MySQL Indexes and Histograms to Speed Up Your Queries
summary
Explains how MySQL uses clustered primary keys and secondary indexes, shows a demo where an index cuts optimizer cost from 10.25 to 0 and reads one row instead of a table scan, and shows a city/district example where adding an index drops cost from 442 to 9 and rows read to 26. Covers functional indexes, multi-value JSON indexes, hash joins for equality joins, invisible indexes and why histograms help only for low‑churn data.
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chapters (21)
- 0:00Introduction
- 0:25Daves background
- 1:12What is an index
- 2:16What is a NoSQL index
- 3:05MySQL clustered index
- 3:51MySQL primary key
- 4:31MySQL secondary keys
- 6:05MySQL indexes
- 8:57Postgres indexes
- 9:18Finding bad schemas
- 13:36Customer ID
- 13:46Create an Index
- 14:20Create a Geometry Index
- 17:50MultiValue Indexes
- 19:29Multiple Column Indexes
- 21:38Foreign Keys
- 22:31Delete Cascade
- 22:52Hash Joints
- 24:10Invisible Indexes
- 26:14Histograms
- 29:22Indexes are fast
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