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Cascading is a data processing API and processing query planner used for defining, sharing, and executing data-processing workflows on a single computing node or distributed computing cluster.
exceeds the processing capacity of a single computing system.In response, developers may adopt Apache Hadoop as the base computing infrastructure, but discover that developing useful applications on Hadoop is not trivial.Cascading eases the burden on these developers and allows them to rapidly create, refactor, test, and execute complex applications that scale linearly across a cluster of computers.results in one-off data-processing applications sprawling haphazardly onto any available disk space or CPU.Apache Hadoop solves the problem with its Global Namespace file system, which provides a single reliable storage framework.This can be done with the raw Java Cascading API, or with a scripting language such as Scale, Clojure, Groovy, JRuby, or Jython (or by one of the DSL's implemented in these languages).
is a person who writes individual functions or operations (typically in Java) or reusable subassemblies that act on the data that passes through the data processing workflow.
A simple example would be a parser that takes a string and converts it to an Integer.
Operations are equivalent to Java functions in the sense that they take input arguments and return data.
In this scenario, Cascading eases the learning curve for developers as they convert their existing applications for execution on a Hadoop cluster for its reliability and scalability.
In addition, it lets developers create reusable libraries and applications for use by analysts, who use them to extract data from the Hadoop file system.
Since Cascading's creation, a number of Domain Specific Languages (DSL's) have emerged as query languages that wrap the Cascading API's, allowing developers and analysts to create ad-hoc queries for data mining and exploration.