November 2010
Intermediate to advanced
336 pages
11h 16m
English
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Chapter 4. Writing basic MapReduce programs
This chapter covers
- Patent data as an example data set to process with Hadoop
- Skeleton of a MapReduce program
- Basic MapReduce programs to count statistics
- Hadoop’s Streaming API for writing MapReduce programs using scripting languages
- Combiner to improve performance
The MapReduce programming model is unlike most programming models you may have learned. It’ll take some time and practice to gain familiarity. To help develop your proficiency, we go through many example programs in the next couple chapters. These examples will illustrate various MapReduce programming techniques. By applying MapReduce in multiple ways you’ll start to develop an intuition and a habit of “MapReduce thinking.” The examples ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.