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The open source Apache Hadoop project, which adopts the Map Reduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services.In this article, we present Map Reduce frame-based applications that can be employed in the next-generation sequencing and other biological domains.MPI is a widely used traditional parallel programming model.
Cloud Web services such as the Amazon Elastic Compute Cloud (EC2) and Amazon Elastic Map Reduce are commercially available, whereas the IBM/Google Cloud Computing University Initiative and the United States Department of Energy’s Magellan service are free.
Users generally upload their data by using a Web interface, after which they can perform operations on a remote client webpage.
With the combination of Map Reduce and the HDFS module, Hadoop aims to implement reliable, scalable and distributed computing.
Aside from the Hadoop framework, numerous other popular open source Apache projects are related to Hadoop, including HBase, Hive, Mahout, Pig and Zoo Keeper.