EaseWithApacheSpark — PySpark Series

Series follows learning from Apache Spark (PySpark) with quick tips and workaround for daily problems in hand.

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Click on the links below to follow -

1. PySpark — Create Data Frame from Python List or Iterable
2. PySpark — Parse Spark Schema from datatype string
3. PySpark — Create Data Frame from API
4. PySpark — Read/Parse JSON column from another Data Frame
5. PySpark — Flatten JSON/Struct Data Frame dynamically
6. PySpark — Merge Data Frames with different Schema
7. PySpark — Optimize Pivot Data Frames like a PRO
8. PySpark — User Defined Functions vs Higher Order Functions
9. PySpark — The Famous Salting Technique
10. PySpark — Columnar Read Optimization
11. PySpark — The Magic of AQE Coalesce
12. PySpark — The Tiny File Problem
13. PySpark — Read Binary Files like PNG or PDF
14. PySpark — Read Compressed gzip files
15. PySpark — JDBC Predicate Pushdown
16. PySpark — Tune JDBC for Parallel effect
17. PySpark — The Basics of Structured Streaming
18. PySpark — Count(1) vs Count(*) vs Count(col_name)
19. PySpark — Distributed Broadcast Variable
20. PySpark — The Cluster Configuration
21. PySpark — Optimize Data Scanning exponentially
22. PySpark — The Factor of Cores
23. PySpark — Fix Column Header with Spaces
24. PySpark — Dynamic Partition Overwrite
25. PySpark — Upsert or SCD1 with Dynamic Overwrite
26. PySpark — Implementing Persisting Metastore
27. PySpark — Setup Delta Lake
28. PySpark — Delta Lake Column Mapping
29. PySpark — Delta Lake Integration using Manifest
30. PySpark — Connect Azure ADLS Gen 2
31. PySpark — Structured Streaming Read from Sockets
32. PySpark — Structured Streaming Read from Files
33. PySpark — Structured Streaming Read from Kafka
34. PySpark — Connect AWS S3
35. PySpark — Data Frame Joins on Multiple conditions
36. PySpark — Worst use of Window Functions
37. PySpark — The Effects of Multiline
38. PySpark — Optimize Huge File Read
39. PySpark — Estimate Partition Count for File Read
40. PySpark — Optimize Parquet Files

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