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Users submit map/reduce jobs to the jobtracker, which puts them in a queue of pending jobs and executes them on a first-come/first-served basis. The jobtracker manages the assignment of map and reduce tasks to the tasktrackers. The tasktrackers execute tasks upon instruction from the jobtracker and also handle data motion between the map and reduce phases. Hadoop DFS Hadoop's Distributed File System is designed to reliably store very large files across machines in a large cluster. It is inspired by the Google File System. Hadoop DFS stores each file as a sequence of blocks, all blocks in a file except the last block are the same size. Blocks belonging to a file are replicated for fault tolerance. The block size and replication factor are configurable per file. Files in HDFS are "write once" and have strictly one writer at any time. Like Hadoop Map/Reduce, HDFS follows a master/slave architecture. An HDFS installation consists of a single Namenode, a master server that manages the filesystem namespace and regulates access to files by clients.

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April 23, 2021
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