Map Reduce Programming – Deep Dive


An exhaustive class which covers in-depth of all MapReduce concepts.
Students will learn:

  • Parallel processing, functional programming as the foundation for Hadoop.
  • How map and reduce work.
  • How map and reduce collaborate through shuffle.
  • HDFS fundamentals. Input, output formats.
  • Simple examples of Map Reduce with Java & Map Reduce with Streaming.
  • Anatomy of a Hadoop job: Job Submission & Execution.
  • Compression, serialization.
  • Configuration and tuning.
  • Multiple map reduce jobs and Hadoop workflow.
  • Monitoring and error handling.
  • Deal with complex Map Reduce examples.

 

Lab Work

Hands on lab exercises working with Big Data sets on a Hadoop cluster running on Amazon EC2.

Prerequisites

Basic Linux command line skills and server-side Java experience

Audience

Developers, Data Analytics professionals, Business Analysts, Managers

Recommended Readings

- O’Reilly’s ‘Hadoop’ book by Tom White
- Hadoop tutorial on YDN

Class Date

June 23rd 2013

Class Duration

4 hours Class

Class Location

3200 Coronado Drive,
Santa Clara,CA 95054

Registration

Option 1:
Pay using Paypal at training@thirdeyecss.com 24 hours before the class.

Option 2:
Send us a check payable to “Third Eye CSS” at the mailing Address : 3200 Coronado Dr, Santa Clara, CA 95054.
Check must be received 24 hours before the class start time.

Option 3:

Contact Information:

Training Department
training@thirdeyecss.com
(408) 290-9949 – Ext 3

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