Hadoop
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The document provides an overview of Hadoop distributed computing. It discusses how Hadoop uses MapReduce and HDFS to efficiently process large amounts of data across clusters of commodity servers. Key features of Hadoop include scaling to large datasets, handling failures automatically, and providing a simple programming model through MapReduce.
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- 14. Secondary NameNode Client HDFS Architecture NameNode DataNodes 1. filename 2. BlckId, DataNodes o 3.Read data Cluster Membership Cluster Membership NameNode : Maps a file to a file-id and list of MapNodes DataNode : Maps a block-id to a physical location on disk SecondaryNameNode: Periodic merge of Transaction log 2/7/2011
- 15. MapReduce: Programming Model How now Brown cow How does It work now brown 1 cow 1 does 1 How 2 it 1 now 2 work 1 M M M M R R <How,1> <now,1> <brown,1> <cow,1> <How,1> <does,1> <it,1> <work,1> <now,1> <How,1 1> <now,1 1> <brown,1> <cow,1> <does,1> <it,1> <work,1> Input Output Map Reduce MapReduce Framework 2/7/2011
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