Low on theory, high on practice, this introduction to Hadoop delivers step-by-step guidance on setting up an instance, and working with each of the components of the Hadoop ecosystem. By the end of this course, you will be capable of implementing an Hadoop instance, storing, processing, and analyzing data with the framework.
If you’re familiar with big data concepts, but new to Hadoop, then this is the course for you. Gain confidence in executing the most useful features of Hadoop by learning from an industry leading expert.
About The Author
Randal Scott King is the Managing Partner of Brilliant Data, a consulting firm specialising in data analytics. In his 16 years of consulting, Scott has amassed an impressive list of clientele from mid-market leaders to Fortune 500 household names. Scott lives just outside Atlanta, GA, with his children.
This video will introduce you to the basic concepts of Hadoop Distributed File System (HDFS) and Yet Another Resource Negotiator (YARN), which are the two core components of Hadoop.
An introduction to the basic concepts of Sqoop and Flume, two tools for the automation of data import into Hadoop.
An introduction to the basic concepts of MapReduce, the computation engine of Hadoop.
An introduction to the basic concepts of Pig, a scripting language for Hadoop.
An introduction to the basic concepts of Hive, Hadoop’s data warehousing solution.
This video will explain how to get data from databases into HDFS.
This video will cover how to import streaming data using the Flume tool.
This video will explore how to build “Word Count” in Eclipse, then save it to a .jar and run it from MapReduce.
Coding the same word counting program, but this time in Pig.
This video will discuss how to use Pig to perform common Extract, Transform, and Load functions on data.
This video will explore how to use predefined code called User Defined Functions (UDFs) in Pig scripts.
This video will cover how to get data into Hive from a database without going to HDFS first.
Using queries in Hive to find information.
A quick summary of what the viewer has learned in the entire course.
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