signo hames 2011
TRANSCRIPT
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B R O U G H T T O Y O U B Y
ONYX TRAININGW W W . O N Y X T R A I N I N G . C O M
F E A T U R I N G
BRENT HAMESS I G N O I N C .
W W W . S I G N O I N C . N E T
OBIEE Performance
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Welcome
Introduction
Agenda Presentation
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ONYX Training 14 years of Learning Services Public and onsite training
Oracle and RDBMS Web Applications Development Data Warehouse & Business Intelligence Mainframe
Training format (instructor-led) Class room Remote Web Mentoring
Contact Ann Kalin at [email protected] more information or visitwww.onyxtraining
ORACLE &
RDBMS
WEB
APPLICATIONS
DEVELOPMENT
DATA
WAREHOUSE &
BUSINESS
INTELLIGENCE
MAINFRAME
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Agenda
Motivation
Historical Performance Tuning Current Performance Tuning
A Solution
Examples
Bottom Shelf
Q/A
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Motivation
Concentrate on areas of improvement you can:
Easily control / influence
Quickly implement
Obtain largest ROI
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Historical Performance Tuning
Low Level
Raw Disk Physical Servers
Dedicated Administrators
Consistent SQL
Ability to modify SQL
Team effort
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Current Performance Tuning
Localized teams
Harder to pinpoint VMs at all layers
Dynamic user-driven SQL
Federated data
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SolutionRequirements
Optimal end userperformance is criticalfor user adoption of BIreporting
Easy to POC Simple to implement
Benefit to all architecture tiers
Low cost
High Reward
Predictable
...
Reduce physical I/OAggregates!
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Aggregate Example Month Level Day Level
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AggregatesImplementation
Process Flow
Using MaterializedViews can substantiallyreduce developmenttime
Determine Reports/Queries withpoorest performance
OBI Usage Tracking
Identify aggregate trends e.g. quarterly reports, regional analysis
Create aggregate tables
Facts and dimensions being aggregated Implement aggregates into OBI
Enable OBI Aggregate Aware
Time aggregations are mostcommon
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AggregatesCosts / Considerations
Nothing is free..butthe benefits ofaggregates typicallymake it an easydecision
Disk Development time
Ownership
Synchronization
Tuning
Batch load time
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Examples
Assumptions
Preliminary analysis complete Aggregates have been created
and loaded
Base understanding of OBI Metadata (hierarchies)
Report Development
Diagnostics
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Example 1: Eliminate Time
Based on business model, many metrics are
presented and/or compared without filtering on time Same concept could be implemented for set time
ranges by having Aggregate tables contain only data
for those time ranges (e.g. last year)
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Initial report view rolls data up toAll Centers and All Time
Example 1:
Eliminate Time
There are other
aggregate opportunitiesfor this report includingAll Centers and AllCenters/All Time
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Example 1:Eliminate Time
FACTS
Before 4.8M Row Fact Table
60,000 Physical Reads
5 Sec Query Response
After
295K Row Fact Table 3681 Physical Reads
1 Sec Query Response
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Example 1:Eliminate Time
OBIImplementation
Physical Layer
Leverage copy/duplicatefunctionality to savedevelopment time
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Example 1:Eliminate Time
OBIImplementationPhysical Layer
Validate all relationshipsfor correctness. Anounce of prevention is
worth a pound of cure.
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Set appropriate logicallevels for table source.
Example 1:Eliminate Time
OBIImplementation
Business Layer
Drag physical table intobusiness layer logicalsource
Map appropriate columns.Leave columns blank thatcannot be satisfied byaggregate.
Dont forget to set levels of other data sourcesfor that logical table
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Example 1:Eliminate Time
OBIImplementation
Results
Use logging and managesessions to validateaggregates are being used
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Example 2: Monthly Rollup
A report combines metrics for 4 different time
intervals: Current Month
Year ago Month
Rolling 12 Months
All Time
A monthly aggregate was the common denominatorfor all levels used in report.
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Initial report view has data at 4different time intervals
Example 2:
Monthly Rollup
A monthly aggregate
seemed like a good firststart given that allintervals could benefit.
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Example 2:Monthly Rollup
FACTS
Before 805 Physical Reads
42Mb Transferred
5 Sec Elapsed Time
After
105 Physical Reads 7.6Mb Transferred
2 Sec Elapsed Time
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OBIImplementationPhysical Layer
Remove columns thatrepresent data at a finergrain than the aggregate(i.e. no daily or weeklycolumns in month timedim)
Example 2:Monthly Rollup
OBIImplementationPhysical Layer
Each level of timeaggregation requires atime dimension at thesame level
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Example 2:Monthly Rollup
OBIImplementationPhysical Layer
Each level of timeaggregation requires atime dimension at thesame level
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Set appropriate logicallevels for table source.
Example 2:Monthly Rollup
OBIImplementationBusiness Layer
Drag physical table intobusiness layer logicalsource
Map appropriate columns.Leave columns blank thatcannot be satisfied byaggregate.
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Set appropriate logicallevels for table source.
Example 2:Monthly Rollup
OBIImplementationBusiness Layer
Drag physical table intobusiness layer logicalsource
Map appropriate columns.Leave columns blank thatcannot be satisfied byaggregate.
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Example 2:Monthly Rollup
OBIImplementationResults
Use logging and managesessions to validateaggregates are being used
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Example 3: Subset
A report compares individual centers against a
subset of base centers No aggregation but the setup in OBI is the same
Would use OBI filter function or logical table
content filter to accomplish same results
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Report allows user to selectbetween All Center or HQ Centercomparisons (blue)
Example 3:
Subset
Using filter (i.e. where
clause) on HQ centersdid not performsufficiently.
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Example 3:Subset
FACTS
Before 1M Row Fact Table
4116 Physical Reads
6 Sec Query Response
After 368K Row Fact Table
2561 Physical Reads
3 Sec Query Response
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OBIImplementation
Physical Layer
This is a true copy. Onlythe table name needs to
be changed.
Example 3:Subset
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Example 3:Subset
OBIImplementation
Physical Layer
Exact same mappingsacross fact tables.
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Map appropriate columns.Leave columns blank thatcannot be satisfied byaggregate.
Drag physical table intobusiness layer logicalsource
Set appropriate logicallevels for table source.
Example 3:Subset
OBIImplementationBusiness Layer
The levels will be the same as the base table
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Example 3:Subset
OBIImplementationResults
Use logging and managesessions to validateaggregates are being used
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Bottom Shelf
Query Rewrite off (db)
Star Transformation on (db) Local Disk for work and temp space (obi)
Disable logical table sources (obi)
Delete Unnecessary rows from all tables (db) Support Derived Tables off (obi)