1. Extreme Performance for DBAs מאיר דודאי| SQL Server MVP| ואלינור

2. All transaction isolation level Differences between Serializeable and Repateable Read RangeX-S locking vsRangeX-U Deep dive into bookmark lookup Page internals Indexes on Sparse columns

3. All transaction isolation level Differences between Serializeable and Repateable Read RangeX-S locking vsRangeX-U Deep dive into bookmark lookup Page internals Indexes on Sparse columns

4. לפני קצת יותר מ-10 שנים...

5. לפני קצת יותר מ-10 שנים...

6. לפני קצת יותר מ-10 שנים...

7. מטרות היכרות עם תהליך P&T כלים חדשים ולא מוכרים לניהול Performance הבנת יישום נכון של Compression היכרות עם יכולות Scale out בגירסאות הנוכחיות וב-Denali

8. מי אני? מאיר דודאי: SQL Server MVP יועץ בתחום בסיסי נתונים ניסיון של למעלה מ-10 שנים ב-SQL Server עורך האתר:

9. ואלינור החברה המובילה בישראל במתן שירותים מקצועיים בתחום בסיסי נתונים: SQL Server, Oracle, MySQL צוות יועצים מוביל המתמחה בכלל הרבדים שלבסיסי הנתונים שותפים של Microsoft ו- Oracle נציגי מוצרים מובילים בתחום ה-DB מעל 300 לקוחות בכל המגזרים

10. My Assumptions About You You may be a part-time or full-time DBA You are familiar with SQL Server in previous versions You would like to learn about new features in SQL Server 2008&R2&2011 that can help you to manage and improve performance You are interested in good lunch, two days free from work, and some giveaways from advertisers

14. ארגז הכלים החדש שלכם

16. Detecting bottlenecks

17. New Performance Monitor in Windows 2008/R2

19. Detecting bottlenecks

20. New Performance Monitor in Windows 2008/R2

22. Having fun with deployment

24. Data-tier Application Component

25. Improves collaboration between developer and DBA

26. Moves developers from a procedural model to a declarative model

27. V1 is targeted at small appsSchema LOGICAL Tables, Views, Procs, UDFs PHYSICAL Users, Logins, Indexes DAC Deployment Profile Deployment Requirements, Management Policies

29. Shows health of

30. SQL Server instances

31. Data-tier applications

32. Database files, filegroups and volumes

33. Provides resource monitoring

34. CPU utilization

35. Storage spaceSQL02 SQL01 SQL03 SQL05 SQL04 DBA UCP Managed Instances Management Studio

36. DEVELOP DEPLOY MANAGE SQL Server Management Studio FinApp Dev DB 1 Deploy / Upgrade DAC Reverse Engineer DAC 2 SQL Server Management Studio 9 4 8 Visual Studio 2010 Manage, Register, Uninstall, Extract, Upgrade DAC Control Point Create policies DBA DBA 7 3 Deploy / Upgrade DAC HR .dacpac Hand-off to DBA Compile + Build FinApp Prod DB 6 Developer SALES 5 Managed Instances

37. Utility Control Point

38. UCP

39. UCP

40. UCP Reports

41. UCP Reports http://bit.ly/j8xMwH

42. UCP Reports

43. What’s missing? Supports only SQL Server 2008 R2 (or later) Better management More counters can be useful… Monitors only DAC Or is it?

44. Fake DAC

45. What’s next? Denali’s Contained Databases…

47. Detecting bottlenecks

48. New Performance Monitor in Windows 2008/R2

50. SSMS Activity Monitor

51. Performance Reports

52. Using Profiler to Detect Blocks

53. Clear Trace & Trace Analyzer

55. Detecting bottlenecks

56. New Performance Monitor in Windows 2008/R2

58. Performance & Resource Monitor

59. New performance counters Database Mirroring Compression stats Transactions volume Mirroring performance Custom counters

60. Custom counters

62. Detecting bottlenecks

63. New Performance Monitor in Windows 2008/R2

65. OS perf indicators

66. Performance data

67. Extensible collection

68. Central repository

69. Consolidate information

70. Open interface

71. Management reports

72. Canned reports

74. Agenda Magic settings RCSI Partition-level lock escalation Architectural design Bulk Load StreamInsight Caching Offloading Traffic Denali HADR

75. GreenRoad Case Study:RCSI GreenRoad is an Israeli startup improving driving behavior for fleets and consumers Works as SAAS More than 400 inserts/sec Users running queries and reports frequently Method used to increase concurrency: RCSI: Read Committed Snapshot Isolation

76. Tran2 (Select) Tran1 (Update) Reader Writer Blocking Data Page S-Lock Blocked Row-1 Row-1 X-Lock

77. Read Committed Snapshot New “flavor” of read committed Turn ON/OFF on a database Readers see committed values as of beginning of statement Writers do not block Readers Readers do not block Writers Writers do block writers Can greatly reduce locking / deadlocking without changing applications

78. Demo

79. Lock Escalation HOBT T1: IX T1: X Page Page Page T1: X T1: X T1: X T1: X T1: X Row Row Row T1: X T1: X T1: X Lock Escalation T1: IX

80. Lock Escalation Converting finer-grain locks to coarse grain locks. Row to Table Page to Table. Benefits Reduced locking overhead Reduces Memory requirement Triggered when Number of locks acquired on a rowset > 5000 Memory pressure

81. Partitioned Tables and Indexes SQL Server 2005 introduced partitioning, which some customers use to scale a query workload Another common use is to streamline maintenance and enable fast range inserts and removals from tables Partitioned Table FG1 FG2 FG3 Partition 2 Partition 3 Partition 1

82. Lock Escalation: The Problem Lock escalation on partitioned tables reduces concurrency as the table lock locks ALL partitions Only way to solve this in SQL Server 2005 is to disable lock escalation Query 1 Query 2 Partitioned Table IX X ESCALATE update update Partition 2 Partition 1 Partition 3 FG1 FG2 FG3

83. Lock Escalation: The Solution SQL Server 2008 allows lock escalation to the partition level, allowing concurrent access to other partitions Escalation to partition level does not block queries on other partitions Query 1 Query 2 Partitioned Table IX ESCALATE update update X Partition 2 Partition 1 Partition 3 FG1 FG2 FG3

84. Demo

85. Filtered Indexes An index with a WHERE clause to specify a criteria Essentially index only a subset of a the table Query optimizer most likely to use when WHERE clause matches that of the filtered index

86. Using Filtered Indexes Advantages of Filtered Indexes Improve query performance, partly by enhancing execution plan quality Smaller index maintenance costs Less disk storage

87. Using Filtered Indexes Scenarios for Filtered Indexes Sparse columns, where most data is null Columns with categories of values Columns with distinct ranges of values

88. Filtered indexes

89. New server option in SQL Server 2008 Only a stub is cached on first execution Full plan cached after second execution SP_CONFIGURE 'show advanced options',1RECONFIGUREGO SP_CONFIGURE 'optimize for ad hoc workloads',1RECONFIGUREGO Optimize for ad hoc workloads

90. “I would not use it on some DWH systems” “Why is this not on by default?” “I can’t think of a reason why opt for adhoc workloads would ever really be a problem” “I definitely recommend it!” “Best movie of 2011! Breathtaking!” “But paintball guns are also not very pleasant!” How good is it?

91. Codename Lyngby Case Study: Power of bulk inserts Security/audit system 50GB of data inserted daily Data is kept for one year and should be available for queries and reports at any time Method used to increase concurrency: Bulk inserts

92. Benefits of Bulk Inserts Improved concurrency Allow application-database decoupling In Lyngby case – 50GB a day! http://www.tapuz.co.il/blog/userBlog.asp?FolderName=Hygge

93. Bulk Inserts & RCSI: SQLCAT Benchmark What happens when you query a table while bulk inserts are running?

94. Bulk Inserts & RCSI: SQLCAT Benchmark And with RCSI? Bulk loading does not affect the size of the version store in tempdb under RCSI Keep in mind: RCSI adds 14 noncompressible bytes into every row in every table Bottom line: RCSI works extremely well with bulk inserts and achieves improved concurrency More details about this benchmark: http://sqlcat.com/technicalnotes/archive/2009/04/06/bulk-loading-data-into-a-table-with-concurrent-queries.aspx

95. StreamInsight:Complex Event Processing SQL Server 2008 R2 feature Processing and querying of event data streams Data queried while “in flight” May involve multiple concurrent event sources Works with high data rates Aims for near-zero latency

96. Isn’t This Just a Database Application? Event request output stream input stream response

97. Caching Your database can get some rest...

98. Microsoft AppFabric

99. Other solutions Memcache Requires application change 3rd party Usually transparent

100. Tapuz Case Study: Offloading Traffic Tapuz is the leading user content based website in Israel 1,200 forums 74,000 blogs 500,000 visitors each month More than 4000 queries/sec Method used to increase concurrency: Offloading using Transactional Replication

101. Compression

103. Storage Cost

104. Workload Performance

105. Manageability Cost

107. Solution – SQL Server 2008 / R2 Store data efficiently in the row/page (+) More data can fit in memory (+) Better Performance for I/O bound workload (-) Performance degradation for CPU bound workload

108. Data Compression SQL Server 2008 ROW and PAGE compression Backup Compression SQL Server 2008 R2 Unicode compression

109. Enabling Compression Examples Latest partition uncompressed Uncompressed PAGE Compressed ROW Compressed Jan-Mar Apr-June July-Sept Oct-Dec

110. Should it be so complex? In real life – usually compress the entire large tables using page compression…

111. Summary – Compression Can reduce size of database significantly Lower total cost of ownership (TCO) Easy to enable/disable No application changes Performance gains!

112. Control Your Resources

113. Resource Hogs What are some of the biggest resource hogs a DBA runs into? Bulk Load Processes Data Archiving Poorly Coded Queries (Runaways) Reporting…

114. Reporting in Production Is this a best practice???

115. Reporting In Production NO!

116. Reporting In Production NOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO

117. Reporting In Production OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO!

118. Resource Governor Similar to a governor you would find on a car It limits the “speed” that a SQL Server session can run at

119. Resource Governor – Workloads Ability to differentiate workloads based on connection property e.g. app_name, login, user, db name Per-request limits Max memory % Max CPU time Grant timeout Max Requests