This book is useful for Hadoop administrators who need to learn how to monitor and diagnose their clusters. Also, the book will prove useful for new users of the technology, as the language used is simple and easy to grasp.
You’ve heard the hype about Hadoop: it runs petabyte–scale data mining tasks insanely fast, it runs gigantic tasks on clouds for absurdly cheap, it’s been heavily committed to by tech giants like IBM, Yahoo!, and the Apache Project, and it’s completely open-source (thus free). But what exactly is it, and more importantly, how do you even get a Hadoop cluster up and running? From Apress, the name you’ve come to trust for hands–on technical knowledge, Pro Hadoop brings you up to speed on Hadoop. You learn the ins and outs of MapReduce; how to structure a cluster, design, and implement the Hadoop file system; and how to build your first cloud–computing tasks using Hadoop. Learn how to let Hadoop take care of distributing and parallelizing your software—you just focus on the code, Hadoop takes care of the rest. Best of all, you’ll learn from a tech professional who’s been in the Hadoop scene since day one. Written from the perspective of a principal engineer with down–in–the–trenches knowledge of what to do wrong with Hadoop, you learn how to avoid the common, expensive first errors that everyone makes with creating their own Hadoop system or inheriting someone else’s. Skip the novice stage and the expensive, hard–to–fix mistakes...go straight to seasoned pro on the hottest cloud–computing framework with Pro Hadoop. Your productivity will blow your managers away. What you’ll learn Set up a stand–alone Hadoop cluster the smart way, laid out simply and step by step so you can get up and running quickly to build your next data center, collaborative, data–intensive Internet services application, Software as a Service (SaaS), and more. Optimize your Hadoop production tasks like an experienced pro. Work with time–proven, bulletproof standard patterns that have been tested and debugged in high–volume production. Understand just enough theoretical knowledge to know why something works in Hadoop, without getting bogged down in abstruse walls of theory. Get detailed explanations of not only how to do something with Hadoop, but also why, from a front–line coder with years in the Hadoop game. Turn someone else’s expensive cluster–wide “wrong” into an orderly, productive "right" with professional–level debugging and testing. Who this book is for IT professionals interested in investigating Hadoop and implementing it in their organizations, and existing Hadoop users who want to deepen their professional toolkits. Table of Contents Getting Started with Hadoop Core The Basics of a MapReduce Job The Basics of Multimachine Clusters HDFS Details for Multimachine Clusters MapReduce Details for Multimachine Clusters Tuning Your MapReduce Jobs Unit Testing and Debugging Advanced and Alternate MapReduce Techniques Solving Problems with Hadoop Projects Based On Hadoop and Future Directions
Until recently, Hadoop deployments existed on hardware owned and run by organizations. Now, of course, you can acquire the computing resources and network connectivity to run Hadoop clusters in the cloud. But there’s a lot more to deploying Hadoop to the public cloud than simply renting machines. This hands-on guide shows developers and systems administrators familiar with Hadoop how to install, use, and manage cloud-born clusters efficiently. You’ll learn how to architect clusters that work with cloud-provider features—not just to avoid pitfalls, but also to take full advantage of these services. You’ll also compare the Amazon, Google, and Microsoft clouds, and learn how to set up clusters in each of them. Learn how Hadoop clusters run in the cloud, the problems they can help you solve, and their potential drawbacks Examine the common concepts of cloud providers, including compute capabilities, networking and security, and storage Build a functional Hadoop cluster on cloud infrastructure, and learn what the major providers require Explore use cases for high availability, relational data with Hive, and complex analytics with Spark Get patterns and practices for running cloud clusters, from designing for price and security to dealing with maintenance
For system administrators tasked with the job of maintaining large and complex Hadoop clusters, this book explains the particulars of Hadoop operations, from planning, installing, and configuring the system to providing ongoing maintenance.
A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key Features Get to grips with the newly introduced features and capabilities of Hadoop 3 Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem Sharpen your Hadoop skills with real-world case studies and code Book Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learn Gain an in-depth understanding of distributed computing using Hadoop 3 Develop enterprise-grade applications using Apache Spark, Flink, and more Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance Explore batch data processing patterns and how to model data in Hadoop Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform Understand security aspects of Hadoop, including authorization and authentication Who this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.
Die escape GmbH betreibt ein MySQL basiertes Dataware-House in das Daten aus verschiedenen Webpräsenzen fließen, um dort ausgewertet zu werden. Nach Jahren des erfolgreichen Betriebs nimmt mit der ständig steigenden Menge an gespeicherten Daten die Leistung des Systems allerdings ab. Die Laufzeiten für Auswertungen steigen und die Agilität sinkt. Kleine Optimierungen und Veränderungen des Systems können das Unbrauchbarwerden hinauszögern, als aber aus Gründen der Leistung auf einen Teil der Abfragen verzichtet werden muss, wird schließlich klar, dass nur eine grundlegende Veränderung des Systems den langfristigen Betrieb sicherstellen kann. Aus diesem Grund wurde nach Technologien gesucht, deren Fähigkeiten die Leistung des bestehenden Dataware-Houses verbessern können. Dies führte zu Hadoop.
If you are a Hadoop programmer who wants to learn about Flume to be able to move datasets into Hadoop in a timely and replicable manner, then this book is ideal for you. No prior knowledge about Apache Flume is necessary, but a basic knowledge of Hadoop and the Hadoop File System (HDFS) is assumed.
Solve specific problems using individual self-contained code recipes, or work through the book to develop your capabilities. This book is packed with easy-to-follow code and commands used for illustration, which makes your learning curve easy and quick.If you are a Hadoop cluster system administrator with Unix/Linux system management experience and you are looking to get a good grounding in how to set up and manage a Hadoop cluster, then this book is for you. It's assumed that you will have some experience in Unix/Linux command line already, as well as being familiar with network communication basics.
Author: Boris Lublinsky
Publisher: John Wiley & Sons
Release Date: 2013-09-12
The go-to guidebook for deploying Big Data solutions withHadoop Today's enterprise architects need to understand how the Hadoopframeworks and APIs fit together, and how they can be integrated todeliver real-world solutions. This book is a practical, detailedguide to building and implementing those solutions, with code-levelinstruction in the popular Wrox tradition. It covers storing datawith HDFS and Hbase, processing data with MapReduce, and automatingdata processing with Oozie. Hadoop security, running Hadoop withAmazon Web Services, best practices, and automating Hadoopprocesses in real time are also covered in depth. With in-depth code examples in Java and XML and the latest onrecent additions to the Hadoop ecosystem, this complete resourcealso covers the use of APIs, exposing their inner workings andallowing architects and developers to better leverage and customizethem. The ultimate guide for developers, designers, and architectswho need to build and deploy Hadoop applications Covers storing and processing data with various technologies,automating data processing, Hadoop security, and deliveringreal-time solutions Includes detailed, real-world examples and code-levelguidelines Explains when, why, and how to use these tools effectively Written by a team of Hadoop experts in theprogrammer-to-programmer Wrox style Professional Hadoop Solutions is the reference enterprisearchitects and developers need to maximize the power of Hadoop.
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. You are expected to be familiar with the Unix/Linux command-line interface and have some experience with the Java programming language. Familiarity with Hadoop would be a plus.
This book is a step-by-step tutorial filled with practical examples which will focus mainly on the key security tools and implementation techniques of Hadoop security.This book is great for Hadoop practitioners (solution architects, Hadoop administrators, developers, and Hadoop project managers) who are looking to get a good grounding in what Kerberos is all about and who wish to learn how to implement end-to-end Hadoop security within an enterprise setup. It’s assumed that you will have some basic understanding of Hadoop as well as be familiar with some basic security concepts.
“This book is a critically needed resource for the newly released Apache Hadoop 2.0, highlighting YARN as the significant breakthrough that broadens Hadoop beyond the MapReduce paradigm.” —From the Foreword by Raymie Stata, CEO of Altiscale The Insider’s Guide to Building Distributed, Big Data Applications with Apache Hadoop™ YARN Apache Hadoop is helping drive the Big Data revolution. Now, its data processing has been completely overhauled: Apache Hadoop YARN provides resource management at data center scale and easier ways to create distributed applications that process petabytes of data. And now in Apache Hadoop™ YARN, two Hadoop technical leaders show you how to develop new applications and adapt existing code to fully leverage these revolutionary advances. YARN project founder Arun Murthy and project lead Vinod Kumar Vavilapalli demonstrate how YARN increases scalability and cluster utilization, enables new programming models and services, and opens new options beyond Java and batch processing. They walk you through the entire YARN project lifecycle, from installation through deployment. You’ll find many examples drawn from the authors’ cutting-edge experience—first as Hadoop’s earliest developers and implementers at Yahoo! and now as Hortonworks developers moving the platform forward and helping customers succeed with it. Coverage includes YARN’s goals, design, architecture, and components—how it expands the Apache Hadoop ecosystem Exploring YARN on a single node Administering YARN clusters and Capacity Scheduler Running existing MapReduce applications Developing a large-scale clustered YARN application Discovering new open source frameworks that run under YARN
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: Adam Jorgensen
Publisher: John Wiley & Sons
Release Date: 2014-02-24
Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools Explores both on-premises and cloud-based solutions Shows how to store, manage, analyze, and share Big Data through the enterprise Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more Helps you build and execute a Big Data plan Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.
In an age where everything is measurable, understanding big data is an essential. From creating new data-driven products through to increasing operational efficiency, big data has the potential to make your organization both more competitive and more innovative. As this emerging field transitions from the bleeding edge to enterprise infrastructure, it's vital to understand not only the technologies involved, but the organizational and cultural demands of being data-driven. Written by O'Reilly Radar's experts on big data, this anthology describes: The broad industry changes heralded by the big data era What big data is, what it means to your business, and how to start solving data problems The software that makes up the Hadoop big data stack, and the major enterprise vendors' Hadoop solutions The landscape of NoSQL databases and their relative merits How visualization plays an important part in data work