Common mistakes developers make in SQL Server Amateurs work until they get it right. Professionals work until they can't get it wrong.

Transcription

1 Common mistakes developers make in SQL Server Amateurs work until they get it right. Professionals work until they can't get it wrong.

2 Who am I? Self-employed 6 years, Visual Basic 3.0 to 6.0, Access 1.0 to 95. Long time consultant 15 years, Visual Basic 6.0, SQL Server 4.21 to 2008R2. Employed 3 years, SQL Server 2000 to 2008R2 and Denali (2011?). MVP Microsoft Valuable Professional SQL Server since Active on several forums as Peso, SwePeso or Pesomannen msdn.microsoft.com

3 Agenda Faster hardware Row By Agonizing Row (pronounced Ree-bar) Bad indexing Index misuse Triggers Indeterministic functions

4 Before we start Before you make any change on a production SQL Server, be sure you test it first in a test environment NO EXCEPTIONS! I mean it! Really! No kidding Iwouldn t lie to you You d be crazy not listening to this advice Never forget, DBAs and developers are the protectors of the organization s data You took this oath when you accepted the job

5 The golden bullet FASTER HARDWARE

6 Faster hardware You can throw faster hardware at a problem if you want but don't be surprised if it doesn't actually help much. True performance can only be found in the code and the design of the database. Let's stop and think about faster hardware to do the same thing Let's say the CPU speed and disk throughput is doubled. That would mean a 2 hour query might drop to 1 hour. Rewriting the old code could drop the query time to 3seconds.

7 Faster hardware More cores mean more queries can request massive numbers of locks simultaneously and the badly written queries need many locks that may cause performance to deteriorate under faster hardware. SQL Server spends more time waiting and less time working.

8 Faster hardware

9 Faster hardware

10 Faster hardware

11 Faster hardware

12 Faster hardware

13 Faster hardware

14 Faster hardware Query Index Parallellism Reads CPU Duration Old query No No 1,805, Old query No Yes 1,845, Old query Yes No 59, Old query Yes Yes 59, New query No No New query Yes No

15 Loops, cursors and triangular joins ROW BY AGONIZING ROW

16 Row By Agonizing Row Phrased by Jeff Moden Good friend and fellow SQL Server MVP from SQLServerCentral. Learn to recognize Triangular Joins They appear in the SELECT list as correlated subqueriesusually with a stand-alone inequality of some sort They can also appear in WHERE clauses with the same type of standalone inequality. Not all Triangular Joins are bad With some restraint and the right criteria, Triangular Joins can be used for some pretty remarkable things Make finite schedules Do high speed dupe checks But, you've really got to be careful. Improperly written Triangular Joins are worse than Cursors or While Loops and can bring a CPU and Disk System right to it's knees. Watch out for "Hidden RBAR"

17 Row By Agonizing Row Many folks think that set-based programming means one of two things It simply doesn't have a Cursor or a While Loop. It's all done in a single query. Both of those are very bad misconceptions as to what set based programming is Touch each row of data only once if you can and as few times as possible if you can't. A loop (cursor) Works row-by-agonizing-row. Overrides the natural abilities of the optimizer. Only operates on a single row instead of a set of rows. Most explicit loops are not set based programming and they just crush performance.

18 Row By Agonizing Row Cursor-based solution Set-based solution

19 Row By Agonizing Row SELECT a.rownum AS RowNum_A, b.rownum AS RowNum_B FROM TableA AS a, TableB AS b WHERE a.rownum <= b.rownum

20 Row By Agonizing Row Good examples from the Phil Factor Speed Phreak competitions Cursor 780 seconds (13 minutes). Set-based 0.3 seconds - 2,500 times faster! Cursor 2,400 seconds (40 minutes). Set-based 1.3 seconds 1,800 times faster! Cursor 4,000 4,500 seconds (70-75 minutes). Set-based 0.5 seconds 9,000 times faster! SQLCLR 0.4 seconds 11,000 times faster!

21 Row By Agonizing Row Kathi Kellenberger, former SQL Server MVP, provides in-depth descriptions and analyses of the different solutions here

22 The hidden performance crusher BAD INDEXING

23 Bad Indexing SELECT ent.entengagementid,thd.thdplaceofsale,count(*) FROM dbo.engagement ent INNER LOOP JOIN dbo.transactionhead thd ON thd.entengagementid = ent.entengagementid INNER JOIN dbo.engagementparameter epr ON epr.teptypeengagementparameterid = (SELECT teptypeengagementparameterid FROM TypeEngagementParameter WHERE tepcode = 'StorePeriodLen') AND DATEDIFF(MM, DATEADD(MM, -CONVERT(INT,eprParameterValue), GETDATE()), thd.thdtransactiondate) > 0 AND epr.tettypeengagementid = ent.tettypeengagementid INNER JOIN dbo.typetransactionhead tth ON tth.tthtypetransactionheadid = thd.tthtypetransactionheadid AND tth.tthcode IN ('Purchase', 'Return', 'Mixed') GROUP BY ent.entengagementid,thdplaceofsale

24 Bad Indexing

25 Bad Indexing SELECT ent.entengagementid, thd.thdplaceofsale, COUNT(*) FROM dbo.typeengagementparameter AS tep INNER JOIN dbo.engagementparameter AS epr ON epr.teptypeengagementparameterid = tep.teptypeengagementparameterid INNER JOIN dbo.engagement AS ent ON ent.tettypeengagementid = epr.tettypeengagementid INNER JOIN dbo.transactionhead AS thd ON thd.entengagementid = ent.entengagementid INNER JOIN dbo.typetransactionhead AS tth ON tth.tthtypetransactionheadid = thd.tthtypetransactionheadid AND tth.tthcode IN ('Purchase', 'Return', 'Mixed') WHERE thd.thdtransactiondate >= DATEADD(MONTH, DATEDIFF(MONTH, ' ', GETDATE()) - CONVERT(INT, epr.eprparametervalue), ' ') AND tep.tepcode = 'StorePeriodLen' GROUP BY ent.entengagementid, thdplaceofsale

26 Bad Indexing

27 Bad Indexing

28 Bad Indexing

29 O Index, Where Art Thou? INDEX MISUSE

30 Index misuse -- Query 1 SELECT * FROM dbo.testindexes WHERE YEAR(MyDate) = Query 2 SELECT * FROM dbo.testindexes WHERE MyDate >= ' ' AND MyDate < ' ' -- Query 3 SELECT * FROM dbo.testindexes WHERE CONVERT(CHAR(4), MyDate, 112) = '2005'

31 Index misuse

32 Index misuse

33 Index misuse

34 Index misuse

35 Index misuse Query Records Scan Count Logical Reads CPU Duration Query 1 1, Query 2 1, Query 3 1, Query 1 10, Query 2 10, Query 3 10, Query 1 100, Query 2 100, Query 3 100, Query 1 1,000, , Query 2 1,000, Query 3 1,000, , Query 1 10,000, ,679 3, Query 2 10,000, Query 3 10,000, ,679 10,

36 To batch or not to batch? TRIGGERS

37 Triggers Create TRIGGER [dbo].[fault_parked_update] ON [dbo].[detail] FOR INSERT, UPDATE AS INT datetime FROM inserted WHERE isdate(faultstart)=1 and isdate(faultend)=1 IS NOT NULL Begin = CASE WHEN ISDATE(@Park1Start)= 1 THEN Cast([ParkedDate1]+' '+[ParkedTime1] as datetime) ELSE CAST(' :00:00' as DateTime) END from detail Where callid = CASE WHEN ISDATE(@Park1End)= 1 THEN Cast([UnParkedDate1]+' '+[UnParkedTime1] as datetime) ELSE CAST(' :00:00' as DateTime) END from detail Where callid = datediff(ss,@park1start,@park1end)/60 = Cast([FaultStart]+' '+[FaultStartTime] as datetime) from detail Where callid = Cast([FaultEnd]+' '+[FaultEndTime] as datetime) from detail Where callid = datediff(ss,@faultstart,@faultend)/60 UPDATE CallLog set Park1 TotalParkedTime FaultMinusParked FaultTotal Where calllog.callid END

38 Triggers CREATE TRIGGER dbo.fault_parked_update ON dbo.detail FOR INSERT, UPDATE AS ;WITH ctevalid(callid, Park1, FaultTotal) AS ( SELECT CallID, CASE WHEN Park1End > Park1Start AND ISDATE(ParkedDate1) = 1 THEN DATEDIFF(SECOND, Park1Start, Park1End) / 60 ELSE 0 END AS Park1, DATEDIFF(SECOND, FaultStart, FaultEnd) / 60 AS FaultTotal FROM ( SELECT CallID, ParkedDate1, CAST(ParkedDate1 + ' ' + ParkedTime1 AS DATETIME) AS Park1Start, CAST(UnParkedDate1 + ' ' + UnParkedTime1 AS DATETIME) AS Park1End, CAST(FaultStart + ' ' + FaultStartTime AS DATETIME) AS FaultStart, CAST(FaultEnd + ' ' + FaultEndTime AS DATETIME) AS FaultEnd FROM inserted WHERE ISDATE(FaultStart) = 1 AND ISDATE(FaultEnd) = 1 AS d ) UPDATE cl SET cl.park1 = v.park1, cl.totalparkedtime = v.park1, cl.faultminusparked = v.faulttotal - v.park1, cl.faulttotal = v.faulttotal FROM dbo.calllog AS cl INNER JOIN ctevalid AS v ON v.callid = cl.callid

39 I didn t see that coming INDETERMINISTIC FUNCTIONS

40 Simple indeterministic function select top(10) case abs(checksum(newid()))%4 when 0 then 0 when 1 then 1 when 2 then 2 when 3 then 3 end from sys.objects CASE WHEN abs(checksum(newid())) % 4 = 0 THEN 0 ELSE WHEN abs(checksum(newid())) % 4 = 1 THEN 1 ELSE WHEN abs(checksum(newid())) % 4 = 2 THEN 2 ELSE WHEN abs(checksum(newid())) % 4 = 3 THEN 3 ELSE NULL END END END END

41 Advanced indeterministic function CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 1 THEN 'Jan' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 2 THEN 'Feb' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 3 THEN 'Mar' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 4 THEN 'Apr' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 5 THEN 'May' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 6 THEN 'Jun' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 7 THEN 'Jul' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 8 THEN 'Aug' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 9 THEN 'Sept' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 10 THEN 'Oct' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 11 THEN 'Nov' ELSE CASE WHEN datepart(month, dbo.fngetorderdate(salesorderid)) = 12 THEN 'Dec' ELSE NULL END END END END END END END END END END END END

42 Want to know more? Married with children 6 year girl, 3 year girl and 1 year boy. One girl to be born on May 11. Live outside Helsingborg Blog at Homepage and contact peso@developerworkshop.net Co-founder of PASS Scania Now part of SQLUG Phil Factor Speed Phreak challenges 3 time winner Another presentation Execution Plan basics