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Big Data with Spark

What to do when data outgrows one machine: distributed thinking, RDDs and DataFrames, lazy transformations vs actions, joins and the expensive shuffle, partitioning, Parquet columnar formats, window functions, Spark SQL, and a capstone analyzing a dataset too big for pandas habits. Taught through runnable pandas stand-ins.

13 lessons about 4 hours Medium
Learn it by writing it.

Every lesson runs real code in your browser, checked the moment you submit. No installing anything, no setup, no waiting.

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What this course covers

  1. When Data Outgrows One Machine
  2. Distributed Thinking
  3. RDDs and DataFrames
  4. Transformations vs Actions
  5. DataFrame Operations
  6. GroupBy and Aggregations
  7. Joins Across Big Tables
  8. Shuffles: The Expensive Move
  9. Partitioning Your Data
  10. Parquet and Columnar Formats
  11. Window Functions
  12. Spark SQL
  13. Capstone: Analyze a Big Dataset

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