September 2017
Beginner to intermediate
412 pages
8h 55m
English
Content preview from Java Data AnalysisBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Summary
This chapter presents some of the ideas and algorithms involved in the analysis of very large datasets. The two main algorithms are Google's PageRank algorithm and the MapReduce framework.
To illustrate how MapReduce works, we have implemented the WordCount example, which counts the frequencies of the words in a collection of text files. The more realistic implementation would be with MongoDB, which is presented in Chapter 10, NoSQL Databases, or in Apache Hadoop, which is briefly described in this chapter.
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.