Comprehensive Guide To Hive Architecture And Query Language
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Comprehensive Guide To Hive Architecture And Query Language
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-14
Comprehensive Guide To Hive Architecture And Query Language written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-14 with Computers categories.
"Comprehensive Guide to Hive Architecture and Query Language" This expertly crafted volume offers a sweeping exploration of Apache Hive, tracing its evolution from its early origins alongside Hadoop to its current standing as a cornerstone in modern data warehousing. Readers are guided through the historical motivations behind Hive’s design, its unique differentiators compared to other analytical platforms, and its integration within both traditional and cloud-native environments. The book not only contextualizes Hive’s role amongst emerging data processing engines such as Presto, Impala, and Spark SQL, but also presents real-world deployment patterns, use cases, and future-facing trends, establishing a solid foundation for readers seeking to understand Hive’s place in today’s data ecosystem. Delving into the heart of Hive’s technical architecture, the guide provides a profound examination of core components including the Metastore, query compilation and optimization processes, execution engines, and robust fault tolerance mechanisms. Coverage extends into advanced data modeling techniques—partitioning, bucketing, and schema evolution—as well as best practices for storage optimization and metadata governance. Readers will gain practical skills in designing performant data warehouses, leveraging Hive’s strengths in balancing manageability, scalability, and extensibility, while implementing secure, compliant, and multi-tenant environments. A substantial focus is also placed on Hive Query Language (HiveQL), equipping practitioners with in-depth knowledge of syntax, advanced analytical patterns, custom functions, and transactional semantics. The book bridges theory and practice with comprehensive discussions on query optimization, performance engineering, workload management, and sophisticated integration scenarios with BI tools, streaming data, Spark SQL, and federated sources. Concluding with chapters on deployment strategies, operational best practices, and emerging innovations such as serverless Hive and data lakehouse architectures, this guide stands as an indispensable resource for architects, engineers, and data professionals striving for mastery of large-scale analytic data platforms.
Advanced Hadoop Techniques A Comprehensive Guide To Mastery
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-05-13
Advanced Hadoop Techniques A Comprehensive Guide To Mastery written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-13 with Computers categories.
Unlock the full potential of Hadoop with "Advanced Hadoop Techniques: A Comprehensive Guide to Mastery"—your essential resource for navigating the intricate complexities and harnessing the tremendous power of the Hadoop ecosystem. Designed for data engineers, developers, administrators, and data scientists, this book elevates your skills from foundational concepts to the most advanced optimizations necessary for mastery. Delve deep into the core of Hadoop, unraveling its integral components such as HDFS, MapReduce, and YARN, while expanding your knowledge to encompass critical ecosystem projects like Hive, HBase, Sqoop, and Spark. Through meticulous explanations and real-world examples, "Advanced Hadoop Techniques: A Comprehensive Guide to Mastery" equips you with the tools to efficiently deploy, manage, and optimize Hadoop clusters. Learn to fortify your Hadoop deployments by implementing robust security measures to ensure data protection and compliance. Discover the intricacies of performance tuning to significantly enhance your data processing and analytics capabilities. This book empowers you to not only learn Hadoop but to master sophisticated techniques that convert vast data sets into actionable insights. Perfect for aspiring professionals eager to make an impact in the realm of big data and seasoned experts aiming to refine their craft, "Advanced Hadoop Techniques: A Comprehensive Guide to Mastery" serves as an invaluable resource. Embark on your journey into the future of big data with confidence and expertise—your path to Hadoop mastery starts here.
Programming Hive
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Author : Edward Capriolo
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-09-26
Programming Hive written by Edward Capriolo and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-26 with Computers categories.
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
A Brief Guide To Big Data Hadoop
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Author : Ambrish Kumar Sharma
language : en
Publisher: AG PUBLISHING HOUSE (AGPH Books)
Release Date : 2022-10-11
A Brief Guide To Big Data Hadoop written by Ambrish Kumar Sharma and has been published by AG PUBLISHING HOUSE (AGPH Books) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-11 with Study Aids categories.
This book delivers various components that make up the Apache Hadoop ecosystem, as well as some general information about the Big Data platform's underlying architectural principles. Use a wide variety of software, including Apache Spark, Elasticsearch, Tableau, and more, to solve a wide range of problems associated with data processing and analytics. Become an experienced Hadoop Architect with the help of this detailed, how-to manual. If you're a data professional looking to further your career in the Hadoop sector and become a Big Data architect, this book is for you. If you're a project manager or mainframe expert interested in making the transition to the Big Data Hadoop industry, you'll discover valuable information in this book.
Hadoop Practice Guide
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Author : Jisha Mariam Jose
language : en
Publisher: Notion Press
Release Date : 2019-08-19
Hadoop Practice Guide written by Jisha Mariam Jose and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-19 with Juvenile Nonfiction categories.
This book is a complete practical approach for Hadoop lovers. It is mainly aimed at beginners who want to have a hands-on experience with Hadoop and its ecosystem. Its simplicity and step-by-step explanation will help students and other readers in the computer science industry to use this book as a reference manual. The book has been divided into various chapters that cover Hadoop installation, Summary on Hadoop core components, General commands in Hadoop with examples, SQOOP-import & export commands with verification steps, Pig Latin Commands, Analysis using Pig Latin, Pig Script examples, HiveQL Queries and expected outputs and HBase with CRUD operations. In short, this book is a guide for programmers and non-programmers to begin their projects in Hadoop. It is also suitable as a reference manual for students and professionals who are new to the Hadoop Ecosystems.
Concise Guide To Databases
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Author : Konstantinos Domdouzis
language : en
Publisher: Springer Nature
Release Date : 2021-05-20
Concise Guide To Databases written by Konstantinos Domdouzis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-20 with Computers categories.
Modern businesses depend on data for their very survival, creating a need for sophisticated databases and database technologies to help store, organise and transport their valuable data. This updated and expanded, easy-to-read textbook/reference presents a comprehensive introduction to databases, opening with a concise history of databases and of data as an organisational asset. As relational database management systems are no longer the only database solution, the book takes a wider view of database technology, encompassing big data, NoSQL, object and object-relational, and in-memory databases. Presenting both theoretical and practical elements, the new edition also examines the issues of scalability, availability, performance and security encountered when building and running a database in the real world. Topics and features: Presents review and discussion questions at the end of each chapter, in addition to skill-building, hands-on exercises Provides new material on database adaptiveness, integration, and efficiency in relation to data growth Introduces a range of commercial databases and encourages the reader to experiment with these in an associated learning environment Reviews use of a variety of databases in business environments, including numerous examples Discusses areas for further research within this fast-moving domain With its learning-by-doing approach, supported by both theoretical and practical examples, this clearly-structured textbook will be of great value to advanced undergraduate and postgraduate students of computer science, software engineering, and information technology. Practising database professionals and application developers will also find the book an ideal reference that addresses today's business needs.
Hadoop The Definitive Guide
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Author : Tom White
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-05-19
Hadoop The Definitive Guide written by Tom White and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-19 with Computers categories.
With the latest edition of this comprehensive resource, readers will learn how to use Apache Hadoop to build and maintain reliable, scalable, distributed systems. Ideal for programmers and administrators wanting to set up and analyze datasets of any size.
Practical Hive
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Author : Scott Shaw
language : en
Publisher: Apress
Release Date : 2016-08-27
Practical Hive written by Scott Shaw and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-27 with Computers categories.
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.
Practical Hadoop Ecosystem
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Author : Deepak Vohra
language : en
Publisher: Apress
Release Date : 2016-09-30
Practical Hadoop Ecosystem written by Deepak Vohra and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Computers categories.
Learn 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.
Scalable Big Data Architecture
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Author : Bahaaldine Azarmi
language : en
Publisher: Apress
Release Date : 2015-12-31
Scalable Big Data Architecture written by Bahaaldine Azarmi and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-31 with Computers categories.
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQLto serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools tointegrate into that pattern.