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  2. Cascading (software) - Wikipedia

    en.wikipedia.org/wiki/Cascading_(software)

    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.

  3. Apache Beam - Wikipedia

    en.wikipedia.org/wiki/Apache_Beam

    Apache Beam is an open source unified programming model to define and execute data processing pipelines, including ETL, batch and stream (continuous) processing. [2] Beam Pipelines are defined using one of the provided SDKs and executed in one of the Beam’s supported runners (distributed processing back-ends) including Apache Flink, Apache Samza, Apache Spark, and Google Cloud Dataflow.

  4. Apache Hadoop - Wikipedia

    en.wikipedia.org/wiki/Apache_Hadoop

    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]

  5. Apache Pig - Wikipedia

    en.wikipedia.org/wiki/Apache_Pig

    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 ...

  6. Apache Flink - Wikipedia

    en.wikipedia.org/wiki/Apache_Flink

    Apache Flink is an open-source, unified stream-processing and batch-processing framework developed by the Apache Software Foundation. The core of Apache Flink is a distributed streaming data-flow engine written in Java and Scala. [3] [4] Flink executes arbitrary dataflow programs in a data-parallel and pipelined (hence task parallel) manner. [5]

  7. Apache Avro - Wikipedia

    en.wikipedia.org/wiki/Apache_Avro

    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.

  8. Jetty (web server) - Wikipedia

    en.wikipedia.org/wiki/Jetty_(web_server)

    Eclipse Jetty is a Java web server and Java Servlet container. While web servers are usually associated with serving documents to people, Jetty is now often used for machine to machine communications, usually within larger software frameworks. Jetty is developed as a free and open source project as part of the Eclipse Foundation.

  9. Apache Impala - Wikipedia

    en.wikipedia.org/wiki/Apache_Impala

    Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software. Impala is promoted for analysts and data scientists to perform analytics on data stored in Hadoop via SQL or business intelligence tools. The result ...