By Sandy Ryza,Uri Laserson,Sean Owen,Josh Wills
In the second one version of this useful publication, 4 Cloudera info scientists current a collection of self-contained styles for acting large-scale facts research with Spark. The authors carry Spark, statistical equipment, and real-world facts units jointly to educate you ways to process analytics difficulties via instance. up-to-date for Spark 2.1, this variation acts as an advent to those thoughts and different most sensible practices in Spark programming.
You’ll begin with an advent to Spark and its atmosphere, after which dive into styles that practice universal techniques—including type, clustering, collaborative filtering, and anomaly detection—to fields equivalent to genomics, defense, and finance.
If you may have an entry-level figuring out of desktop studying and statistics, and also you application in Java, Python, or Scala, you’ll locate the book’s styles beneficial for engaged on your individual info applications.
With this ebook, you will:
- Familiarize your self with the Spark programming model
- Become cozy in the Spark ecosystem
- Learn common techniques in facts science
- Examine whole implementations that research huge public facts sets
- Discover which desktop studying instruments make experience for specific problems
- Acquire code that may be tailored to many uses
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Extra info for Advanced Analytics with Spark: Patterns for Learning from Data at Scale
Advanced Analytics with Spark: Patterns for Learning from Data at Scale by Sandy Ryza,Uri Laserson,Sean Owen,Josh Wills