Instant Mapreduce Patterns - Hadoop Essentials How-To PDF Download
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Author: Srinath Perera
Publisher: Packt Publishing Ltd
ISBN: 1782167714
Category : Computers
Languages : en
Pages : 131
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Book Description
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This is a Packt Instant How-to guide, which provides concise and clear recipes for getting started with Hadoop.This book is for big data enthusiasts and would-be Hadoop programmers. It is also meant for Java programmers who either have not worked with Hadoop at all, or who know Hadoop and MapReduce but are not sure how to deepen their understanding.
Author: Srinath Perera
Publisher: Packt Publishing Ltd
ISBN: 1782167714
Category : Computers
Languages : en
Pages : 131
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Book Description
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This is a Packt Instant How-to guide, which provides concise and clear recipes for getting started with Hadoop.This book is for big data enthusiasts and would-be Hadoop programmers. It is also meant for Java programmers who either have not worked with Hadoop at all, or who know Hadoop and MapReduce but are not sure how to deepen their understanding.
Author: Thilina Gunarathne
Publisher: Packt Publishing Ltd
ISBN: 1783285486
Category : Computers
Languages : en
Pages : 322
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Book Description
If you are a Big Data enthusiast and wish to use Hadoop v2 to solve your problems, then this book is for you. This book is for Java programmers with little to moderate knowledge of Hadoop MapReduce. This is also a one-stop reference for developers and system admins who want to quickly get up to speed with using Hadoop v2. It would be helpful to have a basic knowledge of software development using Java and a basic working knowledge of Linux.
Author: David Rojas
Publisher: Packt Publishing Ltd
ISBN: 1785284037
Category : Computers
Languages : en
Pages : 226
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Book Description
Manage, analyze, and visualize data with Microsoft Excel 2013 to transform raw data into ready to use information About This Book Create formulas to help you analyze and explain findings Develop interactive spreadsheets that will impress your audience and give them the ability to slice and dice data A step-by-step guide to learn various ways to model data for businesses with the help of Excel 2013 Who This Book Is For If you want to start using Excel 2013 for data analysis and business modeling and enhance your skills in the data analysis life cycle then this book is for you, whether you're new to Excel or experienced. What You Will Learn Discover what Excel formulas are all about and how to use them in your spreadsheet development Identify bad data and learn cleaning strategies Create interactive spreadsheets that engage and appeal to your audience Leverage Excel's powerful built-in tools to get the median, maximum, and minimum values of your data Build impressive tables and combine datasets using Excel's built-in functionality Learn the powerful scripting language VBA, allowing you to implement your own custom solutions with ease In Detail Excel 2013 is one of the easiest to use data analysis tools you will ever come across. Its simplicity and powerful features has made it the go to tool for all your data needs. Complex operations with Excel, such as creating charts and graphs, visualization, and analyzing data make it a great tool for managers, data scientists, financial data analysts, and those who work closely with data. Learning data analysis and will help you bring your data skills to the next level. This book starts by walking you through creating your own data and bringing data into Excel from various sources. You'll learn the basics of SQL syntax and how to connect it to a Microsoft SQL Server Database using Excel's data connection tools. You will discover how to spot bad data and strategies to clean that data to make it useful to you. Next, you'll learn to create custom columns, identify key metrics, and make decisions based on business rules. You'll create macros using VBA and use Excel 2013's shiny new macros. Finally, at the end of the book, you'll be provided with useful shortcuts and tips, enabling you to do efficient data analysis and business modeling with Excel 2013. Style and approach This is a step-by-step guide to performing data analysis and business modelling with Excel 2013, complete with examples and tips.
Author: Skanda Bhargav
Publisher: Packt Publishing Ltd
ISBN: 1782175024
Category : Computers
Languages : en
Pages : 288
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Book Description
Make life at the office easier for server administrators by helping them build resilient Ubuntu server systems About This Book Tackle the issues you come across in keeping your Ubuntu server up and running Build server machines and troubleshoot cloud computing related issues using Open Stack Discover tips and best practices to be followed for minimum maintenance of Ubuntu Server 3 Who This Book Is For This book is for a vast audience of Linux system administrators who primarily work on Debian-based systems and spend long hours trying fix issues with the enterprise server. Ubuntu is already one of the most popular OSes and this book targets the most common issues that most administrators have to deal with. With the right tools and definite solutions, you will be able to keep your Ubuntu servers in the pink of health. What You Will Learn Deploy packages and their dependencies with repositories Set up your own DNS and network for Ubuntu Server Authenticate and validate users and their access to various systems and services Maintain, monitor, and optimize your server resources and avoid tremendous load Get to know about processes, assigning and changing priorities, and running processes in background Optimize your shell with tools and provide users with an improved shell experience Set up separate environments for various services and run them safely in isolation Understand, build, and deploy OpenStack on your Ubuntu Server In Detail Ubuntu is becoming one of the favorite Linux flavors for many enterprises and is being adopted to a large extent. It supports a wide variety of common network systems and the use of standard Internet services including file serving, e-mail, Web, DNS, and database management. A large scale use and implementation of Ubuntu on servers has given rise to a vast army of Linux administrators who battle it out day in and day out to make sure the systems are in the right frame of operation and pre-empt any untoward incidents that may result in catastrophes for the businesses using it. Despite all these efforts, glitches and bugs occur that affect Ubuntu server's network, memory, application, and hardware and also generate cloud computing related issues using OpenStack. This book will help you end to end. Right from setting up your new Ubuntu Server to learning the best practices to host OpenStack without any hassles. You will be able to control the priority of jobs, restrict or allow access users to certain services, deploy packages, tackle issues related to server effectively, and reduce downtime. Also, you will learn to set up OpenStack, and manage and monitor its services while tuning the machine with best practices. You will also get to know about Virtualization to make services serve users better. Chapter by chapter, you will learn to add new features and functionalities and make your Ubuntu server a full-fledged, production-ready system. Style and approach This book contains topic-by-topic discussion in an easy-to-understand language with loads of examples to help you take care of Ubuntu Server. Plenty of screenshots will guide you through a step-by-step approach.
Author: Rohit Menon
Publisher: Packt Publishing Ltd
ISBN: 1783558970
Category : Computers
Languages : en
Pages : 348
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Book Description
An easy-to-follow Apache Hadoop administrator’s guide filled with practical screenshots and explanations for each step and configuration. This book is great for administrators interested in setting up and managing a large Hadoop cluster. If you are an administrator, or want to be an administrator, and you are ready to build and maintain a production-level cluster running CDH5, then this book is for you.
Author: Donald Miner
Publisher: "O'Reilly Media, Inc."
ISBN: 1449341985
Category : Computers
Languages : en
Pages : 417
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Book Description
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
Author: Jimmy Lin
Publisher: Springer Nature
ISBN: 3031021363
Category : Computers
Languages : en
Pages : 171
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Book Description
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
Author: Douglas Eadline
Publisher: Addison-Wesley Professional
ISBN: 0134049993
Category : Computers
Languages : en
Pages : 767
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Book Description
Get Started Fast with Apache Hadoop® 2, YARN, and Today’s Hadoop Ecosystem With Hadoop 2.x and YARN, Hadoop moves beyond MapReduce to become practical for virtually any type of data processing. Hadoop 2.x and the Data Lake concept represent a radical shift away from conventional approaches to data usage and storage. Hadoop 2.x installations offer unmatched scalability and breakthrough extensibility that supports new and existing Big Data analytics processing methods and models. Hadoop® 2 Quick-Start Guide is the first easy, accessible guide to Apache Hadoop 2.x, YARN, and the modern Hadoop ecosystem. Building on his unsurpassed experience teaching Hadoop and Big Data, author Douglas Eadline covers all the basics you need to know to install and use Hadoop 2 on personal computers or servers, and to navigate the powerful technologies that complement it. Eadline concisely introduces and explains every key Hadoop 2 concept, tool, and service, illustrating each with a simple “beginning-to-end” example and identifying trustworthy, up-to-date resources for learning more. This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, devops specialist, programmer, architect, analyst, or data scientist. Coverage Includes Understanding what Hadoop 2 and YARN do, and how they improve on Hadoop 1 with MapReduce Understanding Hadoop-based Data Lakes versus RDBMS Data Warehouses Installing Hadoop 2 and core services on Linux machines, virtualized sandboxes, or clusters Exploring the Hadoop Distributed File System (HDFS) Understanding the essentials of MapReduce and YARN application programming Simplifying programming and data movement with Apache Pig, Hive, Sqoop, Flume, Oozie, and HBase Observing application progress, controlling jobs, and managing workflows Managing Hadoop efficiently with Apache Ambari–including recipes for HDFS to NFSv3 gateway, HDFS snapshots, and YARN configuration Learning basic Hadoop 2 troubleshooting, and installing Apache Hue and Apache Spark
Author: Chuck Lam
Publisher: Simon and Schuster
ISBN: 1638352100
Category : Computers
Languages : en
Pages : 471
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Book Description
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.
Author: Kevin Schmidt
Publisher: O'Reilly Media
ISBN: 9781449363628
Category : Computers
Languages : en
Pages : 155
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Book Description
Although you don’t need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic MapReduce (EMR), the hosted Hadoop framework in Amazon Web Services (AWS). Authors Kevin Schmidt and Christopher Phillips demonstrate best practices for using EMR and various AWS and Apache technologies by walking you through the construction of a sample MapReduce log analysis application. Using code samples and example configurations, you’ll learn how to assemble the building blocks necessary to solve your biggest data analysis problems. Get an overview of the AWS and Apache software tools used in large-scale data analysis Go through the process of executing a Job Flow with a simple log analyzer Discover useful MapReduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a MapReduce Job Flow Learn the basics for using Amazon EMR to run machine learning algorithms Develop a project cost model for using Amazon EMR and other AWS tools
