Struggling to conquer Apache Spark?

Learning is hard enough as it is but when you bring in distributed computing frameworks in sophisticated programming languages - things don't get any easier. While self-study can certainly help, without a good guide, things are always more difficult than they should be. That's why I created Spark Tutorials, to make it easier to learn and use Apache Spark. is here to provide simple, easy to follow tutorials to help you get up and running quickly. You'll learn the foundational abstractions in Apache Spark from RDDs to DataFrames and MLLib. Start off with some of the articles below.

Building Apache Spark on your Local Machine

This article will walk you through how to build Apache Spark for usage on your local machine. After that you'll be able to create Spark Clusters or try out Spark on your local computer.

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Spark MLLib - Predict Store Sales with ML Pipelines

In this tutorial we're going to be doing a full-stack machine learning project. We're going all the way from data manipulation to feature creation and finally serving predictions.

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Opening CSV Files in Apache Spark - The Spark Data Sources API and Spark-CSV

This guide will show you how to read in csv files in Apache Spark. We'll walk through how to use this package in both Python and Scala.

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