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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 Hive is a data warehouse software project. 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.
Data-intensive computing is intended to address this need. Parallel processing approaches can be generally classified as either compute-intensive , or data-intensive . [ 6 ] [ 7 ] [ 8 ] Compute-intensive is used to describe application programs that are compute-bound.
Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...
An elastic cloud is a cloud computing offering that provides variable service levels based on changing needs. Elasticity is an attribute that can be applied to most cloud services. It states that the capacity and performance of any given cloud service can expand or contract according to a customer's requirements and that this can potentially be ...
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.
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