PySpark basics for everyday work
Practical guide with clear examples and expected outputs to master core DataFrame transformations. Includes readable chaining patterns and quick validations.
Spark & Delta 101
Query past versions in Delta
Learn versionAsOf and timestampAsOf, validate changes, and understand when time travel is best for auditing, recovery, and regression analysis in Delta Lake.
Spark partitions without the pain
Introduce spark.sql.shuffle.partitions, repartition, and coalesce with a reproducible example to see impact on stages, time, and shuffle size.
What Delta stores on disk
Explore the on‑disk layout, commits, and checkpoints, and see why it matters for performance, maintenance, and troubleshooting in production.
Your first Delta table, step by step
End‑to‑end walkthrough: create a Delta table, insert data, read, filter, and validate results with expected outputs. The minimal base before any optimization work.