How SQL Databases Come up with Algorithms that You Would Have Never Dreamed Of
summary
Argument that modern cost‑based engines (Oracle, SQL Server, PostgreSQL) produce algorithms developers wouldn’t pick: thousand-line-long SQL running against billion-row tables in far below a millisecond, use of window functions to compute cumulative daily revenue instead of nested maps/loops, and the optimizer choosing a surprising plan (scan ~5,400 film_actor rows + hash join rather than six indexed counts). Demo of execution plans, histograms, and adaptive execution plans (Oracle 12 / DB2) shows the DB rewrites algorithms at runtime and it works on real large datasets.
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chapters (11)
- 0:00The power of SQL
- 4:43SQL vs Java productivity
- 7:09The complexity of Java
- 13:26Iterative data challenges
- 17:18Window functions in SQL
- 22:11Streams and declarative code
- 27:29SQL logical operations
- 32:23Understanding execution plans
- 39:14Indexing and data sets
- 44:20Database adaptability
- 48:06Conclusion and wrap-up
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