By Chuck Lam
Hadoop in Action teaches readers tips to use Hadoop and write MapReduce courses. The meant readers are programmers, architects, and venture managers who've to method quite a lot of info offline. Hadoop in Action will lead the reader from acquiring a replica of Hadoop to atmosphere it up in a cluster and writing facts analytic programs.
The ebook starts through making the elemental proposal of Hadoop and MapReduce more uncomplicated to understand through utilising the default Hadoop set up to some easy-to-follow projects, akin to studying adjustments in be aware frequency throughout a physique of records. The e-book maintains in the course of the simple options of MapReduce purposes constructed utilizing Hadoop, together with an in depth examine framework parts, use of Hadoop for quite a few information research initiatives, and diverse examples of Hadoop in action.
Hadoop in Action will clarify the best way to use Hadoop and current layout styles and practices of programming MapReduce. MapReduce is a posh proposal either conceptually and in its implementation, and Hadoop clients are challenged to profit the entire knobs and levers for working Hadoop. This publication takes you past the mechanics of operating Hadoop, instructing you to jot down significant courses in a MapReduce framework.
This ebook assumes the reader may have a simple familiarity with Java, as so much code examples can be written in Java. Familiarity with uncomplicated statistical ideas (e.g. histogram, correlation) might help the reader savour the extra complicated facts processing examples.
buy of the print publication comes with a proposal of a unfastened PDF, ePub, and Kindle e-book from Manning. additionally on hand is all code from the publication.
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Additional info for Hadoop in action
As you become more familiar with Hadoop you can later modify this file to suit your individual needs (logging directory location, Java class path, and so on). The majority of Hadoop settings are contained in XML configuration files. xml. xml. xml. xml. This refactoring better aligns the configuration settings to the subsystem of Hadoop that they control. In the rest of this chapter we’ll generally point out which of the three files used to adjust a configuration setting. xml. In the following subsections we’ll provide further details about the different operational modes of Hadoop and example configuration files for each.
Hadoop uses key/value pairs as its basic data unit, which is flexible enough to work with the less-structured data types. In Hadoop, data can originate in any form, but it eventually transforms into (key/value) pairs for the processing functions to work on. FUNCTIONAL PROGRAMMING (MAPREDUCE) INSTEAD OF DECLARATIVE QUERIES (SQL) SQL is fundamentally a high-level declarative language. You query data by stating the result you want and let the database engine figure out how to derive it. Under MapReduce you 3 This is in fact a hot area within the Hadoop community, and we’ll cover some of the leading projects in chapter 11.
Under MapReduce you 3 This is in fact a hot area within the Hadoop community, and we’ll cover some of the leading projects in chapter 11. Download from Wow! com> 8 CHAPTER 1 Introducing Hadoop specify the actual steps in processing the data, which is more analogous to an execution plan for a SQL engine. Under SQL you have query statements; under MapReduce you have scripts and codes. MapReduce allows you to process data in a more general fashion than SQL queries. For example, you can build complex statistical models from your data or reformat your image data.