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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 ...
Airavat: A MapReduce-based system implemented in Java hardened with SELinux-like access control. [34] 2010 Fuzz: Time-constant implementation in Caml Light of a domain-specific language. [35] 2011 GUPT: Implementation of the sample-and-aggregate framework. [36] 2012
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.
Azure Maps was first introduced in public preview mode under the name "Azure Location Based Services" in 2017, primarily as an enterprise solution. [4] The services was intended to add mapping and location-based functionality onto the existing Azure cloud services suite, seen as a critical part of Microsoft's broader Internet-of-Things (IoT) strategy.
M. MADNESS; Many-task computing; Manycore processor; Map (parallel pattern) Maple (software) MapReduce; MasPar; Massively parallel; Massively parallel processor array
The MapReduce architecture allows programmers to use a functional programming style to create a map function that processes a key–value pair associated with the input data to generate a set of intermediate key–value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Since the system ...
Pig Latin abstracts the programming from the Java MapReduce idiom into a notation which makes MapReduce programming high level, similar to that of SQL for relational database management systems. Pig Latin can be extended using user-defined functions (UDFs) which the user can write in Java , Python , JavaScript , Ruby or Groovy [ 3 ] and then ...
Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]
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