There are many facets to the Apache Spark ecosystem. In this video, learn about its benefits.
- [Instructor] If you head over to the Apache Spark…web site, you can see some of the reasons…that people are using it.…It's fast, it's easy to develop in…because it has a couple of language APIs,…meaning that you can access it using Scala, Java,…Python, R, or SQL.…And it has its own ecosystem.…Just so you know, Apache Spark is written in Scala.…Now the developers of Apache Spark wanted it to be fast…to work on their large data sets.…But when they were working on their big data projects,…many of the scripting languages didn't fit the bill.…
Because Spark runs on a Java virtual machine, or JVM,…it lets you call into other Java-based big data systems…such as Cassandra, HTFS, and Hbase.…Spark runs locally as well as in a cluster,…on premise, or in a cloud.…It runs on top of Hadoop YARN, Apache Mesos,…standalone, or in the Cloud, such as Amazon EC2…or IBM Bluemix.…Although Spark is designed to work on large, distributed…clusters, you can also use it on a single machine mode.…
We'll use this mode for the rest of this course.…
- Benefits of the Apache Spark ecosystem
- Working with the DataFrame API
- Working with columns and rows
- Leveraging built-in Spark functions
- Creating your own functions in Spark
- Working with Resilient Distributed Datasets (RDDs)
Skill Level Intermediate
1. Introduction to Apache Spark
2. Technical Setup
3. Working with the DataFrame API
5. Resilient Distributed Datasets (RDDs)
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