Spark: The Definitive Guide: Big Data Processing Made Simple | Advanced Analytics with Spark: Patterns for Learning from Data at Scale | Programming in Scala | Kafka | Designing Data-intensive Applications | Hadoop | Learning Spark
Apache Spark is amazing when everything clicks. But if you havenât seen the performance improvements you expected, or still donât 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, youâll also learn how to make it sing.
With this book, youâll explore:
- How Spark SQLâs new interfaces improve performance over SQLâs 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 Sparkâs 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
- Sparkâs Streaming components and external community packages
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