My MySQL SQL Presentation
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Indexes are used to efficiently retrieve data from MySQL tables. The most common type is the B-Tree index, which allows quick retrieval of data by key and scanning in order. Indexes work by storing pointers to data rows, improving performance for queries that filter, join, group or sort by indexed columns. Good indexes are small, use minimal data types, and cover columns frequently queried, joined on or used for filtering, grouping and sorting.
My MySQL SQL Presentation
- 2. Most of our data lives in MySQL We want to get it as efficiently as possible How?
- 4. Small tables? Not always practical
- 5. Small tables? Not always practical Indexes?
- 6. Small tables? Not always practical Indexes? OK, but how?
- 8. First things first: What are indexes used for?
- 17. How do indexes work?
- 18. How do indexes work? Storage Types
- 19. BTree
- 21. BTree Ordered key-value map Most common storage type
- 22. BTree Ordered key-value map Most common storage type Quickly find a given key and can be scanned in order
- 23. BTree Ordered key-value map Most common storage type Quickly find a given key and can be scanned in order Works well with ranges All records between 50 and 100 All records starting with 'R'
- 25. Other storage types RTree / Spatial Index - Identify 'close' values in 2+ dimensions - Useful for geographic databases
- 26. Other storage types RTree / Spatial Index - Identify 'close' values in 2+ dimensions - Useful for geographic databases Hash - Unordered key/value map - Faster than BTree, but terrible for ranges
- 27. How do indexes work? Pointers
- 28. Pointers
- 32. Index Types
- 33. Single column
- 34. Single column
- 37. Covering
- 38. Covering
- 39. Covering
- 40. Partial
- 41. Partial
- 42. Partial
- 43. Downsides?
- 47. Selectivity
- 48. Selectivity of a column is the ratio between the number of distinct values and the number of total values
- 49. Selectivity of a column is the ratio between the number of distinct values and the number of total values Primary Keys and Unique Columns Always Have Selectivity of 1
- 50. Selectivity Tips
- 51. Selectivity Tips Always aim for >15%
- 52. Selectivity Tips Always aim for >15% Joins on columns with low selectivity are expensive
- 53. Selectivity Tips Always aim for >15% Joins on columns with low selectivity are expensive Watch out for columns like `status`, `gender`, and `active`
- 54. What makes a good index?
- 55. Small Use smallest data type possible Consider partial indexes on varchar/char to increase selectivity
- 56. Filter Columns Try to identify columns that will be used to filter data
- 57. Join Columns Identify columns that will often be joined on/to from other tables
- 58. Covering Indexes A query that can use a covering index will be substantially faster than one that has to read from the table
- 59. Group/Sort Identify columns that will be used for grouping and sorting
- 61. MySQL cannot use an index if the columns do not form a leftmost prefix of the index
- 72. Slow query log
- 73. Slow query log
- 74. Slow query log
- 75. Explain
- 76. Explain
- 77. Explain