Download - Perf tuning with-multitenant
BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA
HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH
Running your production with MultitenantPerformance & Tuning challenges
Jacques KosticPrincipal Consultant IMS Lausanne
TechEvent 2016-sept-092 09/10/2016
Experience:
• Oracle DBA since 1990• High Availability and Backup & Recovery Architect• SQL and Instance Performance & Tuning• License Audit and Consolidation
Certifications:
• Oracle Certified Master 11g & 12c• Oracle 11g Performance Tuning Certified Expert• Oracle RAC 11g and Grid Infrastructure Administration• Oracle Certified SQL Expert 11g• ITIL Foundation
Teaching Courses at Trivadis:
• Oracle 11g & 12c Grid Infrastructure & RAC• Oracle 11g & 12c Data Guard• Oracle 11g & 12c Performance & Tuning• Oracle 11g & 12c Administration• SQL – PL-SQL
About me
Agenda
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1. Customer context
2. Backgrounds
3. New requirements
4. Performance challenges
5. Demo
6. Q/A
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Customer Context
Constomer Context
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The name will not be disclosed but the most relevantcharacteristics to the project are reported below.
Customer
Environment
Medium size customer from financial sector
Few databases with different workload types
Virtual Private Databases
High level of automation
Consolidation opportunities with the Multitenant Option
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Backgrounds
Backgrounds
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2013 : Initial setup
– Oracle 11.2.0.3
dNFS
6 Cores per nodes
2 Production RAC databases
DataGuard
4 Cores per nodes
2 Standby RAC databases ADG
Up to 5 test databases
Backgrounds
TechEvent 2016-sept-098 09/10/2016
2015 : First Upgrade
– Oracle 12.1.0.2 with Singletenant
dNFS
6 Cores per nodes
2 Production RAC databases
DataGuard
4 Cores per nodes
2 Standby RAC databases ADG
Up to 5 test databases
Backgrounds
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Performance challenges after migration to 12c
Execution plan changes
• Lack of data model design
• Stale statistics
Some queries with huge performance deviations
– New 12c features
• SQL Plan directives due to miss estimates
• Adaptive dynamic sampling triggered automatically when parallelism isin the game
• Some bugs…
How we fixed that?
Backgrounds
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SQL > Alter system set optimizer_adaptive_features=FALSE;
System altered.
SQL>
Et voila!
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New Requirements
New Requirements
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New customer to absorb
Double the size of all databases
Have the same performance in test environments
Same automation procedures
New Requirements
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2016 : Second Upgrade
– Oracle 12.1.0.2 with Multitenant
6 Cores per nodes
2 Production RAC databases
DataGuard
6 Cores per nodes
2 Standby RAC databases ADG
Up to 5 test databases
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Performance Challenges
Performance Challenges
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Production databases
One small OLTP database
One mix OLTP-DWH medium database
–VPD!
– Financial consolidation can be scheduled at any time by endusers
–Average execution time is within one hour
–Parallel executions are used for certain steps
Performance Challenges
TechEvent 2016-sept-0917 09/10/2016
Test databases
Can be refreshed on demand
–Directly from production
– From any backup
Performance tests before pushing changes into production
Has to be closest to production in term of resource allocation
Performance Challenges
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What have we done?
Use more SGA as the ODA X5-2 (256 GB per nodes versus 96 GB)
Remove instance caging and introduce a CDB Resource Plan
Limit the PGA by setting pga_aggregate_limit parameter
Performance Challenges
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Adjust statistics collection methods
Relocate some tablespaces
Optimize Undo for temporary tables by settingTEMP_UNDO_ENABLED parameter
Setup Result Cache
Fine tune some queries
Performance Challenges
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Result after few days
Customer was happy, jobs are running 55% faster
Refreshes from production are completed 40% faster
Performance in test environment is becoming comparable toproduction
General end user perception was good!
Performance Challenges
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After one week, a big mess!
Production Instance was very slow
Several jobs where running into the two PDBs
Massive database waits: free buffer waits!!
Performance Challenges
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Possible causes:
The I/O system is slow.
Waiting for resources, such latches.
The buffer cache is so small and DBWR spends most of it's time cleaning out buffers for server processes.
The buffer cache is so big and they are not enough DBWR processes to free enough buffers in the cache to satisfy requests.
Performance Challenges
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Limitations with Multitenant
Shared pool
Buffer cache
I/O activity
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Demo
Jacques Kostic
Principal Consultant IMS Lausanne
Tel. +41 79 909 72 63
09/10/2016 TechEvent 2016-sept-0925
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