Data Intensive Text Processing With Mapreduce

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Data-Intensive Text Processing with MapReduce

Jimmy Lin,Chris Dyer
Data Intensive Text Processing with MapReduce Book PDF

Author : Jimmy Lin,Chris Dyer
Publisher : Springer Nature
Page : 171 pages
File Size : 40,7 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021367

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Data-Intensive Text Processing with MapReduce by Jimmy Lin,Chris Dyer Pdf

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks

Data-intensive Text Processing with MapReduce

Jimmy Lin,Chris Dyer
Data intensive Text Processing with MapReduce Book PDF

Author : Jimmy Lin,Chris Dyer
Publisher : Morgan & Claypool Publishers
Page : 178 pages
File Size : 43,9 Mb
Release : 2010
Category : Computers
ISBN : 9781608453429

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Data-intensive Text Processing with MapReduce by Jimmy Lin,Chris Dyer Pdf

This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Synthesis Lectures provide concise, original presentations of important research and development topics, published quickly, in digital and print formats. For more information visit www.morganclaypool.com --Book Jacket.

Data-Intensive Text Processing with MapReduce

Jimmy Lin,Chris Dyer
Data Intensive Text Processing with MapReduce Book PDF

Author : Jimmy Lin,Chris Dyer
Publisher : Morgan & Claypool Publishers
Page : 177 pages
File Size : 46,7 Mb
Release : 2010-10-10
Category : Computers
ISBN : 9781608453436

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Data-Intensive Text Processing with MapReduce by Jimmy Lin,Chris Dyer Pdf

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks

Data-intensive Systems

Tomasz Wiktorski
Data intensive Systems Book PDF

Author : Tomasz Wiktorski
Publisher : Springer
Page : 97 pages
File Size : 42,8 Mb
Release : 2019-01-01
Category : Computers
ISBN : 9783030046033

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Data-intensive Systems by Tomasz Wiktorski Pdf

Data-intensive systems are a technological building block supporting Big Data and Data Science applications.This book familiarizes readers with core concepts that they should be aware of before continuing with independent work and the more advanced technical reference literature that dominates the current landscape. The material in the book is structured following a problem-based approach. This means that the content in the chapters is focused on developing solutions to simplified, but still realistic problems using data-intensive technologies and approaches. The reader follows one reference scenario through the whole book, that uses an open Apache dataset. The origins of this volume are in lectures from a master’s course in Data-intensive Systems, given at the University of Stavanger. Some chapters were also a base for guest lectures at Purdue University and Lodz University of Technology.

Designing Data-Intensive Applications

Martin Kleppmann
Designing Data Intensive Applications Book PDF

Author : Martin Kleppmann
Publisher : "O'Reilly Media, Inc."
Page : 658 pages
File Size : 49,9 Mb
Release : 2017-03-16
Category : Computers
ISBN : 9781491903100

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Designing Data-Intensive Applications by Martin Kleppmann Pdf

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Data Intensive Computing Applications for Big Data

M. Mittal,V.E. Balas,D.J. Hemanth
Data Intensive Computing Applications for Big Data Book PDF

Author : M. Mittal,V.E. Balas,D.J. Hemanth
Publisher : IOS Press
Page : 618 pages
File Size : 47,8 Mb
Release : 2018-01-31
Category : Computers
ISBN : 9781614998143

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Data Intensive Computing Applications for Big Data by M. Mittal,V.E. Balas,D.J. Hemanth Pdf

The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Data Algorithms

Mahmoud Parsian
Data Algorithms Book PDF

Author : Mahmoud Parsian
Publisher : "O'Reilly Media, Inc."
Page : 778 pages
File Size : 52,6 Mb
Release : 2015-07-13
Category : COMPUTERS
ISBN : 9781491906156

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Data Algorithms by Mahmoud Parsian Pdf

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. Topics include: Market basket analysis for a large set of transactions Data mining algorithms (K-means, KNN, and Naive Bayes) Using huge genomic data to sequence DNA and RNA Naive Bayes theorem and Markov chains for data and market prediction Recommendation algorithms and pairwise document similarity Linear regression, Cox regression, and Pearson correlation Allelic frequency and mining DNA Social network analysis (recommendation systems, counting triangles, sentiment analysis)

Hadoop: The Definitive Guide

Tom White
Hadoop The Definitive Guide Book PDF

Author : Tom White
Publisher : "O'Reilly Media, Inc."
Page : 687 pages
File Size : 52,8 Mb
Release : 2012-05-10
Category : Computers
ISBN : 9781449338770

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Hadoop: The Definitive Guide by Tom White Pdf

Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Hadoop in Action

Chuck Lam
Hadoop in Action Book PDF

Author : Chuck Lam
Publisher : Simon and Schuster
Page : 471 pages
File Size : 42,9 Mb
Release : 2010-11-30
Category : Computers
ISBN : 9781638352105

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Hadoop in Action by Chuck Lam Pdf

Hadoop in Action teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data analytic programs. The book begins by making the basic idea of Hadoop and MapReduce easier to grasp by applying the default Hadoop installation to a few easy-to-follow tasks, such as analyzing changes in word frequency across a body of documents. The book continues through the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action. Hadoop in Action will explain how to use Hadoop and present design patterns and practices of programming MapReduce. MapReduce is a complex idea both conceptually and in its implementation, and Hadoop users are challenged to learn all the knobs and levers for running Hadoop. This book takes you beyond the mechanics of running Hadoop, teaching you to write meaningful programs in a MapReduce framework. This book assumes the reader will have a basic familiarity with Java, as most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) will help the reader appreciate the more advanced data processing examples. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

MapReduce Design Patterns

Donald Miner,Adam Shook
MapReduce Design Patterns Book PDF

Author : Donald Miner,Adam Shook
Publisher : "O'Reilly Media, Inc."
Page : 250 pages
File Size : 51,7 Mb
Release : 2012-11-21
Category : Computers
ISBN : 9781449341985

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MapReduce Design Patterns by Donald Miner,Adam Shook Pdf

Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you’re using. Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations, and why design patterns are so important. All code examples are written for Hadoop. Summarization patterns: get a top-level view by summarizing and grouping data Filtering patterns: view data subsets such as records generated from one user Data organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easier Join patterns: analyze different datasets together to discover interesting relationships Metapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same job Input and output patterns: customize the way you use Hadoop to load or store data "A clear exposition of MapReduce programs for common data processing patterns—this book is indespensible for anyone using Hadoop." --Tom White, author of Hadoop: The Definitive Guide

Optimizing Hadoop for MapReduce

Khaled Tannir
Optimizing Hadoop for MapReduce Book PDF

Author : Khaled Tannir
Publisher : Packt Publishing Ltd
Page : 120 pages
File Size : 49,8 Mb
Release : 2014-02-21
Category : Computers
ISBN : 9781783285662

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Optimizing Hadoop for MapReduce by Khaled Tannir Pdf

This book is an example-based tutorial that deals with Optimizing Hadoop for MapReduce job performance. If you are a Hadoop administrator, developer, MapReduce user, or beginner, this book is the best choice available if you wish to optimize your clusters and applications. Having prior knowledge of creating MapReduce applications is not necessary, but will help you better understand the concepts and snippets of MapReduce class template code.

Hadoop Operations

Eric Sammer
Hadoop Operations Book PDF

Author : Eric Sammer
Publisher : "O'Reilly Media, Inc."
Page : 298 pages
File Size : 41,6 Mb
Release : 2012-09-26
Category : Computers
ISBN : 9781449327293

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Hadoop Operations by Eric Sammer Pdf

If you’ve been asked to maintain large and complex Hadoop clusters, this book is a must. Demand for operations-specific material has skyrocketed now that Hadoop is becoming the de facto standard for truly large-scale data processing in the data center. Eric Sammer, Principal Solution Architect at Cloudera, shows you the particulars of running Hadoop in production, from planning, installing, and configuring the system to providing ongoing maintenance. Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments. Get a high-level overview of HDFS and MapReduce: why they exist and how they work Plan a Hadoop deployment, from hardware and OS selection to network requirements Learn setup and configuration details with a list of critical properties Manage resources by sharing a cluster across multiple groups Get a runbook of the most common cluster maintenance tasks Monitor Hadoop clusters—and learn troubleshooting with the help of real-world war stories Use basic tools and techniques to handle backup and catastrophic failure

Hadoop Essentials

Shiva Achari
Hadoop Essentials Book PDF

Author : Shiva Achari
Publisher : Packt Publishing Ltd
Page : 194 pages
File Size : 54,5 Mb
Release : 2015-04-29
Category : Computers
ISBN : 9781784390464

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Hadoop Essentials by Shiva Achari Pdf

If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. This book is also meant for Hadoop professionals who want to find solutions to the different challenges they come across in their Hadoop projects.

Big Data Analytics with Hadoop 3

Sridhar Alla
Big Data Analytics with Hadoop 3 Book PDF

Author : Sridhar Alla
Publisher : Packt Publishing Ltd
Page : 471 pages
File Size : 53,6 Mb
Release : 2018-05-31
Category : Computers
ISBN : 9781788624954

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Big Data Analytics with Hadoop 3 by Sridhar Alla Pdf

Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.

Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management

Kosar, Tevfik
Data Intensive Distributed Computing Challenges and Solutions for Large scale Information Management Book PDF

Author : Kosar, Tevfik
Publisher : IGI Global
Page : 353 pages
File Size : 40,5 Mb
Release : 2012-01-31
Category : Computers
ISBN : 9781615209729

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Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management by Kosar, Tevfik Pdf

"This book focuses on the challenges of distributed systems imposed by the data intensive applications, and on the different state-of-the-art solutions proposed to overcome these challenges"--Provided by publisher.