import theme for eclipse for scala for mac

Import Theme For Eclipse For Scala Full Distributed Cluster
Import Theme For Eclipse For Scala How To Set Up
Import Theme For Eclipse For Scala Mac OSx High

If you dont have a cluster available you can quickly set one up on AWS using Hortonworks Data Cloud or on Azure using HDInsight (which is powered by Hortonworks).

For this tutorial well be using Scala, but Spark also supports development with Java, and Python.

Import Theme For Eclipse For Scala Mac OSx High

We will be using be using IntelliJ Version: 2018.2 as our IDE running on Mac OSx High Sierra, and since were using Scala well use SBT as our build manager.

Import Theme For Eclipse For Scala How To Set Up

By the end of the tutorial, youll know how to set up IntelliJ, how to use SBT to manage dependencies, how to package and deploy your Spark application, and how to connect your live program to a debugger.

It may take a minute or two to generate all the folders needed, in the end your folder structure should look something like this.

For example, build.properties allows you to change the SBT version used when compiling your project.

Well show you how to use this file to import third party libraries and documentation.

This is necessary if we want IntelliJ to recognize Spark code.

The syntax additionally appends the Scala version, in our case transforming spark-core into spark-core2.2.

The important thing to remember is that each version of Spark is designed to be compatible with a specific version of Scala, so Spark might not compile or run correctly if you use the wrong version of Scala.

For Spark 2.3.x you need to use Scala 2.11.12.

If SBT fails to import your libraries you may want to search mvnrepository to find out what your build.sbt file should look like.

For production work it is preferable to pull Spark directly from Hortonworks repository, this HCC article will help you get started setting up for production.

Right click and save shakespeare.txt to your computer, later well want to Spark to retrieve this file from HDFS (Hadoop Distributed File System), so lets place it there.

If everything is set up correctly, the IDE should print HelloWorld.

This should run the Spark job and print the frequency of each word that appears in Shakespeare, the expected output looks like this.

To run Spark against multiple machines, we would need to change this value to YARN.

This is a good way to quickly build and test an application, but it is somewhat unrealistic since Spark is only running on a single machine.

In production use Spark will usually process data stored on a distributed file system like HDFS (or perhaps S3 or Azure Blog Storage if running in the cloud).

Spark is also usually run in clustered mode (ie, distributed across many machines).

First well learn how to deploy Spark against the Hortonworks Data Platform Sandbox, which is a single-node Hadoop environment, and then well learn how to deploy Spark in the cloud.

Import Theme For Eclipse For Scala Full Distributed Cluster

Although were still running Spark on a single machine, well be using HDFS and YARN (a cluster resource manager), so this will be a closer approximation of running a full distributed cluster than what weve done previously.

A jar is a file that contains both our code and all the dependencies that our code needs to work.

By packaging our code as an assembly we guarantee that all dependency jars (as defined in build.sbt) will be present when our code runs.

Right click on the main file and select Copy Path, now the path is copied to your clipboard.

We need to specify the main class, the jar to run, and the run mode (local or cluster).

Import Theme For Eclipse For Scala For Mac