Advanced ASE Performance Tuning Tips

1

Advanced ASE Performance Tuning Tips

Janis Griffin

Senior DBA / Performance Evangelist

2© 2015 SOLARWINDS

Who Am I?

» Senior DBA / Performance Evangelist for Solarwinds§ [email protected] § Twitter - @DoBoutAnything§ Current – 25+ Years in Oracle, Sybase, SQL Server§ DBA and Developer

» Specialize in Performance Tuning» Review Database Performance for Customers and

Prospects» Common Thread – Paralyzed by Tuning

mailto:[email protected]

3© 2015 SOLARWINDS

Before we start, do you know…

» The most important problem in your database instance?»

» If that new program is hurting database performance?»

» Did that recent fix really solved the database issue?»

» Which bottlenecks in your database directly impacted end-user service?

»

4© 2015 SOLARWINDS

Agenda - 4 Tips

» Focus on Tuning Queries

» Utilize Response Time Analysis (RTA)

» Examine Query Execution Plans

» Use SQL or Query Diagramming§ Who registered yesterday for Tuning Class§ Check order status§ Current paychecks for specific employees§

5© 2015 SOLARWINDS

Why Focus on Queries

» Most Applications§ Read and Write data to/from database§ Simple manipulation of data§ Deal with smaller amounts of data

» Most Databases§ Examine larger amounts of data, return a little§ Inefficiencies quickly become bottleneck

» Why do SQL tuning?§ “Gives the biggest bang for your buck”§ Changes to SQL are Safer§ Most of performance issues are SQL related

6© 2015 SOLARWINDS

Challenges Of Tuning

» SQL Tuning is Hard § Who should tune – DBA or Developer§ Which SQL to tune§

» Requires Expertise in Many Areas§ Technical – Plan, Data Access, SQL Design§ Business – What is the Purpose of SQL?§

» Tuning Takes Time§ Large Number of SQL Statements§ Each Statement is Different§

» Low Priority in Some Companies§ Vendor Applications§ Focus on Hardware or System Issues§

» Never Ending

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Which SQL to Tune

Methods for Identifying

» User / Batch Job Complaints§ Known Poorly Performing SQL§ Trace Session/Process§

» Queries Performing Most I/O (LIO / PIO)§ Table or Index Scans

» Queries Consuming CPU

» Highest Response Times - DPA (formally Ignite)

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Response Time Analysis (RTA)

§Understand the total t ime a Query spends in Database§Measure t ime while Query executes§SAP ASE helps by providing Wait Events

Focus on Response Time

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Wait Time Tables (ASE 12.5.0.3+)

http://froebe.net/blog/wp-content/uploads/2013/09/ASE-15.7-Monitoring-Tables-Diagram-Sybase-Inc_.pdf

http://froebe.net/blog/wp-content/uploads/2013/09/ASE-15.7-Monitoring-Tables-Diagram-Sybase-Inc_.pdf

10© 2015 SOLARWINDS

Response Time Query

» MDA Query Example

SELECT mP.Login, mP.DBName, mPL.ClientHost, RTRIM(mPL.Application), mPP.ObjectName, mP.WaitEventID, mPS.SQLText, mPS.BatchID, mPS.LineNumber, mP.LineNumber CurrentLineNumberFROM monProcessSQLText mPS, monProcessLookup mPL, (monProcess mPLEFT OUTER JOIN monProcessProcedures mPP ON mP.SPID=mPP.SPID AND mP.KPID=mPP.KPID)WHERE mP.SPID=mPL.SPID AND mP.KPID=mPL.KPIDAND mP.SPID=mPS.SPID AND mP.KPID=mPS.KPIDAND coalesce(mP.FamilyID,0) = 0 AND mP.BatchID > 0


Top Wait Events At Server Level

select WaitEventID, convert(numeric(16,0),Waits) as "Waits", convert(numeric(16,0),WaitTime) as "WaitTime" into #waits1 from monSysWaitsgoselect Description, convert(int,sum(w.Waits)) as "Count", convert(int,sum(w.WaitTime)/1000) as "Seconds" from #waits1 w, monWaitEventInfo ei where w.WaitEventID = ei.WaitEventID group by Description order by 3 desc


RTA – Proactive

Refreshed on :08/12/14 02:35:18 PM


Users Complain: 10am – 12pm Slow

Top 15 SQL Statements | GIBSON:5000 | August 8, 2014 to August 12, 2014Daily Time Range: 10:00 AM-12:00 PM


RTA – Firefighting

Day: Tuesday – August 10,2014 Refreshed on: 08/12/2014 05:09:57 PM


RTA - Blocking Issue

Day: Tuesday – August 10,2014 Refreshed on: 08/12/2014 05:02:02

SQL Statements Executed by Blocking Session 125 while Holding the Lock | GIBSON:5000August 10, 2014 – 12:00PM to 4:00PM


RTA – Long Term Trends

Top 15 SQL Statements | GIBSON:5000 | July 31,2014 to August 24, 2014


RTA – Current Problem

Refreshed on: 08/12/2014 05:34:42 PM


RTA – Current Problem

Refreshed on: 08/12/2014 05:39:06 PM


Identify End-to-END Time

Accurate End-to-End Response Time Analysis


Get Table & COLUMN Info

» Understand objects in execution plans§ Table Definitions & Segment sizes

• Is it a View – get underlying definition• Number of Rows / Partitioning

§ Examine Columns in Where Clause• Cardinality of columns • Data Skew / Histograms

§

§ Statistic Gathering • Tip: Out-of-date statistics can impact performance

» Understand expensive data access targets§ TableScans versus IndexScans§

» Know the indexes – if multi-column, order is important


Get The Execution Plan

» SET SHOWPLAN ON § set statistics io, time on

simulate, subquerycache, plancost

§ set noexec on http://help.sap.com/Download/Multimedia/ASE_16.0/ptstats.pdf

» Interactive SQL (Sybase iAnyWhere or SAP dbisql) § Plan Viewer– must execute query§ Details, XML & Advanced (abstract & missing)

» Abstract Plans-sysqueryplans /sysquerymetrics§ sp_configure'enable metrics capture', 1

» Application Tracing (v15.0.2+)§ set tracefile "<file-path>" for <spid>§ Works when you know a problem will occur

http://help.sap.com/Download/Multimedia/ASE_16.0/ptstats.pdf


Get The Execution Plan - tracing

set statistics plancost onset tracefile ’/db1/trc/trc32.tx’ for 32

© 2015 SOLARWINDS

Examine the Execution Plan

» Find Expensive Operators§ Examine cost of each step§ Look for full table or index scans

» Review the ‘restrict’ & ‘sort’ operators§ Are the ‘restrict’ steps early in plan? § Large sorts that don’t fit into memory§ Look for Implicit conversions when using parmeters

» Review JOIN operators§ Nested loop

• effective when there is a useful index available§ Merge Join

• good when most of the rows must be processed and they are already sorted by join keys

§ Hash Join• good when most of the rows from source sets are processed

§ Nary Nested Loop • More efficient when you have more than 2 nested loops

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Engineer out the Stupid

» Look for Performance Inhibitors

§ Cursor or row by row processing

§ Parallel processing - OLAP vs OLTP§

§ Hard-coded Hints§

§ Nested views that use link servers

§ Abuse of Wild Cards (*) or No Where Clause§

§ Code-based SQL Generators (e.g. Hibernate)§

§ Non-SARG-able / Scalar Functions• Select… where upper(first_name) = ‘JANIS’

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Execution Plan Example


» Who registered yesterday for SQL Tuning

SELECT s.FNAME, s.LNAME, r.SIGNUP_DATEFROM STUDENT s INNER JOIN REGISTRATION r ON s.STUDENT_ID =

r.STUDENT_IDINNER JOIN CLASS c ON r.CLASS_ID = c.CLASS_IDWHERE c.NAME = 'SQL TUNING'AND r.SIGNUP_DATE BETWEEN @BegDate AND

@EndDateAND r.CANCELLED = 'N‘

Case Study 1


Relationship Diagram for Tables in Query


Execution Plan


SQL Diagramming

» Great Book “SQL Tuning” by Dan Tow§ Great book that teaches SQL Diagramming§ http://www.singingsql.com

REGISTRATION

STUDENT CLASS

5

1

30

1

.05

.002

select count(1) from registration where cancelled = 'N'and signup_date between '2015-01-29 00:00' and '2015-01-30 00:00'

4,141 / 79,999 = 0.05

select count(1) from class where name = 'SQL TUNING'

2 / 1,000 = .002


create index cl_name ON CLASS(NAME)

New Execution Plan

Why would an TableScan still occur on REGISTRATION?


Database Diagram


create index reg_alt on REGISTRATION(CLASS_ID)

New Execution Plan


create index reg_alt ON REGISTRATION (CLASS_ID, SIGNUP_DATE,CANCELLED)

Better Execution Plan


» Lookup Shipment Status for caller

SELECT o.OrderID, c.FirstName, c.LastName, p.ProductID, p.Description, s.ActualShipDate, s.ShipStatus, s.ExpectedShipDateFROM SalesOrder oINNER JOIN OrderItem i ON i.OrderID = o.OrderIDINNER JOIN Customer c ON c.CustomerID = o.CustomerIDINNER JOIN Shipment s ON s.ShipmentID = i.ShipmentIDLEFT OUTER JOIN Product p ON p.ProductID = i.ProductIDLEFT OUTER JOIN Address a ON a.AddressID = s.AddressIDWHERE c.LastName LIKE ISNULL('Griffin','') + '%'AND o.OrderDate >= DATEADD(day, -30,getdate())AND s.ShipStatus <> 'C'order by LastName

Case Study 2


Database Diagram


Execution Plan


SQL Diagramming

o .02

.005

SELECT COUNT(1)*1.0/(SELECT COUNT(1) FROM Customer) FROM Customer WHERE LastName LIKE 'Griffin%'0.005

SELECT COUNT(1)*1.0/(SELECT COUNT(1) FROM [SalesOrder]) FROM [SalesOrder] WHERE OrderDate >= DATEADD(day, -30, GETDATE()).02

SELECT COUNT(1)*1.0/(SELECT COUNT(1) FROM [Shipment]) FROM [Shipment] WHERE ShipStatus <> 'C'.04

i c

ps

a

.04


New Execution Plan

» CREATE INDEX CUST_LASTNAME ON Customer(LastName)

»


SQL Diagramming

o .02

.005




i c

ps

a

.04


CREATE INDEX SALESORDER_ODATE ON SalesOrder (OrderDate)

New Execution Plan


SQL Diagramming

o .02

.005




i c

ps

a

.04


Data Skew Problems

» Only 4% of rows are <> ‘C’» How about changing the query?

§ AND s.ShipStatus = 'I'

» Add Histogram on ShipStatus

SELECT ShipStatus, COUNT(1)CntFROM [Shipment]GROUP BY ShipStatus


UPDATE STATISTICS example.dbo.Shipment (ShipStatus)go

New Execution Plan


Case Study 3

» Current paychecks for specific employees

SELECT e.empno, e.first_name, e.last_name, d.dname,l.street_address,l.city, l.state_province, l.postal_code FROM emp e INNER JOIN dept d ON e.deptno = d.deptno INNER JOIN loc l ON d.location_id = l.location_id WHERE (e.first_name = @first or e.last_name = @last) AND EXISTS ( SELECT 1 FROM wage_pmt w WHERE w.empno = e.empno AND w.pay_date>= DATEADD(day,-31,GETDATE()) )

» Execution Stats – 6681 Logical I/O» Average Execution - 15.012 seconds» Resource - 99% CPU


Execution Plan


SQL Diagramming

select count(1) from wage_pmtwhere pay_date >= DATEADD(day,-31,GETDATE())

109568 / 1027192 = .106

select max(cnt), min(cnt) from (select last_name, count(1) cnt from emp group by last_name)

128 / 6848 = .018 – max64 /= 6848 = .009 – min

emp

dept

wage_pmt

1000

1

150

1

.02

.10

loc1

9

.009


New Execution Plan

» create index IX_EMP_LN on emp(last_name)» Create index IX_EMP_FN on emp(first_name


Wage_Pmt table – no index on empno


Better Execution Plan

» create index IX_WAGE_EMPNO on wage_pmt(empno)»

»

»

»

»

»

»

»

»

»

»

Execution time = 0.546 seconds


Best execution Plan

Covered Index:create index IX_EMP on emp(empno, last_name, first_name, deptno)

Time: 0.066 secs


Monitor

» Monitor the improvement§ Be able to prove that tuning made a difference§ Take new metric measurements§ Compare them to initial readings§ Brag about the improvements – no one else will

» Monitor for next tuning opportunity§ Tuning is iterative§ There is always room for improvement§ Make sure you tune things that make a difference

» Shameless Product Pitch - DPA


Improved Performance

Average Wait Time per Execution for SQL Statement Current Paychecks by Name | GIBSON:5000 March 15, 2015

Daily Time Range: 5:00 PM-12:00 AM

Logical Reads = 1198 Execution Time = .066 seconds

© 2015 SOLARWINDS

Takeaway Points

» Tuning Queries gives more “bang for the buck”» Make sure you are tuning the correct query» Use Wait Events and Response Time Analysis

§ Locking problems may not be a Query Tuning issue§ Wait Events tell you where to start

» Use “Execution or Query Plans”» SQL Diagramming - “Get it right the First Time”

§ Query Tuner Tools can mislead you

» Monitor for next tuning opportunity

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Advanced ASE Performance Tuning Tips