natural born killers, performance issues to avoid

Natural Born Killers, performance issues to avoid

Richard Douglas

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Natural Born Killer

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Source: http://cheezburger.com/View/5939764992

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Adhering to best practices?

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Your host

• Richard Douglas

• Systems Consultant

• SQL Server MCITPro

• Maidenhead SQL User Group Leader

• Blog: http://SQL.RichardDouglas.co.uk

• Twitter: @SQLRich

• Email: Richard.Douglas@Quest.comRichard_Douglas@Dell.com

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Agenda

• Statistics

• Table Design

• Scalar UDF’s

• Indices

• Key lookups

• Sargability

• Table variables

• Parameter sniffing

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Statistics

• SQL uses a cost based optimizer

• Costs influenced by statistics

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Statistics

• Creating Statistics– Automatic

– Manual

– CREATE STATISTICS

– sp_CreateStats

• Updating Statistics

• Sp_UpdateStats

• UPDATE STATISTICS

Permanent Table Temporary Table

1st record 1st record

- 6 records

LT 500 recs, 500 changes LT 500 recs, 500 changes

GT 500 recs, 500 changes + 20%

GT 500 recs, 500 changes + 20%

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Table Design

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ream/

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Example of bad design

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Example of a better design

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Table Design – Size comparison

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Good table design benefits

• Minimise the CPU overhead.

• Increase the number of records in the buffer cache.

• Reduce the amount of physical disk IO.

• Reduce the amount of network traffic.

• Reduce the data file size(s).

• Reduce the working size of the Transaction Log.

• Reduce Full/Diff /T-Log backup file size.Thereby increasing your ability to deliver your RTO.

• Keep transaction time to a minimum.

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Scalar User Defined Functions

• The Good– Re-Usable code

• The Bad– Runs once per record in record set

– They don’t take advantage of parallelism

– They use Nested Loop joins regardless

• The Ugly– So ugly it’s hidden from the query plan and IO statistics

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Scalar UDF Solutions and Alternatives

• If you have to use them:– View the actual IO usage in Profiler

• If you can replace them:– Look at Table Value Functions

– Look at CLR

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Indices

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It’s all about DWI knowledge:

Indexing strategies

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Bad example; Surname, Firstname, Middle Initial

Golden Rules for Clustered Indexes

• Narrow

• Static

• Progressive

• Unique

• Fixed width

• Not Null

Impacts nonclusteredindexes

Fragmentation

Space impact

This example will 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

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Golden Rules for NonClustered Indexes

• Have an optimal clustered key

• Not narrow

• Reduce unnecessary overhead

– Fixed Width

– Not null

• Consolidate

• Index foreign keys

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Key Lookups – The silent killer

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Sargability

• SARGable – “Search ARGument able”

• T-SQL functions around a predicate can break SARGability

• Some caveats to remember

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Table Variables Vs. Temp Tables

Table Variables

• Fast when used with small data sets.

• Have a limited scope

• Use less locking and logging resources than temp tables– http://sql.richarddouglas.co.uk/archive/2011/06/rollback-gotchas-

part-2-2.html

• Estimated statistics always show 1 record

• Cannot be altered after they are declared

• Mythbuster - MAY be memory only, this isn’t guaranteed

• Generally faster with smaller data sets

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Table Variables Vs. Temp Tables

Temp Tables

• Uses statistics– Stat population will cause recompiles (statement level in 2005 +)

– Can create better plans

• Wider scope

• Can be rolled back

• Can be altered after creation

• Generally faster with larger data sets

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Parameter Sniffing

• What is it?– It’s all a matter of statistics

• How do I know when it will affect me?– Monitor the IO and CPU

– This means baselining your environment

• What are my options?– Rewrite dynamic queries

– Query Hints:

– WITH RECOMPILE

– OPTIMIZE FOR

– Plan Guides

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Demos

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Summary

• Statistics

• Table Design

• Scalar UDF’s

• Indices

• Key lookups

• Sargability

• Table variables

• Parameter sniffing

32 Dell SoftwareUnderstanding Indices

Any questions?

Thank you

Richard_Douglas@Dell.com@SQLRich

http://bit.ly/11jr4fC