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Hands-On Big Data Analysis with Hadoop 3

Build effective analytics solutions with Hadoop 3
Course from Udemy
 10 students enrolled
 en
Store data with HDFS and learn in detail about HBase
Share and access data in a SQL-like interface for HDFS
Analyze real-time events using Spark Streaming
Perform complex big data analytics using MapReduce
Analyze data to perform complex processing with Hive and Pig
Explore functional programming using Spark
Learn to import data using Sqoop

This course is your guide to performing real-time data analytics and stream processing with Spark. Use different components and tools such as HDFS, HBase, and Hive to process raw data. Learn how tools such as Hive and Pig aid in this process.

In this course, you will start off by learning data analysis techniques with Hadoop using tools such as Hive. Furthermore, you will learn to apply these techniques in real-world big data applications. Also, you will delve into Spark and its related tools to perform real-time data analytics, streaming, and batch processing on your application.

Finally, you'll learn how to extend your analytics solutions to the cloud.

Please note that this course is based on Hadoop 3.0 but the code used in the course is compatible with Hadoop 3.2.

About the Author

Tomasz Lelek is a software engineer, programming mostly in Java and Scala. He has been working with the Spark and ML APIs for the past 5 years, with production experience in processing petabytes of data.

He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before attempting to solve a problem. Recently he was a speaker at conferences in Poland—Confitura and JDD (Java Developers Day)—and at Krakow Scala User Group. He has also conducted a live coding session at the Geecon Conference.

Hands-On Big Data Analysis with Hadoop 3
$ 94.99
per course
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