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 structure The choice between data
joins in Core Spark and Spark SQL Techniques for getting the most
out of standard RDD transformations How to work around performance
issues in Spark's key/value pair paradigm Writing high-performance
Spark code without Scala or the JVM How to test for functionality
and performance when applying suggested improvements Using Spark
MLlib and Spark ML machine learning libraries Spark's Streaming
components and external community packages
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