Scalable Programming with Scala and Spark

Course Description

Get your data to fly using Spark and Scala for analytics, machine learning and data science.

If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.

Scala is a general purpose programming language - like Java or C++. It's functional programming nature and the availability of a REPL environment make it particularly suited for a distributed computing framework like Spark.

Using Spark and Scala you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.

---

Learning Outcomes

Use Spark for a variety of analytics and Machine Learning tasks

Understand functional programming constructs in Scala

Implement complex algorithms like PageRank or Music Recommendations

Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings

Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX

Write code in Scala REPL environments and build Scala applications with an IDE

---

Pre-requisites:

All examples work with or without Hadoop. If you would like to use Spark with Hadoop, you'll need to have Hadoop installed (either in pseudo-distributed or cluster mode).

The course assumes experience with one of the popular object-oriented programming languages like Java/C++.

---

Who is this course intended for?

Engineers who want to use a distributed computing engine for batch or stream processing or both

Analysts who want to leverage Spark for analyzing interesting datasets

Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it.