Practical MySQL Indexing guidelines by Stéphane Combaudon
Stéphane Combaudon of Dailymotion.
Index: separate data structure to speed up SELECTs. Think of index in a book. In MySQL, key=index. Consider that indexes are trees.
InnoDB’s clustered index – data is stored with the Primary Key (PK) so PK lookups are fast. Secondary keys hold the PK values. Designing InnoDB PK’s with care is critical for performance.
An index can filter and/or sort values. An index can contain all the fields needed for the query you don’t need to go to the table (a covering index).
MySQL only uses 1 index per table per query (not 100% true – OR clauses), so think of a composite index when you can. Can’t index TEXT fields (use a prefix). Same for BLOBs and long VARCHARs.
Indexes: speed up queries, increases the size of your dataset, slows down writes. How big is the write slowdown? Simple test by Stephane, for in-memory workloads he says adding 2 keys makes performance 2x worse; for on-disk workloads he says its 40x worse. Never neglect the slowdown of your writes when you have an index. There is a graph in the slidedeck.
What is a bad index? Unused indexes. Redundant indexes. Duplicate indexes.
Indexing is not an exact science, but guessing is probably not the best way to design indexes. Always check your assumptions – EXPLAIN does not tell you everything, time your queries with different index combinations, SHOW PROFILES is often valuable. Slow query log is a good place to start.
Many slides with examples, so I hope Stephane posts the deck soon. If possible, try to sort & filter (an index is not always the best for sorting).
InnoDB’s clustered index is always covering. SELECT by PK is the fastest access with InnoDB.
An index can give you 3 benefits: filtering, sorting, covering.
See Userstats v2 – you need Percona Server or MariaDB 5.2+. See also pt-duplicate-key-checker to find redundant indexes easily. See also pt-index-usage to help answer questions not covered by userstats.