Understand what Hadoop is and what it is used for Develop and run MapReduce jobs in Python Use MapReduce to analyze different types like social network data, movie data, and more Run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce Get to grips with the other Hadoop-based techs like Hive, Spark and Pig Big Data processing is creating a lot of buzz in the market lately, with organizations having to deal with large amounts of data on a daily basis. Processing such data and extracting actionable insights from it is a major challenge; that’s where Hadoop and MapReduce comes to the rescue. This course will teach you how to use MapReduce for Big Data processing – with lots of practical examples and use-cases. You will start with understanding the Hadoop ecosystem and the basics of MapReduce. You will proceed to see how MapReduce can be used to process different types of data – whether it is analyzing movie ratings or your social network data. You will also learn how to run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce. The course wraps up with an overview of other Hadoop-based technologies such as Hive, Pig, and the in-demand Apache Spark. Understand how MapReduce can be used to process and analyze large data sets Frame your complex data analysis problems as multi-stage MapReduce jobs Over 10 real-world examples to help you learn the concepts of Hadoop and MapReduce for Big Data processing Taming.Big.Data.with.MapReduce.and.Hadoop.Hands.On.part2.rarLearn
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