Understanding indices
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This document discusses understanding database indices. It covers index architecture including heaps, clustered, and nonclustered indexes. It discusses using SQL Server dynamic management objects to view index usage and missing indexes. The document outlines golden rules for optimal index design and the importance of index maintenance to prevent fragmentation. Regular index maintenance is recommended to minimize storage space usage and I/O.
Understanding indices
- 1. UNDERSTANDING INDICES Richard Douglas • Sales Engineer, SQL Sentry • Social Media: @SQLRich, LinkedIn, • Blog Info: http://blogs.sqlsentry.com/author/RichardDouglas/; http://SQL.RichardDouglas.co.uk
- 2. Tuning blog: http://www.sqlperformance.com/ E-mail ebooks@sqlsentry.com for free copies of our $10 e-books:
- 3. “CAN’TYOUJUST PUT AN INDEXON IT?”
- 6. YOU NEED THE BIG PICTURE
- 7. It’s all about DWI knowledge: INDEXING STRATEGIES D W I a t a o r k l o a d n t e r n a l s
- 8. YOUR HOST • Richard Douglas • Sales Engineer at SQL Sentry • Blog: http://SQL.RichardDouglas.co.uk • Twitter: @SQLRich • Email: RDouglas@SQLSentry.com • Slides: http://www.Slideshare.net/SQLRich
- 9. AGENDA • Pre requisites • Understanding indexes and their architecture • Utilising SQL Server DMO’s • Index golden rules • The importance of maintenance
- 10. Understanding the SQL Server Data Page PRE REQUISITES • A data page is 8KB (8192 bytes) • Page header is 96 bytes leaving 8096 bytes for data • Slot array stores the logical order Page header 1 - Cooper 1 2 - Hofstadter 2 3 - Koothrappali 3 4 - Kripke 54 5 - Wolowitz 5
- 11. INDEX ARCHITECTURE Heaps Clustered Indexes Nonclustered Indexes Nonclustered Columnstore Indexes
- 12. HEAP STRUCTURE
- 14. INDEX EXAMPLE 1 Douglas 2 Kline 3 Bertrand 4 Martin 5 White 6 Fallen 7 Edwards 8 Ozar 9 Randal 10 Trip 11 Cunningham 12 Woody 13 La Rock 14 Locke 6993 Saxby 6994 Fryer 6995 Sabin 6996 Langford 6997 Bolton 6998 Fairweather 6999 Whittles 1 ,1, 100 8, 1, 101 You Get The Idea File 1 Page 100 File 1 Page 101 File 1 Page 404 File 1 Page 911 File 1 Page 999 Nothing to see here, move along please Please help my query performance is poor 1 ,1, 100 Other records 6993, 1, 999 6993, 1, 999 dbo.Customer Clustered primary key on an identity. Lowest key
- 17. INDEX OPTIONS Fill factor Pad Index Filtered index (WHERE) Include Data Compression Online
- 19. INTRODUCING INDEX DMO’S • Admin o Sys.dm_db_index_physical_stats • Usage o Sys.dm_db_index_usage_stats o Sys.dm_db_index_operational_stats • Missing o Sys.dm_db_missing_index_details o Sys.dm_db_missing_index_columns o Sys.dm_db_missing_index_groups o Sys.dm_db_missing_index_group_stats
- 20. MISSING INDEX LIMITATIONS • Not intended to fine tune an indexing configuration. • Only gathers 500 missing index groups. • Optimal column orders for the index are not specified. • In some scenarios it has been known to only return information on included columns. • Returns only raw information about columns. • Does not suggest filtered indexes. • It can return different costs for the same missing index group that appears multiple times in XML Showplans. • Multiple similar indexes may be returned. • Only considers non-trivial query plans.
- 21. Bad example; Surname, Firstname, Middle Initial GOLDEN RULES FOR CLUSTERED INDEXES • Narrow • Static • Progressive • Unique • Fixed width • Not Null Impacts nonclustered indexes Fragmentation Space impact This example could have 13 bytes of overhead alone; • 4 byte uniquifier • 2 byte variable offset + 6 bytes for variable length fields • 1 byte for NULL values and NULL bitmap
- 22. GOLDEN RULES FOR NONCLUSTERED INDEXES • Have an optimal clustered key • Not narrow • Reduce unnecessary overhead o Fixed Width o Not null • Consolidate • Index foreign keys
- 23. Page split scenario THE IMPORTANCE OF MAINTENANCE Page header Data Row 1 Data Row 2 Data Row 3 Data Row 4 321 Data Row 5 5 Page header Data Row 4 Data Row 5 54 Page header Data Row 6 Data Row 7 Data Row 8 Data Row 10 109876 Data Row 9 Page pointers
- 24. Two main types FRAGMENTATION • Logical / External “When the next logical page is not the next physical page” o Significantly reduces scan performance o Can cause extra IO • Physical / Internal “When page density is sub optimal” o Increased storage space o More room required in the buffer pool o More IO’s to read in the data o More logging, bigger backups
- 25. FIXING FRAGMENTATION • Rebuild Indexes • Reorganize Indexes • Options o Maintenance plan o Custom/community scripts o Third party tools • Guideline(sys.dm_db_Index_Physical_Stats provides these figures) o 0 – 5% No action o 5 – 30% Reorganize o 30% + Rebuild
- 26. MAINTENANCE BEST PRACTICES • Auto Close • Auto Shrink • Statistics • Recovery models If you value your job, don’t turn the top two on.
- 29. THANK YOU! • Slides will be available at http://Slideshare.net/SQLRich • More information at: o SQLSkills, et al • E-mail ebooks@sqlsentry.com for free copies of our e-books: o Just tell them where you met me • My contact info for other questions: o RDouglas@SQLSentry.com o Twitter: @SQLRich o Blogs: http://SQL.RichardDouglas.co.uk / http://http://blogs.sqlsentry.com/author/RichardDouglas