Advanced Analytics with Spark
Josh Wills, Sandy Ryza, Uri Laserson, Sean Owens
Language: English
Published by O'Reilly Media, US, 2017
- Softcover
- New
Seller: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
AbeBooks seller since June 20, 2025
Condition: New
£ 35.82
Quantity: Over 20 available
Add to basketItem description from seller
In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection-to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find the book's patterns useful for working on your own data applications. With this book, you will: Familiarize yourself with the Spark programming model Become comfortable within the Spark ecosystem Learn general approaches in data science Examine complete implementations that analyze large public data sets Discover which machine learning tools make sense for particular problems Acquire code that can be adapted to many uses.…
Seller Inventory # LU-9781491972953
- Title
- Advanced Analytics with Spark
- Author
- Josh Wills, Sandy Ryza, Uri Laserson, Sean Owens
- Publisher
- O'Reilly Media, US
- Publication year
- 2017
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1491972955
- ISBN 13
- 9781491972953
- Edition
- 2nd Edition
- Item weight
- 666 grams
In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming.
You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—including classification, clustering, collaborative filtering, and anomaly detection—to fields such as genomics, security, and finance.
If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find the book’s patterns useful for working on your own data applications.
With this book, you will:
- Familiarize yourself with the Spark programming model
- Become comfortable within the Spark ecosystem
- Learn general approaches in data science
- Examine complete implementations that analyze large public data sets
- Discover which machine learning tools make sense for particular problems
- Acquire code that can be adapted to many uses
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
Rarewaves USA United
HEBRON, KY, U.S.A.
AbeBooks seller since June 20, 2025
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