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{ "item_title" : "Big Data Processing With Hadoop", "item_author" : [" T. Revathi", "K. Muneeswaran", "M. Blessa Binolin Pepsi "], "item_description" : "Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/52/253/790/1522537902_b.jpg", "price_data" : { "retail_price" : "195.00", "online_price" : "195.00", "our_price" : "195.00", "club_price" : "195.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Big Data Processing With Hadoop|T. Revathi

Big Data Processing With Hadoop

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Overview

Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.

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Details

  • ISBN-13: 9781522537908
  • ISBN-10: 1522537902
  • Publisher: Engineering Science Reference
  • Publish Date: November 2018
  • Dimensions: 10 x 7 x 0.63 inches
  • Shipping Weight: 1.47 pounds
  • Page Count: 220

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