Map Reduce – Concepts & Programming
This class is being offered in partnership with the Linux Professional Institute.
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.
Hands on lab exercises working with Big Data sets on a Hadoop cluster running on Amazon EC2.
Basic Linux command line skills and server-side Java experience
Developers, Data Analytics professionals, Business Analysts, Managers
July 28, 2013;
August 11, 2013,
August 25, 2013,
4 hours Class; 1:00 – 5:00 p.m.
3200 Coronado Drive,
Santa Clara,CA 95054
Pay using Paypal at firstname.lastname@example.org 24 hours before the class.
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.
(408) 290-9949 – Ext 3