There has never been a MapReduce Guide like this.

It contains 134 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about MapReduce.

A quick look inside of some of the subjects covered: Hadoop - History, Apache Hadoop, MapReduce - Logical view, Facebook, Inc. - Technical aspects, Computer clusters - Task scheduling, Google App Engine Experimental, CouchDB - Bibliography, Snappy (software), Doug Cutting - Use of MapReduce paradigm, Apache Hadoop Commercially supported Hadoop-related products, Data-intensive computing - Hadoop, Index (search engine) - Challenges in parallelism, Netezza - Products, Sawzall (programming language) - Motivation, Data-intensive computing - System architectures, Amazon DynamoDB - Overview, Amazon Elastic Compute Cloud - Persistent storage, Apache Hive - HiveQL, Hadoop - Other applications, Apache Gora, Predictive Analysis - Technology and big data influences, Pig (programming language), MapReduce - Examples, Distributed file system for cloud - Supporting techniques, MapReduce - Restricted programming framework, MapReduce - Overview, Cassandra (database) - History, Teradata - Teradata and Big Data, Teradata - Acquisitions, Aster Data Systems - Products, Hadoop - Commercially supported Hadoop-related products, Hadoop - Architecture, Computer cluster - Task scheduling, Apache Hadoop Papers, Hadoop - Other file systems, Couchbase Server - Product history, BigTable - History, MongoDB - Main features, HDFS, Amazon AWS - Compute, Apache Cassandra - Main features, and much more..