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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 ...
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with Hadoop Streaming to implement the map and reduce parts of the user's program. [15]
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.
SQLAlchemy, open source, a Data Mapper ORM; SQLObject, open source; Storm, open source (LGPL 2.1) developed at Canonical Ltd. Tryton, open source; web2py, the facilities of an ORM are handled by the DAL in web2py, open source; Odoo – Formerly known as OpenERP, It is an Open Source ERP in which ORM is included.
A Data Mapper is a Data Access Layer that performs bidirectional transfer of data between a persistent data store (often a relational database) and an in-memory data representation (the domain layer). The goal of the pattern is to keep the in-memory representation and the persistent data store independent of each other and the data mapper itself.
Its primary use is in Apache Hadoop, where it can provide both a serialization format for persistent data, and a wire format for communication between Hadoop nodes, and from client programs to the Hadoop services. Avro uses a schema to structure the data that is being encoded.
Maps and electoral vote counts for the 2012 presidential election. Our latest estimate has Obama at 281 electoral votes and Romney at 191.
CERN and other physics experiments have collected big data sets for many decades, usually analyzed via high-throughput computing rather than the map-reduce architectures usually meant by the current "big data" movement. In 2004, Google published a paper on a process called MapReduce that uses a similar architecture. The MapReduce concept ...