By Alex Holmes
Hadoop in perform, moment version offers over a hundred confirmed, immediately worthwhile innovations that can assist you triumph over great information, utilizing Hadoop. This revised re-creation covers alterations and new gains within the Hadoop center structure, together with MapReduce 2. fresh chapters conceal YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. you will additionally get new and up-to-date ideas for Flume, Sqoop, and Mahout, all of that have obvious significant new models lately. in brief, this can be the main useful, updated assurance of Hadoop on hand at any place.
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Additional info for Hadoop in Practice, 2nd Edition
There are numerous other projects that Cloudera has been working on: highlights include Flume, a log collection and distribution system; Sqoop, for moving relational data in and out of Hadoop; and Cloudera Search, which offers near-real-time search indexing. HORTONWORKS Hortonworks is also made up of a large number of Hadoop committers, and it offers the same advantages as Cloudera in terms of the ability to quickly address problems and feature requests in core Hadoop and its ecosystem projects.
You could use an intermediary datastore, such as a database, but that would be inefficient. A better approach would be to tokenize each line and produce an intermediary file containing a word per line. Each of these intermediary files could then be sorted. The final step would be to open all the sorted intermediary files and call a function for each unique word. This is what MapReduce does, albeit in a distributed fashion. 10 walks you through an example of a simple inverted index in MapReduce.
Public static class Reduce extends Reducer