The document discusses indexing in MySQL databases. It defines indexing as adding metadata like page numbers to data to allow for faster retrieval. Indexes provide advantages like faster queries but also disadvantages like using extra storage space. Indexes are most useful for operations that retrieve data, not add or modify it. The document provides examples of using CREATE INDEX and DROP INDEX statements to add and remove indexes. It also discusses when indexes are appropriate to apply, such as to fields used in WHERE clauses, and when they are not needed, like on usually unchanging fields. Finally, it covers index types like single column, multi-column, and range indexes as well as indexing methods like B+ trees and hashing.

1. MySQL Database Indexing By Abdul Barek tekSymmetry, LLC 12th January, 2010

2. What is Indexing? Like our text/reference books indexing 1000 pages of contents (Data) 4-5 pages indexes (meta data) to retrieve data quickly Indexes with page number (pointer)

3. Advantages Quick (less time) in data retrieval Less work for DB Engine in data searching

4. Disadvantages Requires extra space (4-5 pages for books) Create/update/delete index when DB insert/update/delete on data Using too many indexes will slow down database server (I.e.; index for ‘the’, ‘on’ of books)

5. Fetch >> Operation 95% fetch/data retrieval 5% insert/update/delete So why not indexing?

6. How to create/drop index CREATE INDEX indexName ON tableName(columnName) DROP INDEX indexName ON tableName

7. A students table (without index on name field)

8. Select statement without index EXPLAIN SELECT * FROM ‘students’ WHERE name =‘shishir’

9. Select statement with index EXPLAIN SELECT * FROM ‘students’ WHERE name =‘shishir’

10. Where will we apply index? All fields in where clause All foreign keys Where will we not apply index? Fields which is almost constant - select * from news where active=1

11. Where index will work Column = value LIKE ‘abc%‘, Full text search Comparison(<, <=, >, >=, BETWEEN) All joins with foreign keys Where index will not work LIKE ‘%abc%‘ LIKE ‘%abc’

12. Types of mysql indexing Single Column Select * from table where name=‘abc’ Multi-column Select * from table where name=‘abc’ AND age=18 create index indexName on table(col1,col2..) Multi column will be single column when ‘OR’ Select * from table where name=‘abc’ OR age=18

13. MySQL Indexing methods

14. Indexing graphical example (B+)

15. Indexing graphical example (B+) - cont

16. Indexing graphical example (B+) - Range

17. Indexing graphical example (Hash)

18. Question?