Hadoop is indispensible when it comes to processing big data?as necessary to understanding your information as servers are to storing it. This course is your introduction to Hadoop, its file system (HDFS), its processing engine (MapReduce), and its many libraries and programming tools. Developer and big-data consultant Lynn Langit shows how to set up a Hadoop development environment, run and optimize MapReduce jobs, code basic queries with Hive and Pig, and build workflows to schedule jobs. Plus, get a sneak peek at some up-and-coming libraries like Impala and the lightning-fast Spark.
LEVEL – Intermediate
COURSE TOPICS:
Understanding Hadoop core components: HDFS and MapReduce
Setting up your Hadoop development environment
Working with the Hadoop file system
Running and tracking Hadoop jobs
Tuning MapReduce
Understanding Hive and HBase
Exploring Pig tools
Building workflows
Using other libraries, such as Impala, Mahout, and Storm
Understanding Spark
Visualizing Hadoop output
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Instructor’s Welcome Note:
– Hi, I’m Lynn Langit, and welcome to Hadoop Fundamentals. Hadoop is a set of technologies that’s used to store and process huge amounts of data. In this course, I’ll focus on using Hadoop to process data, rather than setting up and administering it. We’ll take a look at business scenarios where Hadoop is an appropriate tool. I’ll also cover libraries, such as MapReduce 1.0 and MapReduce 2.0. In addition, we’ll take a look at Hive and Pig, which are often used in Hadoop implementations. Finally, I’ll show you how to tune MapReduce, and I’ll give you a sneak peek at some of the other new Hadoop libraries.
The Hadoop ecosystem is making big data projects possible for businesses and other organizations. So let’s get started.
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