Practical SQL query monitoring and optimization Today the project owners demand results as soon as possible and most often - for yesterday. Time to market is crucial and it is practical to deliver bit-by-bit, get feedback and grow with the number of your customers. But as the project grows, the team does too and not all have the same expertise. As well rarely in the beginning the requirements clear enough to allow performance-wise SQL interaction. In most cases there does not exist an ORM that can solve this task for you and you will need to have hard T-SQL writer in the team. If you already know this story or are going this way then in this practical session we will share how to monitor, measure and optimize your SQL code and DB layer interaction.

1. Practical SQL Query Monitoring
and Optimization
Identify Data Layer Bottlenecks

2. About me
Project Manager @
10 years professional experience
Microsoft Certified Specialist
ivelin.andreev@icb.bg
http://www.linkedin.com/in/ivelin
Business Interests
ASP.NET, AJAX, jQuery
SOA, Integration
GIS, Mapping
SQL optimization
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3. A Well Known Story
Monitor and Measure Application
Analyze Tier Interaction
Getting Performance Hints
Identify Problematic Queries
Optimization Query Performance
Measure the Effect
Maintain
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4. Warning: A Bottleneck
Visual Studio Performance Wizard
CPU and Memory Sampling
Concurrency
Tier Interaction
SQL Server Profiler
Create trace
Analyze trace results
Replay trace
Log analyzer
Most frequent and timely queries
Identify long-running locks (and deadlocks)
Identify I/O activity
SQL Solutions Trace Analyzer / Deadlock Detector

5. Row vs. Chunk at a Time
Row at a time (RAT) processing
SELECT * FROM Activities WHERE ParentId = 1
SELECT * FROM Activities WHERE ParentId = 2
SELECT * FROM Activities WHERE ParentId = 16
Chunk at a time (CAT) processing
SELECT * FROM Activities WHERE ParentId IN (1,2,16)
Likely to happen when:
Components with own DataSource extraction
Complex code by different developers

6. DEMO 1
Row vs. Chunk at a Time
Analyzing Trace Logs

7. Getting Help
Analyze Execution Plan
Database Tuning Advisor
Suggests indexes and statistics
Opt.1: Improvement 20%
Opt.2: Improvement 20%
Dynamic Management Views
Missing Indexes (sys.dm_db_missing_index_groups)
Slowest Queries (sys.dm_exec_query_stats)

8. DEMO 2
Tuning Advisor
Dynamic Management Views

9. Analyze Query Plan
Tools
SQL Server Management Studio
SQL Sentry: free @ http://www.sqlsentry.com
Query Plan
Colour-scaled cost information
Cost filter by CPU, I/O or both
Better plan layout
Top Operations
Tuning Tips

10. Query Plan Basics
Table Scan (Heap)
Clustered index missing
Scans data pages (all data)
Index Scan
Scans index pages (less data)
Relies on order of pages
Index Seek
Highly selective queries (10-15% of rows)
Indexed Views
Require: Schema binding
Require: Deterministic functions

11. DEMO 3
Query Plan Explorer
OR vs. UNION

12. Indexes
Index types
Clustered / Non-clustered
Filtered index(SQL 2008)
Covering index
Objective
Optimal performance
Reduce slow scans
Difference in large data sets

13. Are Indexes Magical ?
Choosing Indexes
Measure query impact
Measure index size
Maintenance
Fragmentation = poor disk I/O
Reorganize vs. Rebuild
Automate: Nightly Job
Anti-patterns
Create indexes blindly
Execute non-indexable queries
SELECT * FROM Employees WHERE CAST(PNumber AS INT) 1
SELECT * FROM Customers WHERE ContactName LIKE ‘%a%’
SELECT * FROM Employees WHERE FName=‘a’ OR LName=‘b’
Reject indexes because of their overhead

14. SQL Server Statistics
Objective
WHERE clause order
Statistics on data distribution
Query Optimizer creates efficient plan
Up-to-date check
Automatically created for index keys
Estimated vs. Actual Rows
Maintenance
DB Default: AUTOCREATE and AUTOUPDATE
EXEC sp_updatestats
Automate: Nightly Job

15. User Defined Functions
Procedures vs. Functions
Performance vs. Reusability
Complex conditions
Used through the whole application
i.e. IsCaseClosed
Chunk at a Time
Table valued parameters (SQL 2008 and on)
Pass result from one function to next

16. Optimize Locks
Data Integrity
Data commit waits
NOLOCK
Prevent Deadlocks
Returns uncommitted data
Incorrect results
Less/More rows could be returned
Update one entity, retrieve another
Index page splits under heavy load(GUID)

17. DEMO 4
The NOLOCK Problem

18. Common Table Expressions (CTE)
Alias of a query (SQL 2005)
Advantages
Readability and reusability
Implement recursive query
Materializes when used
Uses indexes (Table v@r not)
Disadvantages
Can be used only once
Must be used immediately

19. Other
UNION vs. UNION ALL
Data Types
Do you really need BIGINT?
Requires storage
Requires time to read
Requires memory
BIGINT INT Delta (MB) Delta (%)
Primary Key 1267 977 290 23%
By_PropID_CountryID 813 741 72 9%
By_String 303 230 73 24%

20. SQL Resource Governor
Shared DB Server
Prioritize queries
Reporting vs. Dashboard
Memory, CPU
Connections, Parallelism
RG Configuration
Pools
Workload Groups
Custom classification function
Available in SQL Server Enterprise

21. Test Under Load
Life’s complicated
Concurrent queries
Multiple user
Cached Buffers
Tools
SQL Server Profiler Replay
SQL Server 2012 Distributed Replay
Snap In @ http://dreplaygui.codeplex.com/
SQL Load Generator
http://sqlloadgenerator.codeplex.com/

22. Summary
Steps
Capture/Analysis/Optimization
Measure the improvement
Maintain
Remember
Reoccurring improvement
Ideally you should analyze all SQL
Changes can affect SQL performance
in data size
result set size

23. DEMO 5
Trace Replay
SQL Load Generator
Resource Governor

24. Other Approaches
Caching
Application (Static)
Session
Context
WCF Session
Entity Framework Caching
Paging
Lazy loading
Parallel binding
Historical / Live data tables

25. SQL Saturday #152 Sponsors