Selasa, 22 Mei 2012

[Q331.Ebook] Get Free Ebook High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren

Get Free Ebook High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren

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High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren

High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren



High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren

Get Free Ebook High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren

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High Performance Spark: Best practices for scaling and optimizing Apache Spark, by Holden Karau, Rachel Warren

If you’ve successfully used Apache Spark to solve medium sized-problems, but still struggle to realize the "Spark promise" of unparalleled performance on big data, this book is for you. High Performance Spark shows you how take advantage of Spark at scale, so you can grow beyond the novice-level. It’s ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications.

  • Learn how to make Spark jobs run faster
  • Productionize exploratory data science with Spark
  • Handle even larger data sets with Spark
  • Reduce pipeline running times for faster insights

  • Sales Rank: #357340 in Books
  • Published on: 2016-12-25
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.84" h x .59" w x 5.91" l, .0 pounds
  • Binding: Paperback
  • 175 pages

About the Author

Holden Karau is transgender Canadian, and an active open source contributor. When not in San Francisco working as a software development engineer at IBM's Spark Technology Center, Holden talks internationally on Spark and holds office hours at coffee shops at home and abroad. She makes frequent contributions to Spark, specializing in PySpark and Machine Learning. Prior to IBM she worked on a variety of distributed, search, and classification problems at Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a Bachelor of Mathematics in Computer Science. Outside of software she enjoys playing with fire, welding, scooters, poutine, and dancing.

Rachel Warren is a data scientist and software engineer at Alpine Data Labs, where she uses Spark to address real world data processing challenges. She has experience working as an analyst both in industry and academia. She graduated with a degree in Computer Science from Wesleyan University in Connecticut.

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