Apache spark spark (950 résultats)

paperback. Etat : Good.

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Etat : very_good. Fast Free Shipping â" Very Good condition book with a firm cover and clean pages. Shows normal use and some light wear or limited notes markings. A solid, nice copy to enjoy.

Paperback. Etat : 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.…

Paperback. Etat : 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.

Etat : Very 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.…

Etat : 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.…

Etat : very_good. Book is in very good condition and may include minimal underlining highlighting. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service.

Paperback. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Etat : good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.…

Paperback. Etat : 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.

Etat : 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.

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

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

Paperback. Etat : 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.…

Etat : 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.

Etat : Very 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.…

Etat : 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.…

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Etat : Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

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Paperback. Etat : 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.

Paperback. Etat : 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.

Paperback. Etat : 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.

paperback. Etat : Good. 1st Edition. Corners are slightly bent. Used - Good.

Paperback. Etat : Fair. 2nd. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Paperback. Etat : 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.