Cloudera Developer Training l 20-23 Aug2015 | Chennai

Cloudera Developer Training l 20-23 Aug2015 | Chennai


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About The Event

Cloudera’s 4-day training program gives Hadoop developers the expertise to harness the full power of the open source technology and bring their organizations' data to life . Xebia is an official training partner of Cloudera, the leader in Apache Hadoop-based software and services.

Programme and Course Overview

Learn how to harness the power of Apache Hadoop by building robust data processing applications that unlock the full potential of your (big)data. Xebia (based in Hilversum, Amsterdam area) is an official training partner of Cloudera, the leader in Apache Hadoop-based software and services. Xebia University delivers a developer-focused Cloudera Certified training course that closely analyses Hadoop’s structure and provides hands-on exercises that teach you how to import data from existing sources; process data with a variety of techniques such as Java Map Reduce programs and Hadoop Streaming jobs; and work with Apache Hive and Pig.


Upon completion of the course, attendees receive a Cloudera Certified Developer for Apache Hadoop (CCDH) practice test. Certification is a great differentiator; it helps establish you as a leader in the field, providing employers and customers with tangible evidence of your skills and expertise.

Learn more about the CCDH Certification Exam here:

Target Group & Prerequisites: 

This course is appropriate for developers who will be writing, maintaining and/or optimizing Hadoop jobs. Participants should have programming experience; knowledge of Java is highly recommended. Understanding of common computer science concepts is a plus. Prior knowledge of Hadoop is not required.

Course Content :

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

  • The internals of MapReduce and HDFS and how to write MapReduce code
  • Best practices for Hadoop development, debugging, and implementation of workflows and common algorithms
  • How to leverage Hive, Pig, Sqoop, Flume, Oozie, and other Hadoop ecosystem projects
  • Creating custom components such as WritableComparables and InputFormats to manage complex data types
  • Writing and executing joins to link data sets in MapReduce
  • Advanced Hadoop API topics required for real-world data analysis




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