Book Content
chapters • 9h8m total length
1. Understanding Spark
2. Installing Spark
3. Resilient Distributed Datasets
4. DataFrames
5. Prepare Data for Modeling
6. Introducing MLlib
7. Introducing the ML Package
8. GraphFrames
9. TensorFrames
10. Polyglot Persistence with Blaze
11. Structured Streaming
12. Free Spark Cloud Offering
13. Packaging Spark Applications
