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Awantik Das edited this page Mar 17, 2017 · 3 revisions

Introduction

  • What is Apache Spark?
  • Spark Jobs and APIs
  • Review of Resilient Distributed Datasets (RDDs), DataFrames, and Datasets
  • Review of Catalyst Optimizer and Project Tungsten
  • Review of the Spark 2.0 architecture

Resilient Distributed Datasets (RDD)

  • Internal workings of an RDD
  • Creating RDDs
  • Global versus local scopes
  • Transformations
  • Actions
  1. Understanding Spark
  2. Spark Jobs & API
  3. Architecture
  4. RDD Internals
  5. Creating RDD
  6. Understanding Deployment & Program Behaviour
  7. RDD Transformation & Action
  8. Assignments 1
  9. Best Practices -1
  10. Introduction to DataFrame
  11. PySpark SQL
  12. Pandas to DataFrames
  13. Machine Learning with PySpark
  14. Transformers
  15. Estimators
  16. Spark Streaming
  17. Structured Streaming
  18. GraphX & GraphFrames
  19. Data Processing Architectures
  20. Problems
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