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Author: Shiva Achari
Publisher: Packt Publishing Ltd
Published: 2015-04-29
Total Pages: 194
ISBN-13: 1784390461
DOWNLOAD EBOOKIf 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.
Author: Srinath Perera
Publisher: Packt Publishing Ltd
Published: 2013-05-22
Total Pages: 131
ISBN-13: 1782167714
DOWNLOAD EBOOKFilled 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: Dayong Du
Publisher: Packt Publishing Ltd
Published: 2018-06-30
Total Pages: 203
ISBN-13: 1789136512
DOWNLOAD EBOOKThis book takes you on a fantastic journey to discover the attributes of big data using Apache Hive. Key Features Grasp the skills needed to write efficient Hive queries to analyze the Big Data Discover how Hive can coexist and work with other tools within the Hadoop ecosystem Uses practical, example-oriented scenarios to cover all the newly released features of Apache Hive 2.3.3 Book Description In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey. By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems What you will learn Create and set up the Hive environment Discover how to use Hive's definition language to describe data Discover interesting data by joining and filtering datasets in Hive Transform data by using Hive sorting, ordering, and functions Aggregate and sample data in different ways Boost Hive query performance and enhance data security in Hive Customize Hive to your needs by using user-defined functions and integrate it with other tools Who this book is for If you are a data analyst, developer, or simply someone who wants to quickly get started with Hive to explore and analyze Big Data in Hadoop, this is the book for you. Since Hive is an SQL-like language, some previous experience with SQL will be useful to get the most out of this book.
Author: Chuck Lam
Publisher: Simon and Schuster
Published: 2010-11-30
Total Pages: 471
ISBN-13: 1638352100
DOWNLOAD EBOOKHadoop 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: Douglas Eadline
Publisher: Addison-Wesley Professional
Published: 2015-10-28
Total Pages: 767
ISBN-13: 0134049993
DOWNLOAD EBOOKGet 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: Sridhar Alla
Publisher: Packt Publishing Ltd
Published: 2018-05-31
Total Pages: 471
ISBN-13: 1788624955
DOWNLOAD EBOOKExplore 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.
Author: Arun C. Murthy
Publisher: Pearson Education
Published: 2014
Total Pages: 336
ISBN-13: 0321934504
DOWNLOAD EBOOK"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 HadoopTM YARN, two Hadoop technical leaders show you how to develop new applications and adapt existing code to fully leverage these revolutionary advances." -- From the Amazon
Author: Tom White
Publisher: "O'Reilly Media, Inc."
Published: 2012-05-10
Total Pages: 687
ISBN-13: 1449338771
DOWNLOAD EBOOKReady 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
Author: Deepak Vohra
Publisher: Apress
Published: 2016-09-30
Total Pages: 429
ISBN-13: 1484221990
DOWNLOAD EBOOKLearn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.
Author: Amol Fasale
Publisher: Packt Publishing Ltd
Published: 2015-02-24
Total Pages: 176
ISBN-13: 1784397725
DOWNLOAD EBOOKIf you have a working knowledge of Hadoop 1.x but want to start afresh with YARN, this book is ideal for you. You will be able to install and administer a YARN cluster and also discover the configuration settings to fine-tune your cluster both in terms of performance and scalability. This book will help you develop, deploy, and run multiple applications/frameworks on the same shared YARN cluster.
