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Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Sprache: Englisch
Verlag: O'Reilly Media, Incorporated, 2012
ISBN 10: 1449319335 ISBN 13: 9781449319335
Anbieter: Better World Books: West, Reno, NV, USA
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Paperback. Zustand: Very Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or limited writing/highlighting. We ship orders daily and Customer Service is our top priority!
Paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
EUR 4,09
Anzahl: 3 verfügbar
In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Anbieter: Goodwill of Silicon Valley, SAN JOSE, CA, USA
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Anbieter: HPB-Emerald, Dallas, TX, USA
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Anbieter: Textbooks_Source, Columbia, MO, USA
Erstausgabe
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Sprache: Englisch
Verlag: O'Reilly Media, Incorporated, 2012
ISBN 10: 1449319335 ISBN 13: 9781449319335
Anbieter: TextbookRush, Grandview Heights, OH, USA
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Anbieter: California Books, Miami, FL, USA
Zustand: New.
Anbieter: London Bridge Books, London, Vereinigtes Königreich
EUR 7,40
Anzahl: 1 verfügbar
In den Warenkorbpaperback. Zustand: Good.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. 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.