Programming Hive - 11 Angebote vergleichen

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Apache Hive is a data warehouse infrastructure in Apache Hadoop. It can be used for data summarization, analysis and query. Apache Hive was first developed by Facebook and is now being used and developed further by Netflix. Programming Hive provides the reader with a low down on Hive. The book also takes us through the SQL dialect that is used in Hive, HiveQL. One can also quickly learn to analyze large sets of data using this book.Written by experts, Programming Hive first offers a perspective on setting up and using Hive in various environments. The authors then explain the various aspects of Hadoop and MapReduce, which is a programming model applied to large data sets with parallel algorithms applied in cluster. The book then explains the working of Hive within the confines of Hadoop and explains, with real life case studies, how various companies have dealt with obstacles involving petabytes of data using Hive. The example oriented approach to explanation of topics makes learning easier for the readers.In this book, readers will learn how to create and alter databases and to use functions and indexes. The book will also allow readers to use various queries like filtering, grouping and also load and extract data from data tables. The readers will be able to learn integrating Hive with various other data processing programs. Lastly, the book also elaborates on the benefits and disadvantages of running Hive on MapReduce.Programming Hive offers a comprehensive guide to Hive and aims to provide an in-depth learning experience. This first edition of the book was published by Shroff/O'Reilly in 2012 and is available in paperback. , Paperback, संस्करण: First, लेबल: Shroff, Shroff, उत्पाद समूह: Book, प्रकाशित: 2012-11-12, स्टूडियो: Shroff, बिक्री रैंक: 16144.

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Programming Hive, Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoops data warehouse infrastructure. Youll quickly learn how to use Hives SQL dialectHiveQLto summarize, query, and analyze large datasets stored in Hadoops 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. Youll 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 tablesand 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 Amazons Elastic MapReduce, Taschenbuch, 01.10.2012.

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Data, Data Topics, 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. print.

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Data, Data Topics, 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. bundle.

Lieferung aus: Vereinigte Staaten von Amerika, In Stock, plus shipping.
Data, Data Topics, 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. ebook.

Von Händler/Antiquariat, Rheinberg-Buch [53870650], Bergisch Gladbach, Germany.
Neuware - 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 328 pp. Englisch.

Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
Neuware - 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 328 pp. Englisch.

Von Händler/Antiquariat, Rhein-Team Lörrach Ivano Narducci e.K. [57451429], Lörrach, Germany.
Neuware - 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 328 pp. Englisch.

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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 indexesCustomize data formats and storage options, from files to external databasesLoad and extract data from tables-and use queries, grouping, filtering, joining, and other conventional query methodsGain best practices for creating user defined functions (UDFs)Learn Hive patterns you should use and anti-patterns you should avoidIntegrate Hive with other data processing programsUse storage handlers for NoSQL databases and other datastoresLearn the pros and cons of running Hive on Amazon's Elastic MapReduce.

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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 ecos... 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 indexesCustomize data formats and storage options, from files to external databasesLoad and extract data from tables—and use queries, grouping, filtering, joining, and other conventional query methodsGain best practices for creating user defined functions (UDFs)Learn Hive patterns you should use and anti-patterns you should avoidIntegrate Hive with other data processing programsUse storage handlers for NoSQL databases and other datastoresLearn the pros and cons of running Hive on Amazon’s Elastic MapReduce Productinformatie:Taal: Engels;Formaat: Epub zonder kopieerbeveiliging (DRM) ;Bestandsgrootte: 3.12 MB;Kopieerrechten: Het kopiëren van (delen van) de pagina's is niet toegestaan ;ISBN10: 1449326978;ISBN13: 9781449326975; Engels | Ebook | 2012.