High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark - Info and Reading Options
By Holden Karau and Rachel Warren

"High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark" is published by O'Reilly Media in Jun 16, 2017 - Sebastopol, CA and it has 358 pages.
“High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark” Metadata:
- Title: ➤ High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark
- Authors: Holden KarauRachel Warren
- Number of Pages: 358
- Publisher: O'Reilly Media
- Publish Date: Jun 16, 2017
- Publish Location: Sebastopol, CA
“High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark” Subjects and Themes:
- Subjects: ➤ Data mining - Spark (Electronic resource : Apache Software Foundation) - Big data - Computer programs - Apache (computer program) - Data mining -- Computer programs
Edition Identifiers:
- The Open Library ID: OL26834196M - OL19543510W
- ISBN-13: 9781491943205
- ISBN-10: 1491943203
- All ISBNs: 1491943203 - 9781491943205
AI-generated Review of “High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark”:
"High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark" Description:
The Open Library:
xiv, 341 pages : 24 cm
Open Data:
"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." -- back cover
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