High-Performance-Spark-Best-Practices-for-Scaling-and-Optimizing-Apache-Spark
COPY LINK: https://pdf.bookcenterapp.com/yumpu/1491943203 Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you’ll also learn how to make it sing.With this book, you’ll explore:How Spark SQL’s new interfaces improve performance over SQL’s RDD data structureThe choice between data joins in Core Spark and Spark SQLTechniques for getting the most out of standard RDD transformationsHow to work around performance issues in Spark’s key/value pair paradigmWriting high-performance Spark code without Scala or the JVMHow to test for functionality and performance when applying suggested improvementsUsing Spark MLlib and Spark ML machine learning librariesSpark’s Streaming components and external community packages
COPY LINK: https://pdf.bookcenterapp.com/yumpu/1491943203
Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you’ll also learn how to make it sing.With this book, you’ll explore:How Spark SQL’s new interfaces improve performance over SQL’s RDD data structureThe choice between data joins in Core Spark and Spark SQLTechniques for getting the most out of standard RDD transformationsHow to work around performance issues in Spark’s key/value pair paradigmWriting high-performance Spark code without Scala or the JVMHow to test for functionality and performance when applying suggested improvementsUsing Spark MLlib and Spark ML machine learning librariesSpark’s Streaming components and external community packages
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High Performance Spark: Best Practices
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COPY LINK: https://pdf.bookcenterapp.com/yumpu/1491943203 Apache Spark is amazing when
everything clicks. But if you haven’tseen the performance improvements you expected, or
still don’tfeel confident enough to use Spark in production, this practical book is for you.
Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your
Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for
software engineers, data engineers, developers, and system administrators working with largescale
data applications, this book describes techniques that can reduce data infrastructure costs
and developer hours. Not only will you gain a more comprehensive understanding of Spark,
you’llalso learn how to make it sing.With this book, you’llexplore:How Spark
SQL’snew interfaces improve performance over SQL’sRDD data structureThe
choice between data joins in Core Spark and Spark SQLTechniques for getting the most out of
standard RDD transformationsHow to work around performance issues in Spark’skey/value
pair paradigmWriting high-performance Spark code without Scala or the JVMHow to test for
functionality and performance when applying suggested improvementsUsing Spark MLlib and
Spark ML machine learning librariesSpark’sStreaming components and external
community packages
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