Hadoop is a large-scale distributed batch processing infrastructure. While it can be used on a single machine, its true power lies in its ability to scale to hundreds or thousands of computers, each with several processor cores. Hadoop is also designed to efficiently distribute large amounts of work across a set of machines.
How large an amount of work? Orders of magnitude larger than many existing systems work with. Hundreds of gigabytes of data constitute the low end of Hadoop-scale. Actually Hadoop is built to process "web-scale" data on the order of hundreds of gigabytes to terabytes or petabytes. At this scale, it is likely that the input data set will not even fit on a single computer's hard drive, much less in memory. So Hadoop includes a distributed file system which breaks up input data and sends fractions of the original data to several machines in your cluster to hold. This results in the problem being processed in parallel using all of the machines in the cluster and computes output results as efficiently as possible.
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