  In this paper, a technology for massive data storage and computing named
Hadoop is surveyed. Hadoop consists of heterogeneous computing devices like
regular PCs abstracting away the details of parallel processing and developers
can just concentrate on their computational problem. A Hadoop cluster is made
of two parts: HDFs and Mapreduce. Hadoop cluster uses HDFS for data management.
HDFS provides storage for input and output data in MapReduce jobs and is
designed with abilities like high-fault tolerance, high-distribution capacity,
and high throughput. It is also suitable for storing Terabyte data on clusters
and it runs on flexible hardware like commodity devices.
