Apache spark (335 Ergebnisse)

Sprache: Englisch
Verlag: Pearson Education (US), 2016
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Paperback. Zustand: Very Good. Apache Spark is rapidly becoming the preferred computing engine for Big Data systems. It's fast, fast, scalable, fault-tolerant, and exceptionally flexible and extensible. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to successfully build practical Spark solutions. Each short, easy lesson builds on all that's come before: you'll learn all of Spark's essentials, and extend it to meet your unique challenges. Apache Spark in 24 Hours, Sams Teach Yourself covers all this, and much more: What Apache Spark does, and how it fits into the Big Data landscape How to deploy Spark local or in the cloud, and use the Spark Cluster Architecture How to program Spark applications with Scala, functional Python, and the Spark API How to use RDs for caching, persistence, and output How to use Spark with both SQL and NoSQL How to work with advanced Spark programming techniques and common processing patterns How to extend spark with streaming, machine learning, R, and Sparkling Water How to manage Spark, extend it, and improve its performance Where Spark is headed, and how to prepare for the future Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; Did You Know? tips offer insider advice and shortcuts; and Watch Out alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Spark to solve a wide spectrum of Big Data problems.…

Sprache: Englisch
Verlag: Sams Publishing, 2016
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Sprache: Englisch
Verlag: Sams Publishing, 2016
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Sprache: Englisch
Verlag: Sams Publishing, 2016
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Sprache: Englisch
Verlag: Sams Publishing, 2016
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Sprache: Englisch
Verlag: Sams Publishing (edition 1), 2016
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Paperback. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Sprache: Englisch
Verlag: Pearson Education, 2016
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Zustand: Good. 1st Edition. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Sprache: Englisch
Verlag: Pearson Education, 2016
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Sprache: Englisch
Verlag: Pearson Education, 2016
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Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Zustand: Good. Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book ? Understand how Spark can be distributed across computing clusters ? Develop and run Spark jobs efficiently using Python ? A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn ? Find out how you can identify Big Data problems as Spark problems ? Install and run Apache Spark on your computer or on a cluster ? Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets ? Implement machine learning on Spark using the MLlib library ? Process continuous streams of data in real time using the Spark streaming module ? Perform complex network analysis using Spark's GraphX library ? Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain ? quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.…

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Zustand: Very Good. 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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Paperback. Zustand: Good. Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data.

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Paperback. Zustand: Very Good. Before you can build analytics tools to gain quick insights, you first need to know how to process data in real time. With this practical guide, developers familiar with Apache Spark will learn how to put this in-memory framework to use for streaming data.

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Paperback. Zustand: Good. Analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud. Learn the fundamentals, and more, of running analytics on large clusters in Azure and AWS, using Apache Spark with Databricks on top. Discover how to squeeze the most value out of your data at a mere fraction of what classical analytics solutions cost, while at the same time getting the results you need, incrementally faster. This book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. You will begin by learning how cloud infrastructure makes it possible to scale your code to large amounts of processing units, without having to pay for the machinery in advance. From there you will learn how Apache Spark, an open source framework, can enable all those CPUs for data analytics use. Finally, you will see how services such as Databricks provide the power of Apache Spark, without you having to know anything aboutconfiguring hardware or software. By removing the need for expensive experts and hardware, your resources can instead be allocated to actually finding business value in the data. This book guides you through some advanced topics such as analytics in the cloud, data lakes, data ingestion, architecture, machine learning, and tools, including Apache Spark, Apache Hadoop, Apache Hive, Python, and SQL. Valuable exercises help reinforce what you have learned. What You Will Learn Discover the value of big data analytics that leverage the power of the cloudGet started with Databricks using SQL and Python in either Microsoft Azure or AWSUnderstand the underlying technology, and how the cloud and Apache Spark fit into the bigger picture See how these tools are used in the real world Run basic analytics, including machine learning, on billions of rows at a fraction of a cost or free Who This Book Is ForData engineers, data scientists, and cloud architects who want or need to run advanced analytics in the cloud. It is assumed that the reader has data experience, but perhaps minimal exposure to Apache Spark and Azure Databricks. The book is also recommended for people who want to get started in the analytics field, as it provides a strong foundation.…

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Paperback. Zustand: Very Good. Analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud. Learn the fundamentals, and more, of running analytics on large clusters in Azure and AWS, using Apache Spark with Databricks on top. Discover how to squeeze the most value out of your data at a mere fraction of what classical analytics solutions cost, while at the same time getting the results you need, incrementally faster. This book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. You will begin by learning how cloud infrastructure makes it possible to scale your code to large amounts of processing units, without having to pay for the machinery in advance. From there you will learn how Apache Spark, an open source framework, can enable all those CPUs for data analytics use. Finally, you will see how services such as Databricks provide the power of Apache Spark, without you having to know anything aboutconfiguring hardware or software. By removing the need for expensive experts and hardware, your resources can instead be allocated to actually finding business value in the data. This book guides you through some advanced topics such as analytics in the cloud, data lakes, data ingestion, architecture, machine learning, and tools, including Apache Spark, Apache Hadoop, Apache Hive, Python, and SQL. Valuable exercises help reinforce what you have learned. What You Will Learn Discover the value of big data analytics that leverage the power of the cloudGet started with Databricks using SQL and Python in either Microsoft Azure or AWSUnderstand the underlying technology, and how the cloud and Apache Spark fit into the bigger picture See how these tools are used in the real world Run basic analytics, including machine learning, on billions of rows at a fraction of a cost or free Who This Book Is ForData engineers, data scientists, and cloud architects who want or need to run advanced analytics in the cloud. It is assumed that the reader has data experience, but perhaps minimal exposure to Apache Spark and Azure Databricks. The book is also recommended for people who want to get started in the analytics field, as it provides a strong foundation.…

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Paperback. Zustand: Good. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether theyre used for building dynamic network models or forecasting real-world behavior.

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Paperback. Zustand: Very Good. Discover the roadblocks you may face in data engineering and keep up with the latest trends such as Delta Lake. This book will help you learn how to build data pipelines that can auto-adjust to changes. Using practical examples, you will implement a solid data engineering platform that will streamline data science, ML, and AI tasks.…

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Verlag: O'Reilly (edition ), 2019
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paperback. Zustand: Very Good. Individually inspected: Light reading wear. Very good condition, Intact book with light amount of love.