Geek Sync | SQL Server Indexing Basics
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The document provides an overview of SQL Server indexing, focusing on clustered and non-clustered indexes. It explains the characteristics, advantages, and scenarios where these indexes are useful or not useful. Key points include the importance of data sort order, index uniqueness, and the impact of indexing on performance.
![Non Clustered Indexes
When are they not useful?
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Geek Sync | SQL Server Indexing Basics
- 1. SQL Server Indexing Basics August 11, 2015 Mindy Curnutt Director of DB Architecture TMW Systems, Inc. @sqlgirl
- 3. Clustered Indexes • What are they? • Desired Qualities 2
- 4. Clustered Indexes What are they? • Sort Order of the data within the table • One per table 3
- 5. Clustered Indexes Desired Qualities • Increasing • Static • Narrow Data Type • Unique 4
- 6. Clustered Indexes Increasing • Data is added to the end of the index • Reduces fragmentation 5
- 7. Clustered Indexes Static • Changes cause… • Fragmentation • Additional overhead for Non Clustered Indexes 6
- 8. Clustered Indexes Narrow Data Type • Less Data Duplicated • Smaller… • Databases • Backups • Maintenance Plan Times • Scans 7
- 9. Clustered Indexes Unique • Not Required • Prevents Uniqueifier • Best to be narrow! 8
- 10. Clustered Indexes Demos • No Clustered Index (Heap) • Non Unique Clustered Index • Unique Clustered Index 9
- 11. Non Clustered Indexes • What are they? • Why are they useful? • When are they not useful? 10
- 12. Non Clustered Indexes What are they? 11 Clustered Index Non Clustered Index
- 13. Non Clustered Indexes Why are they useful? • Smaller than table itself • Seek vs Scan 12 SELECT COUNT(*) FROM addressbook WHERE phone LIKE '707942%'
- 14. Non Clustered Indexes When are they not useful? • When too many rows are returned and all the columns needed for the query are not present in the nonclustered index • Extra work for SQL regarding inserts, updates and deletes 13
- 15. Non Clustered Indexes When are they not useful? 14 SELECT COUNT(*) FROM addressbook WHERE phone LIKE '707942%' AND [street name] LIKE 'Stringer%'