Dan Sullivan walks you through the steps needed to install Scala.
- [Instructor] Scala's freely available for downloading,…at scala-lang.org.…Now I have to open the browser…and navigate it to that website,…and I've selected download,…and I'm simply going to click and download Scala.…This download package is a compressed file.…So, it's done downloading,…I'm going to switch over to a terminal window,…and I'm going to change my default directory…to where I downloaded the Scala file.…
Now the commands I'm going to execute…will work on a Mac or Linux.…Now similar steps will work in Windows environment,…but the commands and the step tools…will be slightly different.…So, the first thing I want to do,…is I just want to list the download.…So I have a tar file,…that means that I'm going to use a tar command…to uncompress,…and now what that does is creates a folder for me.…
I'm going to move that folder from my downloads directory,…and I'm going to put that in user local.…Now I'm going to cd over to user local.…I want to be able to refer to this directory as Scala,…so I'm going to create something called a link.…
Dan also focuses on using Scala with Spark, a distributed processing platform. He first describes how to work with Resilient Distributed Datasets (RDDs)—a fundamental Spark data structure—and then explains how to use Scala with Spark DataFrames, a new class of data structure specially designed for analytic processing. He wraps up the course by providing a summary of advantages of using Scala for data science.
- The advantages of Scala for data science
- Scala data types
- Scala arrays, vectors, and ranges
- Parallel processing in Scala
- Mapping functions over parallel collections
- When and when not to use parallel collections
- Using SQL in Scala
- Scala and Spark RDDs
- Scala and Spark DataFrames
- Creating DataFrames
Skill Level Intermediate
Java for Data Scientists Essential Trainingwith Charles Kelly2h 43m Intermediate
1. Introduction to Scala
2. Parallel Processing in Scala
3. Using SQL in Scala
4. Scala and Spark RDDs
5. Scala and Spark DataFrames
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