Guide to High Performance Distributed Computing: Case by K.G. Srinivasa, Anil Kumar Muppalla

By K.G. Srinivasa, Anil Kumar Muppalla

This well timed text/reference describes the advance and implementation of large-scale allotted processing platforms utilizing open resource instruments and applied sciences. finished in scope, the ebook offers state of the art fabric on development excessive functionality disbursed computing platforms, supplying functional information and most sensible practices in addition to describing theoretical software program frameworks. beneficial properties: describes the basics of creating scalable software program structures for large-scale information processing within the new paradigm of excessive functionality allotted computing; offers an summary of the Hadoop environment, through step by step guideline on its set up, programming and execution; reports the fundamentals of Spark, together with resilient allotted datasets, and examines Hadoop streaming and dealing with Scalding; offers specific case reviews on methods to clustering, facts class and regression research; Explains the method of making a operating recommender procedure utilizing Scalding and Spark.

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Extra resources for Guide to High Performance Distributed Computing: Case Studies with Hadoop, Scalding and Spark

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The Financial trading markets and online banking solutions have also led to the Internet financial revolution [15]. Information society: Ever increasing global information repository the World Wide Web; rise in web search services like Google search and Microsoft Bing; Emerging digitization of information from books(for example, Google Books). Rapidly increasing user generated content on media and information repositories like Youtube, Wikipedia, and Flickr; Social networking services like Facebook, Myspace, Twitter harboring user related content [16].

User generated content on services like Youtube has seen as an expression of user creativity. This creativity has been encouraged by networked technologies. Healthcare: The growth of health related informatics including storing patient data and related privacy issues; Telemedicine to deliver diagnosis and treatment remotely, also supporting advanced telemedicine services like remote surgery; Increasing networking and embedded systems solutions for assisted living, for example, monitoring the health of elderly at their homes and keeping the doctor informed of events automatically[17]; Supporting collaboration between health teams.

This model is popular in other implementations as well. The NFS provides its own communication protocol that allows clients to access the files, thus enabling heterogeneous processes running on different operating systems and hardware to share a common file system. The clients are unaware of the location of the files stored in a distribute file service. Instead, an interface is provided to the file system that is similar to the conventional local file system. For example, Hadoop provides command line 18 1 Introduction interface to copy, delete, and list files in the Hadoop Distributed File System(HDFS).

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