payneal / Spark-The_Definitive_Guide

Notes from Spark: The definitive guide

Spark: The Definitive Guide

Part I. General Overview of Big Data and Spark

1. What is Apache Spark
2. A gentles Introduction to Spark
3. A Tour of Sparks Toolset

Part II. Structured APIs - Dataframes, SQL, and Data Sets

4. Structurf API overview
5. Basic Structured Operations
6. Working with different types of Data
7. Aggregations
8. Joins
9. Data Sources
10. SparkSQL
11. Datasets

Part III. low-level apis

12. Resilient Distributed Datasets (RDDs)
13. Advanced RDDS
14. Distributed Shared Variables

Part IV. Production Applications

15. How Spark Runs on a Cluster
16. Developing Spark Applications
17. Deploying Spark
18. Monitoring and Debuging
19. Performance Tuning

Part V. Streaming

20. Stream Processing Fundementals
21. Structurf Straming Basics
22. Event-Time and Stateful Production
23. Structured Streaming In Production

Part VI. Advanced Analytics and Machine Learning

24. Advanced Analytics and Machine Learning Overview
25. Preprocessing and Feature Engineering
26. Classification
27. Regression
28. Recommendation
29. Unsupervised Learning
30. graph Analytics
31. Deep learningue

Part VII. EcoSystem

32. Language Specifics: Python(Pyspark) and R (SparkRand sparklyr)