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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]
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 ...
Avro is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format.
Groovy: an object-oriented, dynamic programming language for the Java platform; Guacamole: HTML5 web application for accessing remote desktops [7] Gump: integration, dependencies, and versioning management; Hadoop: Java software framework that supports data intensive distributed applications; HAWQ: advanced enterprise SQL on Hadoop analytic engine
Hive facilitates the integration of SQL-based querying languages with Hadoop, which is commonly used in data warehousing applications. [5] While initially developed by Facebook , Apache Hive is used and developed by other companies such as Netflix and the Financial Industry Regulatory Authority (FINRA).
Jaql (pronounced "jackal") is a functional data processing and query language most commonly used for JSON query processing on big data. It started as an open source project at Google [1] but the latest release was on 2010-07-12. IBM [2] took it over as primary data processing language for their Hadoop software package BigInsights.
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.