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Apache Hadoop (/ h ə ˈ d uː p /) is a collection of open-source software utilities for reliable, scalable, distributed computing.It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
The HDFS is normally installed on a cluster of computers. The design concept of Hadoop is informed by Google's, with Google File System, Google MapReduce and Bigtable, being implemented by Hadoop Distributed File System (HDFS), Hadoop MapReduce, and Hadoop Base (HBase) respectively. [26]
The MapReduce concept provides a parallel processing model, and an associated implementation was released to process huge amounts of data. With MapReduce, queries are split and distributed across parallel nodes and processed in parallel (the "map" step). The results are then gathered and delivered (the "reduce" step).
Many companies use cloud storage services such as Google Cloud Storage and Amazon S3 or a distributed file system such as Apache Hadoop distributed file system (HDFS). [7] There is a gradual academic interest in the concept of data lakes.
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A distributed database is a database in which data is stored across different physical locations. [1] It may be stored in multiple computers located in the same physical location (e.g. a data centre); or maybe dispersed over a network of interconnected computers.
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