ISBN: 9781491923948 - big data for chimps: a guide to massive-scale data processing in practice (25 resultados)

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  • Idioma: Inglés

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    Condición: Very Good. 1st Edition. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. …

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  • Idioma: Inglés

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  • Idioma: Inglés

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  • Idioma: Inglés

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    Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA

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    Paperback. Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data. Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster Dive into map/reduce mechanics and build your first map/reduce job in Python Understand how to run chains of map/reduce jobs in the form of Pig scripts Use a real-world dataset-baseball performance statistics-throughout the book Work with examples of several analytic patterns, and learn when and where you might use them.…

  • Idioma: Inglés

    Editorial: O'Reilly Media, US, 2015

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    Paperback. Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data. Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster Dive into map/reduce mechanics and build your first map/reduce job in Python Understand how to run chains of map/reduce jobs in the form of Pig scripts Use a real-world dataset-baseball performance statistics-throughout the book Work with examples of several analytic patterns, and learn when and where you might use them.…

  • Idioma: Inglés

    Editorial: O'Reilly Media 10/22/2015, 2015

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    Paperback or Softback. Condición: New. Big Data for Chimps: A Guide to Massive-Scale Data Processing in Practice. Book.

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    Editorial: O'Reilly Media 2015-10-23, 2015

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    Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 3-4 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Idioma: Inglés

    Editorial: O'Reilly Media, Sebastopol, 2015

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    Paperback. Condición: new. Paperback. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data. Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster Dive into map/reduce mechanics and build your first map/reduce job in Python Understand how to run chains of map/reduce jobs in the form of Pig scripts Use a real-world dataset-baseball performance statistics-throughout the book Work with examples of several analytic patterns, and learn when and where you might use them Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: O'Reilly Media, Inc, USA, 2015

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  • Idioma: Inglés

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    Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. Num Pages: 220 pages. BIC Classification: UNF. Category: (XV) Technical / Manuals. Dimension: 180 x 233 x 15. Weight in Grams: 392. . 2015. 1st Edition. Paperback. . . . . …

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    Condición: New. In English.

  • Idioma: Inglés

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    Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. Num Pages: 220 pages. BIC Classification: UNF. Category: (XV) Technical / Manuals. Dimension: 180 x 233 x 15. Weight in Grams: 392. . 2015. 1st Edition. Paperback. . . . . Books ship from the US and Ireland. …

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    Taschenbuch. Condición: Neu. Neuware - Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems.Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data.- Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster- Dive into map/reduce mechanics and build your first map/reduce job in Python- Understand how to run chains of map/reduce jobs in the form of Pig scripts- Use a real-world datasetbaseball performance statisticsthroughout the book- Work with examples of several analytic patterns, and learn when and where you might use them.…

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    Kartoniert / Broschiert. Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn t have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools t.

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    Editorial: O'Reilly Media, US, 2015

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    Paperback. Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data. Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster Dive into map/reduce mechanics and build your first map/reduce job in Python Understand how to run chains of map/reduce jobs in the form of Pig scripts Use a real-world dataset-baseball performance statistics-throughout the book Work with examples of several analytic patterns, and learn when and where you might use them.…

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    Editorial: O'Reilly Media, Sebastopol, 2015

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    Paperback. Condición: new. Paperback. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data. Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster Dive into map/reduce mechanics and build your first map/reduce job in Python Understand how to run chains of map/reduce jobs in the form of Pig scripts Use a real-world dataset-baseball performance statistics-throughout the book Work with examples of several analytic patterns, and learn when and where you might use them Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Idioma: Inglés

    Editorial: O'Reilly Media, US, 2015

    1491923946 / 9781491923948

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    Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK

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    Paperback. Condición: New. Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data. Learn the necessary mechanics of working with Hadoop, including how data and computation move around the cluster Dive into map/reduce mechanics and build your first map/reduce job in Python Understand how to run chains of map/reduce jobs in the form of Pig scripts Use a real-world dataset-baseball performance statistics-throughout the book Work with examples of several analytic patterns, and learn when and where you might use them.…

  • Idioma: Inglés

    Editorial: Oreilly & Associates Inc, 2015

    1491923946 / 9781491923948

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Paperback. Condición: Brand New. 200 pages. 9.00x7.00x0.75 inches. In Stock. This item is printed on demand.