1. Perfmon and Profiler 101

2. About Me: Brent Ozar SQL Server Expert for Quest Software Former SQL DBA Managed >80tb SAN, VMware Dot-com-crash experience Specializes in performance tuning

3. Today’s Agenda The Civic & Godzilla Metrics, Trace, Mitigations Taking Before and After Pictures Helpful Tools Sample Scenarios Resources and Q&A

4. If You Don’t Need to Go Fast… Photo Licensed With Creative Commons From http://flickr.com/photos/stevekeys/2755142278/

5. But The Faster You Want To Go

6. The More You Have To Measure

7. Windows “Check Engine” Light

8. And If You Wanna Go Fast:

9. Two Approaches to Detection Exceptions Monitoring: Check Engine Light Reactive Actions Proactive Monitoring: Detailed Gauges Preventative Actions

10. Metrics-Trace-Mitigation Process

11. Where Do We Start?

12. Capture Metrics With Perfmon Performance Monitor, aka Perfmon Ships with all Windows versions Polls any server from your desktop Pulls performance metrics Writes them to a file Requires some OS permissions Does not include alerts or analytics

13. 12

14. Memory Counters Memory – Available Mbytes Paging File - % Usage SQLServer:Buffer Manager – Buffer cache hit ratio Page life expectancy SQLServer:Memory Manager – Memory Grants Pending

15. Storage Metrics: Physical Disk Avg. Disk Queue Length Avg. Disk sec/Read Avg. Disk sec/Write Disk Reads/sec Disk Writes/sec % Disk Time

16. CPU & Other Metrics Processor - % Processor Time System – Processor Queue Length SQLServer:General Statistics – User Connections

17. 16 The Raw Output: CSV Files

18. 17 Adding Analytical Formulas

19. 18 That’s a Lot of Zeroes!

20. 19 Sorting High to Low

21. What To Look For, In Order System – Processor Queue Length Memory – Available Mbytes Lock pages in memory!

22. What To Look For Next Disk metrics on the page file drive Disk metrics on the log file drive Disk metrics on the data file drive Disk metrics on the TempDB drive

23. Got Everything on One Drive? Narrow it down with the DMV sys.dm_io_virtual_file_stats

24. Capture Queries with a Trace

25. Columns to Capture What’s Going On Text Data DatabaseID and/or DatabaseName Login Name Host Name Application Name What The Impact Was CPU Reads Writes Duration Start Time End Time

26. Profiler’s Results: A Trace Table

27. Order By Duration Descending

28. Casting and Grouping

29. Correlate Metrics & Trace Show a cause and effect relationship Fields to mentally “join” on: Date/Time ranges CPU Reads/Writes Duration

30. Metrics-Trace-Mitigation Process

31. If Our Servers Were Houses… Before After

32. Consistent and Repeatable 100 users accessing the web site Closing a typical financial period 10 users running a report Importing 100,000 records for a nightly ETL process Think scripts, think load generation tool Capture statistics during test run

33. When To Take A Picture Before Adding new hardware Installing a SQL Server service pack Changing storage configurations New application versions Every quarter After

34. Plus Monitoring For… Before Things break Populations change over time Budgeting Need to enforce standards We’re not the only ones working on the house After

35. Save Perfmon & Profiler Data Central file share Even better: in a database Name by server, by date Revisit every budget season Use for new hire training

36. Tool: Performance Dashboard

37. Tool: Data Mining

38. Table Analysis Tools For The Cloud

39. Detect Categories of Load

40. Works for Profiler Results Too

41. Tool: ClearTrace

42. Cleans Up Queries

43. Sample Problem #1 Metrics tell us: Very high disk queue lengths on data drive Trace tells us: Report queries doing table scans w/o indexes Many scheduled reports run simultaneously

44. Ways We Can Mitigate It Add covering indexes Modify existing indexes Add hard drives to the data file array Add memory to cache scanned tables Run reports serially, not all at once

45. Sample Problem #2 Metrics tell us: Page file drive queue lengths average >20 Page file use averages >1% Available memory averages less than 250mb Trace tells us: No unusual queries

46. Memory Configuration

47. Ways We Can Mitigate It Add memory and enable AWE/PAE Add memory and upgrade to 64-bit Move the app to its own server Reduce SQL’s min/max memory sizes

48. Sample Problem #3 Metric looks OK, but every 15 minutes: Long drive queues on the log file drive Page life expectancy drops near zero Network traffic jumps Trace tells us: Transaction log backups are running

49. Ways We Can Mitigate It Stop doing log backups Put the databases in simple mode Add drives to the transaction log array Throttle the transaction log backups

50. Sample Problem #4 Metrics tell us: CPU average is high Disk, memory look OK Trace tells us: Queries are using cursors Operating on individual records, not sets

51. How We Can Mitigate It Buy really fast processors Spend a lot on licensing Change cursor to set-based query

52. Wrapping Things Up Double-check the event log first Don’t get overwhelmed: focus with the Metric – Trace – Mitigation process Show a clear cause and effect Use pro tools to get an edge

53. Resources On The Web My blog about Perfmon:www.BrentOzar.com/perfmon Excel Table Analysis Tools for the Cloud:www.SQLServerDataMining.com/cloud ClearTrace: http://www.cleardata.biz/cleartrace/ SQL Server community:SQLServerPedia.com