Overview:

This online training webinar introduces the MapReduce approach, one of the principal techniques that enable easy processing and analysis of Big Data in a distributed architecture. First announced by Google in 2004, this Big Data technique has its origins in the "map" and "reduce" functions in functional programming. Today, the most widely known use is in the Apache Hadoop project; It is also implemented by many other big data environments and tools.

Description:

The two-hour training event will focus on the following topics: Map & Reduce Functions, Distributed MapReduce Structure, Accessing Big Data in MapReduce, MapReduce Phases, Combine & Partition Functions, and Examples.

Target audience:

Everyone interested in Big Data processing and analysis. 

Prerequisite knowledge:

Basic programming.

Media / Workflow

Online via Zoom.

Skills to be gained

At the end of the webinar, the student will know:

• Basics of MapReduce approach and architecture.
• Methods to access Big Data in MapReduce solutions.
• How to write Map, Reduce, Combine and Partition functions.