Scala for Spark in Production; Alexy Khrabrov, Andy Petrella, Xavier Tordoir; 2017

Scala for Spark in Production Upplaga 1

av Alexy Khrabrov, Andy Petrella, Xavier Tordoir
If you're an Apache Spark developer, this practical book provides an introduction to the Scala programming language to help you get more out of this framework. Written in Scala, Spark uses its rich Domain-Specific Language (DSL) abilities to present SQL views, extensibility, streaming, and DataFrames. With Scala, you'll be able to perform on par with Java, and work with distributed systems based on the Java Virtual Machine (JVM). Spark succeeded mostly because it took very intuitive Scala collections API and made them work on a cluster, unifying the memory of all of its machines to present a coherent view of a "big data" collection. Spark tries to conform to the Scala API as close as possible, and in this book, we take a view that Spark is "simply" distributed Scala. That makes many points of Spark much easier to understand
If you're an Apache Spark developer, this practical book provides an introduction to the Scala programming language to help you get more out of this framework. Written in Scala, Spark uses its rich Domain-Specific Language (DSL) abilities to present SQL views, extensibility, streaming, and DataFrames. With Scala, you'll be able to perform on par with Java, and work with distributed systems based on the Java Virtual Machine (JVM). Spark succeeded mostly because it took very intuitive Scala collections API and made them work on a cluster, unifying the memory of all of its machines to present a coherent view of a "big data" collection. Spark tries to conform to the Scala API as close as possible, and in this book, we take a view that Spark is "simply" distributed Scala. That makes many points of Spark much easier to understand
Upplaga: 1a upplagan
Utgiven: 2017
ISBN: 9781491929285
Förlag: O'Reilly Media
Format: Häftad
Språk: Engelska
Sidor: 200 st
If you're an Apache Spark developer, this practical book provides an introduction to the Scala programming language to help you get more out of this framework. Written in Scala, Spark uses its rich Domain-Specific Language (DSL) abilities to present SQL views, extensibility, streaming, and DataFrames. With Scala, you'll be able to perform on par with Java, and work with distributed systems based on the Java Virtual Machine (JVM). Spark succeeded mostly because it took very intuitive Scala collections API and made them work on a cluster, unifying the memory of all of its machines to present a coherent view of a "big data" collection. Spark tries to conform to the Scala API as close as possible, and in this book, we take a view that Spark is "simply" distributed Scala. That makes many points of Spark much easier to understand
If you're an Apache Spark developer, this practical book provides an introduction to the Scala programming language to help you get more out of this framework. Written in Scala, Spark uses its rich Domain-Specific Language (DSL) abilities to present SQL views, extensibility, streaming, and DataFrames. With Scala, you'll be able to perform on par with Java, and work with distributed systems based on the Java Virtual Machine (JVM). Spark succeeded mostly because it took very intuitive Scala collections API and made them work on a cluster, unifying the memory of all of its machines to present a coherent view of a "big data" collection. Spark tries to conform to the Scala API as close as possible, and in this book, we take a view that Spark is "simply" distributed Scala. That makes many points of Spark much easier to understand
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I november 2017 släpptes boken Scala for Spark in Production skriven av Alexy Khrabrov, Andy Petrella, Xavier Tordoir. Det är den 1a upplagan av kursboken. Den är skriven på engelska och består av 200 sidor djupgående information om data. Förlaget bakom boken är O'Reilly Media.

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