Learning PySpark
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0
Publisher:Packt Publishing Limited
By: Tomasz Drabas and Denny Lee
Paid access
|Jun 2024
Table of Contents
- Understanding Spark
- Installing Spark
- Resilient Distributed Datasets
- DataFrames
- Prepare Data for Modeling
- Introducing MLlib
- Introducing the ML Package
- GraphFrames
- TensorFrames
- Polyglot Persistence with Blaze
- Structured Streaming
- Free Spark Cloud Offering
- Packaging Spark Applications
PDF ISBN: 978-1-78646-625-9
Publisher: Packt Publishing Limited
Copyright owner: © 2017 Packt Publishing Limited
Publication date: 2024
Language: English
Pages: 274
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