/hadoop
Set the path for Hadoop in the ~/.bashrc file
Use a text editor such as gedit, nano, vim, or try Sublime IDE to complete a Hadoop path export in the script
~/.bashrc. The command for Sublime is
subl ~/.bashrc. Otherwise, use one of the text editors mentioned to continue the installation processes for Hadoop Spark Scala.
Add the commands for
- Save the file with the edits, and then use the command
sourceto perform a file reload.
From a terminal window, confirm the variable
$PATHaddition with the
Alternatively, input this command below to get the version number of Hadoop:
- The path root of your Hadoop
HDFScan be found with this command:
NOTE: Try to export the Hadoop configuration directory files
HADOOP_CONF_DIRagain if errors were returned when you checked the path.
Fixing the command not found error in Hadoop
hadoop: command not founderror by verifying the path of the directory. Check system paths such as
Next, confirm that the commands for
exportlocated in your profile for bash are pointed to the system path.
Finally, use the command
sourceto do a bash profile reload.
Install the Scala programming language
If you’re using a macOS, use the sbt compiler to install Scala or read on to learn how to use Homebrew command.
apt-getgives you the default Scala stable release for distros of Linux with this code:
NOTE: Always check that you have the latest stable version of Scala. It’s listed on the site.
- As promised, here’s the Scala installation via the Homebrew method for macOS users:
- From a terminal window within Scala, use the command
scalato get the version information:
- To leave the Scala interface and get back to a command prompt, type
Troubleshooting compiling and execution in Scala
- Troubleshoot Linux compiling errors by uninstalling
scala-librarydefaults. It could be a compatibility issue, so try to reinstall another version of
scalato continue moving forward with the installation steps for Hadoop Spark Scala.
Uninstall Scala from Debian Linux
- Repair Debian Linux distros by reinstalling Scala. First, uninstall
scala-libraryusing Oracle JDK and sudo command:
sudo apt-get remove scala
sudo apt-get remove --auto-remove scala
sudo apt-get purge scala
Install a different version of Scala
- Get a more compatible version of Scala with the
- Lastly, install the
.debDebian packages with the
- Use Homebrew for the Spark installation if you have a macOS:
- Linux systems must download Spark and build it. See the next section to learn how to do it.
Build Spark on Linux
Hadoop versions 2.7 or later, download the Spark 3.0 preview version.
All other versions of Hadoop, get the stable version.
Next, from a terminal window, use
tar xvfto extract the files:
- Rename the extracted folder, and then put it in the directory
/optin Linux using the command
NOTE: You must have elevated privileges for
sudoto use the command stated above due to the directory
/optpermissions restrictions to complete the steps for the Hadoop Spark Scala installations.
- Modify the bash profile script once more with this command:
- Save the file.
Use the Spark Shell
- From a terminal window, access the Spark shell:
- Within the interface, add the library for Apache Spark:
- Exit with the command
The Hadoop Spark Scala represents a set of large dataset processing fundamentals that benefit developers. They realize that application development occurs fast when all three are utilized together. And it’s no secret that when datasets are huge, speed in processing matters. All things considered, now’s the time to install Hadoop with Spark and the Scala programming language. When you do, increased productivity is within your reach.
Pilot the ObjectRocket Platform Free!
Try Fully-Managed CockroachDB, Elasticsearch, MongoDB, PostgreSQL (Beta) or Redis.Get Started