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Cascading is a software abstraction layer for Apache Hadoop and Apache Flink. Cascading is used to create and execute complex data processing workflows on a Hadoop cluster using any JVM-based language (Java, JRuby, Clojure, etc.), hiding the underlying complexity of MapReduce jobs. It is open source and available under the Apache License.
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]
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 ...
Apache Pig [1] is a high-level platform for creating programs that run on Apache Hadoop. The language for this platform is called Pig Latin . [ 1 ] Pig can execute its Hadoop jobs in MapReduce , Apache Tez, or Apache Spark . [ 2 ]
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. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data.
MRUnit: Java library that helps developers unit test Apache Hadoop map reduce jobs; MXNet: Deep learning programming framework; ODE: Apache ODE is a WS-BPEL implementation that supports web services orchestration using flexible process definitions.
Cutting and Mike Cafarella, realizing the importance of this paper to extending Lucene into the realm of extremely large search problems, created the open-source Hadoop framework. This framework allows applications based on the MapReduce paradigm to be run on large clusters of commodity hardware.
In the past, many of the implementations use the Apache Hadoop platform, however today it is primarily focused on Apache Spark. [3] [4] Mahout also provides Java/Scala libraries for common math operations (focused on linear algebra and statistics) and primitive Java collections. Mahout is a work in progress; a number of algorithms have been ...