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The library is designed for use popular data platforms including Hadoop, Spark, R, and MATLAB. [4] [8] History. ... Training and Prediction. Regression.
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...
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 ...
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.
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]
Hadoop: Java software framework that supports data intensive distributed applications; HAWQ: advanced enterprise SQL on Hadoop analytic engine; HBase: Apache HBase software is the Hadoop database. Think of it as a distributed, scalable, big data store
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.
Training with Deeplearning4j occurs in a cluster. Neural nets are trained in parallel via iterative reduce, which works on Hadoop-YARN and on Spark. [7] [17] Deeplearning4j also integrates with CUDA kernels to conduct pure GPU operations, and works with distributed GPUs.
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