Data Intensive Text Processing With Mapreduce

Download Data Intensive Text Processing With Mapreduce full books in PDF, epub, and Kindle. Read online Data Intensive Text Processing With Mapreduce ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Data-Intensive Text Processing with MapReduce

Author : Jimmy Lin
Publisher : Springer Nature
ISBN 13 : 3031021363
Total Pages : 171 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Data-Intensive Text Processing with MapReduce by : Jimmy Lin

Download or read book Data-Intensive Text Processing with MapReduce written by Jimmy Lin and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Jimmy Lin
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608453421
Total Pages : 178 pages
Book Rating : 4.6/5 (84 download)

DOWNLOAD NOW!

Book Synopsis Data-intensive Text Processing with MapReduce by : Jimmy Lin

Download or read book Data-intensive Text Processing with MapReduce written by Jimmy Lin and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Jimmy Lin
Publisher : Morgan & Claypool Publishers
ISBN 13 : 160845343X
Total Pages : 177 pages
Book Rating : 4.6/5 (84 download)

DOWNLOAD NOW!

Book Synopsis Data-Intensive Text Processing with MapReduce by : Jimmy Lin

Download or read book Data-Intensive Text Processing with MapReduce written by Jimmy Lin and published by Morgan & Claypool Publishers. This book was released on 2010-10-10 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Tomasz Wiktorski
Publisher : Springer
ISBN 13 : 3030046036
Total Pages : 97 pages
Book Rating : 4.0/5 (3 download)

DOWNLOAD NOW!

Book Synopsis Data-intensive Systems by : Tomasz Wiktorski

Download or read book Data-intensive Systems written by Tomasz Wiktorski and published by Springer. This book was released on 2019-01-01 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Martin Kleppmann
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491903104
Total Pages : 658 pages
Book Rating : 4.4/5 (919 download)

DOWNLOAD NOW!

Book Synopsis Designing Data-Intensive Applications by : Martin Kleppmann

Download or read book Designing Data-Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Hadoop: The Definitive Guide

Author : Tom White
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449338771
Total Pages : 687 pages
Book Rating : 4.4/5 (493 download)

DOWNLOAD NOW!

Book Synopsis Hadoop: The Definitive Guide by : Tom White

Download or read book Hadoop: The Definitive Guide written by Tom White and published by "O'Reilly Media, Inc.". This book was released on 2012-05-10 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Chuck Lam
Publisher : Simon and Schuster
ISBN 13 : 1638352100
Total Pages : 471 pages
Book Rating : 4.6/5 (383 download)

DOWNLOAD NOW!

Book Synopsis Hadoop in Action by : Chuck Lam

Download or read book Hadoop in Action written by Chuck Lam and published by Simon and Schuster. This book was released on 2010-11-30 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Data Algorithms

Author : Mahmoud Parsian
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491906154
Total Pages : 778 pages
Book Rating : 4.4/5 (919 download)

DOWNLOAD NOW!

Book Synopsis Data Algorithms by : Mahmoud Parsian

Download or read book Data Algorithms written by Mahmoud Parsian and published by "O'Reilly Media, Inc.". This book was released on 2015-07-13 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)

Data Intensive Computing Applications for Big Data

Author : M. Mittal
Publisher : IOS Press
ISBN 13 : 1614998140
Total Pages : 618 pages
Book Rating : 4.6/5 (149 download)

DOWNLOAD NOW!

Book Synopsis Data Intensive Computing Applications for Big Data by : M. Mittal

Download or read book Data Intensive Computing Applications for Big Data written by M. Mittal and published by IOS Press. This book was released on 2018-01-31 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimizing Hadoop for MapReduce

Author : Khaled Tannir
Publisher : Packt Publishing Ltd
ISBN 13 : 1783285664
Total Pages : 120 pages
Book Rating : 4.7/5 (832 download)

DOWNLOAD NOW!

Book Synopsis Optimizing Hadoop for MapReduce by : Khaled Tannir

Download or read book Optimizing Hadoop for MapReduce written by Khaled Tannir and published by Packt Publishing Ltd. This book was released on 2014-02-21 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

MapReduce Design Patterns

Author : Donald Miner
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449341985
Total Pages : 250 pages
Book Rating : 4.4/5 (493 download)

DOWNLOAD NOW!

Book Synopsis MapReduce Design Patterns by : Donald Miner

Download or read book MapReduce Design Patterns written by Donald Miner and published by "O'Reilly Media, Inc.". This book was released on 2012-11-21 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Hadoop Operations

Author : Eric Sammer
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 144932729X
Total Pages : 298 pages
Book Rating : 4.4/5 (493 download)

DOWNLOAD NOW!

Book Synopsis Hadoop Operations by : Eric Sammer

Download or read book Hadoop Operations written by Eric Sammer and published by "O'Reilly Media, Inc.". This book was released on 2012-09-26 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Big Data Analytics with Hadoop 3

Author : Sridhar Alla
Publisher : Packt Publishing Ltd
ISBN 13 : 1788624955
Total Pages : 471 pages
Book Rating : 4.7/5 (886 download)

DOWNLOAD NOW!

Book Synopsis Big Data Analytics with Hadoop 3 by : Sridhar Alla

Download or read book Big Data Analytics with Hadoop 3 written by Sridhar Alla and published by Packt Publishing Ltd. This book was released on 2018-05-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Cloud Computing

Author : Frederic Magoules
Publisher : CRC Press
ISBN 13 : 1466507837
Total Pages : 231 pages
Book Rating : 4.4/5 (665 download)

DOWNLOAD NOW!

Book Synopsis Cloud Computing by : Frederic Magoules

Download or read book Cloud Computing written by Frederic Magoules and published by CRC Press. This book was released on 2016-04-19 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical techniques and describes completely new methods and innovative algorithms. The

Hadoop Essentials

Author : Shiva Achari
Publisher : Packt Publishing Ltd
ISBN 13 : 1784390461
Total Pages : 194 pages
Book Rating : 4.7/5 (843 download)

DOWNLOAD NOW!

Book Synopsis Hadoop Essentials by : Shiva Achari

Download or read book Hadoop Essentials written by Shiva Achari and published by Packt Publishing Ltd. This book was released on 2015-04-29 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Doing Data Science

Author : Cathy O'Neil
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 144936389X
Total Pages : 408 pages
Book Rating : 4.4/5 (493 download)

DOWNLOAD NOW!

Book Synopsis Doing Data Science by : Cathy O'Neil

Download or read book Doing Data Science written by Cathy O'Neil and published by "O'Reilly Media, Inc.". This book was released on 2013-10-09 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Big Data with Hadoop MapReduce

Author : Rathinaraja Jeyaraj
Publisher : CRC Press
ISBN 13 : 1000439089
Total Pages : 269 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!

Book Synopsis Big Data with Hadoop MapReduce by : Rathinaraja Jeyaraj

Download or read book Big Data with Hadoop MapReduce written by Rathinaraja Jeyaraj and published by CRC Press. This book was released on 2020-05-01 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all the necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc. Ultimately, readers will be able to: • understand what big data is and the factors that are involved • understand the inner workings of MapReduce, which is essential for certification exams • learn the features and weaknesses of MapReduce • set up Hadoop clusters with 100s of physical/virtual machines • create a virtual machine in AWS • write MapReduce with Eclipse in a simple way • understand other big data processing tools and their applications