Programming Hive

Author: Edward Capriolo,Dean Wampler,Jason Rutherglen

Publisher: "O'Reilly Media, Inc."

ISBN: 1449326986

Category: Computers

Page: 350

View: 6006

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Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop’s data warehouse infrastructure. You’ll quickly learn how to use Hive’s SQL dialect—HiveQL—to summarize, query, and analyze large datasets stored in Hadoop’s distributed filesystem. This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem. You’ll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. Use Hive to create, alter, and drop databases, tables, views, functions, and indexes Customize data formats and storage options, from files to external databases Load and extract data from tables—and use queries, grouping, filtering, joining, and other conventional query methods Gain best practices for creating user defined functions (UDFs) Learn Hive patterns you should use and anti-patterns you should avoid Integrate Hive with other data processing programs Use storage handlers for NoSQL databases and other datastores Learn the pros and cons of running Hive on Amazon’s Elastic MapReduce
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Handbook of Research on Big Data Storage and Visualization Techniques

Author: Segall, Richard S.,Cook, Jeffrey S.

Publisher: IGI Global

ISBN: 1522531432

Category: Computers

Page: 917

View: 8077

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The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
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Network Data Analytics

A Hands-On Approach for Application Development

Author: K. G. Srinivasa,Siddesh G. M.,Srinidhi H.

Publisher: Springer

ISBN: 3319778005

Category: Computers

Page: 398

View: 5693

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In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.
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Hadoop: The Definitive Guide

Author: Tom White

Publisher: "O'Reilly Media, Inc."

ISBN: 1449338771

Category: Computers

Page: 688

View: 4424

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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
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Smart Computing and Communication

Third International Conference, SmartCom 2018, Tokyo, Japan, December 10–12, 2018, Proceedings

Author: Meikang Qiu

Publisher: Springer

ISBN: 3030057550

Category: Computers

Page: 462

View: 3557

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This book constitutes the refereed proceedings of the Third International Conference on Smart Computing and Communications, SmartCom 2018, held in Tokyo, Japan, in December 2018. The 45 papers presented in this volume were carefully reviewed and selected from 305 submissions. They focus on topics from smart data to smart communications, as well as smart cloud computing to smart security.
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Hadoop For Dummies

Author: Dirk deRoos

Publisher: John Wiley & Sons

ISBN: 1118652207

Category: Computers

Page: 416

View: 2795

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Let Hadoop For Dummies help harness the power of yourdata and rein in the information overload Big data has become big business, and companies and organizationsof all sizes are struggling to find ways to retrieve valuableinformation from their massive data sets with becoming overwhelmed.Enter Hadoop and this easy-to-understand For Dummiesguide. Hadoop For Dummies helps readers understand thevalue of big data, make a business case for using Hadoop, navigatethe Hadoop ecosystem, and build and manage Hadoop applications andclusters. Explains the origins of Hadoop, its economic benefits, and itsfunctionality and practical applications Helps you find your way around the Hadoop ecosystem, programMapReduce, utilize design patterns, and get your Hadoop cluster upand running quickly and easily Details how to use Hadoop applications for data mining, webanalytics and personalization, large-scale text processing, datascience, and problem-solving Shows you how to improve the value of your Hadoop cluster,maximize your investment in Hadoop, and avoid common pitfalls whenbuilding your Hadoop cluster From programmers challenged with building and maintainingaffordable, scaleable data systems to administrators who must dealwith huge volumes of information effectively and efficiently, thishow-to has something to help you with Hadoop.
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Big Data and Hadoop

Author: VK Jain

Publisher: KHANNA PUBLISHING

ISBN: 938260913X

Category: Education

Page: 600

View: 8113

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This book introduces you to the Big Data processing techniques addressing but not limited to various BI (business intelligence) requirements, such as reporting, batch analytics, online analytical processing (OLAP), data mining and Warehousing, and predictive analytics. The book has been written on IBMs Platform of Hadoop framework. IBM Infosphere BigInsight has the highest amount of tutorial matter available free of cost on Internet which makes it easy to acquire proficiency in this technique. This therefore becomes highly vunerable coaching materials in easy to learn steps. The book optimally provides the courseware as per MCA and M. Tech Level Syllabi of most of the Universities. All components of big Data Platform like Jaql, Hive Pig, Sqoop, Flume , Hadoop Streaming, Oozie: HBase, HDFS, FlumeNG, Whirr, Cloudera, Fuse , Zookeeper and Mahout: Machine learning for Hadoop has been discussed in sufficient Detail with hands on Exercises on each.
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IBM Information Server: Integration and Governance for Emerging Data Warehouse Demands

Author: Chuck Ballard,Manish Bhide,Holger Kache,Bob Kitzberger,Beate Porst,Yeh-Heng Sheng,Harald C. Smith,IBM Redbooks

Publisher: IBM Redbooks

ISBN: 0738438499

Category: Computers

Page: 194

View: 1128

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This IBM® Redbooks® publication is intended for business leaders and IT architects who are responsible for building and extending their data warehouse and Business Intelligence infrastructure. It provides an overview of powerful new capabilities of Information Server in the areas of big data, statistical models, data governance and data quality. The book also provides key technical details that IT professionals can use in solution planning, design, and implementation.
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Planning for Big Data

Author: Edd Wilder-James

Publisher: "O'Reilly Media, Inc."

ISBN: 1449329640

Category: Computers

Page: 83

View: 8442

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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
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Practical Hive

A Guide to Hadoop's Data Warehouse System

Author: Scott Shaw,Andreas François Vermeulen,Ankur Gupta,David Kjerrumgaard

Publisher: Apress

ISBN: 1484202716

Category: Computers

Page: 265

View: 3196

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Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data. What You Will Learn Install and configure Hive for new and existing datasets Perform DDL operations Execute efficient DML operations Use tables, partitions, buckets, and user-defined functions Discover performance tuning tips and Hive best practices Who This Book Is For Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.
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