Hadoop and MapReduce are standard, cookie-cutter ways of taking complicated jobs that parallelize the jobs that run on a number of machines and get the results back for your convenience. The power and versatility of the MapReduce programming paradigm and the great design underlying Hadoop have spawned an entire ecosystem of its own. One side effect of this Hadoop ecosystem and popularity is the rise of clustered or distributed computing. But it is a simple fact that configuring a cluster of distributed machines is quite complicated and expensive. Ask yourself how many companies or organizations do you know that run Hadoop in a fully distributed mode with raw Hadoop, without making use of nice company versions such as Cloudera. The answer is probably none. That's because it takes a lot of work to get Hadoop and MapReduce going in fully distributed mode...
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