Overview:Algorithmic Aspects of Parallel Data Processing - Foundations and Trends in Databases - The last decade has seen a huge and growing interest in processing large data sets on large distributed clusters. This trend began with the MapReduce framework, and has been widely adopted by several other systems, including PigLatin, Hive, Scope, Dremmel, Spark and Myria to name a few. While the applications of such systems are diverse (for example, machine learning, data analytics), most involve relatively standard data processing tasks like identifying relevant data, cleaning, filtering, joining, grouping, transforming, extracting features, and evaluating results. This has generated great interest in the study of algorithms for data processing on large distributed clusters. Algorithmic Aspects of Parallel Data Processing discusses recent algorithmic developments for distributed data processing. It uses a theoretical model of parallel processing called the Massively Parallel Computation (MPC) model, which is a simplification of the BSP model where the only cost is given by the amount of communication and the number of communication rounds. The survey studies several algorithms for multi-join queries, sorting, and matrix multiplication. It discusses their relationships and common techniques applied across the different data processing tasks.
This book is on page /ef28172a407799e584bbe1bbae7aeb68/book/1603728799-9781680834062. It was written by the following authors: Paraschos Koutris, Dan Suciu, Semih Salihoglu. Book Algorithmic Aspects of Parallel Data Processing - Foundations and Trends in Databases, which can be read online, published by the company: now publishers Inc. Other books on similar topics can be found in sections: Computing, Internet. The book was published on 2018-02-01. It has 144 pages and is published in Paperback format and weight 213 g. File for download Algorithmic Aspects of Parallel Data Processing - Foundations and Trends in Databases has PDF format and is called algorithmic-aspects-of-parallel-data-processing-foundations-and-trends-in-databases.pdf. Other books you can download below. Our objectif-paleo.fr site is not responsible for the content of PDF files.
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