KScope14 - Real-Time Data Warehouse Upgrade - Success Stories

www.rittmanmead.com inquiries@rittmanmead.com @rittmanmead
Real-Time Data Warehouse
Upgrade - Success Stories
Nick Hurt - IFPI
Michael Rainey - Rittman Mead
KScope 2014 - Seattle, WA

Introduction
•Michael Rainey (Rittman Mead)
‣Principal Consultant
‣Oracle Data Integration expert
-GoldenGate and Oracle Data Integrator
‣Oracle ACE @mRainey

T : +44 (0) 1273 911 268 (UK) or (888) 631-1410 (USA) or  
+61 3 9596 7186 (Australia & New Zealand) or +91 997 256 7970 (India)
E : info@rittmanmead.com
W : www.rittmanmead.com
About Rittman Mead
• Oracle Gold partner with offices in US
(Atlanta), Europe, Australia, India and
South Africa
• World leading specialist partner for
technical excellence, solutions delivery
and innovation in Oracle BI
• Provide consulting, training, global
managed services for customers around
the world
• 120+ consultants including 1 Oracle
ACE Director, 3 Oracle ACEs and 1
Oracle ACE Associate
• All expert in Oracle BI, DW, EPM and
Analytics tech
• Skills in broad range of supporting
Oracle tools: OBIEE, OBIA, ODIEE,
Essbase, Oracle OLAP, GoldenGate,
Exadata, Endeca
• Blog : http://www.rittmanmead.com/blog/
• Twitter : @rittmanmead

Introduction
•Nick Hurt (IFPI)
‣Solutions Developer at IFPI - using Oracle since 2002
@nicholas_hurt
•IFPI = International Federation of Photographic Industries
‣represents the interests of recording industry worldwide
‣green light for OBIEE in 2010
‣required “near” real-time anti-piracy analytics
‣joined in 2011 to work on delivery

Agenda
•IFPI data - the good, the challenging, the ugly
•Pre-upgrade
‣Environment
‣Challenges
•Overview of GoldenGate and Oracle Data Integrator
•Upgrade - planning, migration steps
•Post-upgrade results
•Closing remarks on real-time warehousing

Challenges of IFPI data

•The good
‣Seek & destroy infringing URLs

•The good
•The challenging
‣Velocity - 1 mil+ upserts per day
‣Volatility depth - indefinite retrospective updates
‣Large wide product dimension - 12 million rows

•The good
•The challenging
‣Velocity - 1 mil+ upserts per day
‣Volatility depth - indefinite retrospective updates
‣Large wide product dimension - 12 million rows
•The ugly
‣Multiple redundant updates
‣Back-dated corrections
‣Multiple sources of information (data consistency & quality)
-heavy data cleansing - identifying duplicates
-inconsistencies (error-tolerant/error-correction ETL)

Link Lifecycle
Time
Infringing
URL Detected
t0
Link Found
Primary event

Link Lifecycle
Time
Deleted /
Matching
t0+tn
Link Correction
Optional events
Infringing
URL Detected
t0
Link Found
Primary event

Link Lifecycle
Time
Deleted /
Matching
t0+tn
Link Correction
Cease
& Desist
t1 = t0+tn
Link Actioned
Optional events
Infringing
URL Detected
t0
Link Found
Primary event

Link Lifecycle
Time
Deleted /
Matching
t0+tn
Link Correction
Cease
& Desist
t1 = t0+tn
Link Actioned
Take-
down
t2 = t1+tn
Link Removed
Optional events
Infringing
URL Detected
t0
Link Found
Primary event

Process Flow / Dataset
Event Detected
ETL
Cleansing
De-duping
Summaries
Dashboards
Fact table representation
Time Found Link New Unique File Unique Link Actioned Taken-down
4/10/14 2:50 PM www.4shared.com/rar/-6ebvl89/Justin_Bieber_-_All_Around_The.html 1 1 0 0
4/15/14 11:44 AM www.4shared.com/mp3/-2J4lahU/Nickel_Back_-_If_Everyone_Care.htm 1 1 0 0
4/15/14 2:50 PM www.4shared.com/rar/-6ebvl89 0 1 0 0
Time

Process Flow / Dataset
Fact table representation
Time Found Link New Unique File Unique Link Actioned Taken-down
4/10/14 2:50 PM www.4shared.com/rar/-6ebvl89/Justin_Bieber_-_All_Around_The.html 1 1 1 1
4/15/14 11:44 AM www.4shared.com/mp3/-2J4lahU/Nickel_Back_-_If_Everyone_Care.htm 1 1 1 0
4/15/14 2:50 PM www.4shared.com/rar/-6ebvl89 0 1 1 1
4/15/14 11:01 PM www.4shared.com/mp3/-qXkFru8/Kanye_West__Jay-Z_Bingo_Player.html 1
Event Detected Summaries
Dashboards
Time
ETL upserts

Pre-Upgrade Architecture
EDW
OBIEE
Dashboards
ODS
Subscriber Views
Star Schema
ETL
OLTP (source)
Streams &
CDC
OWB Mappings

Asynchronous Distributed HotLog Conﬁguration
Pre-Upgrade Architecture - Streams and Oracle CDC

Pre-upgrade Challenges
•Throughput
•Complex views
•Recovery after VM/DB crash
•Maintenance and development
•Purging auditing information
•Volume of redo
•Oracle’s Statement of direction

Over to you…
•Michael Rainey
@mRainey

Oracle GoldenGate

Oracle Data Integrator 11g
•Oracle’s strategic product for data integration
•Uses ELT (Extract, Load, Transform) approach
‣No middle ETL engine necessary
‣Uses the power of the target database to  
perform transformations
•Supports heterogeneous data sources
•Declarative design - separation of business and  
technical integration
•Data integrity controls create a “data firewall”
•Extensible through “Knowledge Modules”

ODI 11g Journalizing (CDC)
•Oracle Data Integrator Change Data Capture (CDC) delivered via Journalizing
‣Identify, capture, and deliver changes made to source data
‣Journalizing Knowledge Module (JKM) performs setup and creates infrastructure
•ODI CDC Framework
‣Capture Process - mechanism for capturing changed data from the source
database (Ex. Oracle GoldenGate)
‣Journals - tables (J$) hold references to changed records and the change type
(insert / update / delete)
‣Journalizing Views - (JV$, JV$D) provides access to changed data, used by IKM /
LKM in mappings
‣Subscribers - used to allow consumption of changed data at different intervals, for
multiple applications, etc.

GoldenGate and ODI Integration
•JKM Oracle to Oracle Consistent (OGG) Knowledge Module
‣ODI Metadata used to generate GoldenGate parameter files  
(extract, pump, replicate) and 
configuration files
‣Delivered with ODI
•ODI CDC Framework generated
‣Staging table - replicate of  
source
‣J$ (journal) table - change rows
•Journalized data used in  
transformations (via JV$ views)

Migration Decisions / Upgrade Planning
•ODI Master repository location
•GoldenGate considerations
‣Installation and configuration (RAC is trickier)
‣Classic vs Integrated capture (requires EE for both source & target)
‣How to use it? Product built for migration and/or replication
‣Naming conventions
•OWB mappings to ODI interfaces
‣Various migration approaches
•Control, Monitoring & Alerting (no free lunch)
•Testing & Go-live approach

Migration Steps
•Migrate OLTP applications to RAC
‣GoldenGate RAC target kept in-sync during application migration
•Performance tuning & ODI KM Modifications
‣Retain existing CDC framework objects when adding new tables
‣Update column mapping in replicat
‣Remove unnecessary code in Integration Knowledge Module
•Generate GoldenGate extract, pump and replicat
‣ODI Journalizing Knowledge Module
‣Source definitions file recommended
•Migrate OWB mappings to ODI interfaces
‣3Rs: re-assess, replicate and refine existing mappings
•Test the migration
‣Run both systems in parallel and compare results
‣Trends, aggregates, row counts

Micro-batch ETL

Micro-batch ETL
Variables to track
execution status
Error
handling
Recursive
execution
Execute
Load Plan

Post-Upgrade Architecture
EDW
OBIEE
Dashboards
2-node RAC
OLTP (source)
ODS
J$ Tables
Star Schema
ETL
GoldenGate Replication
ODI Interfaces
(CDC)
Control, Alerting, Monitoring

Control, Alerting and Monitoring
•GoldenGate status and lag
•ODI Agent monitoring
•ETL throughput / health: ODI session tables
•Enterprise Manager job scheduler to control ETL process
•Monitoring dashboard
!
!

GoldenGate Status and Lag

ODI Agent Monitoring and Healthcheck

Monitoring Dashboard

Monitoring Dashboard
Fact Table Load -
Volume and Duration
ETL currently running
and duration
Scheduled Job
Duration
OLTP -> BI Latency

Upgrade Results
•Reduced lag
‣From 5-15 minutes to <1 minute
•Stabilised fact mapping with equivalent load volumes
‣Pre-upgrade 2 mins - hours
‣Post-upgrade 10 - 25 seconds
•Reduced ETL downtime
‣2+ days p/m to minutes p/m
•Simpler to extend tables under CDC
•Purging audit information <1 hour rather than days

Upgrade Effects
•Faster troubleshooting & diagnosis times
•Shorter maintenance & development times
•Focus on performance and streamlining processes
•Investigation into excessive redo volumes
‣Understanding incremental statistics
•MDM project kick-off
•Contemplation of The Reference Architecture…

Reference Architecture & Realtime DW
•Staging Data Layer
‣Buffers reception for right-time distribution
‣Apply business rules to make the data clean, consistent and complete
‣Retain rejected data for manual/automatic correction

•Performance Layer
‣Dimensional model - star schema
‣Permanent & non-volatile data (traditionally speaking)

•Performance Layer
‣Dimensional model - star schema
‣Permanent & non-volatile data (traditionally speaking)
•Something in-between…
‣Caters for deeply volatile data by persisting historic and real-time facts
‣Combines elements of staging and performance layers
‣Facilitates agile de-coupled ETL processes

Real-time DW/BI - Blogged by Stewart Bryson 2011
http://www.rittmanmead.com/2011/05/real-time-bi-an-introduction/

Reference Architecture - Mashup

ReferenceArchitecture-Mashup
Sources
Staging Data Layer Performance Layer
Foundation Layer
refresh intervalETL interval
timeframe
Time
latency
Query
performance

Sources
Staging Data Layer
OLTP
Performance Layer
ReferenceDWArchitectureMashup
Foundation Layer
Standard
EDW
(Star)
In-memory
MaterializedViews
OLAP
Temporary Structures
timeframe
Time
latency
Query
performance

Sources
Staging Data Layer
OLTP
Performance Layer
Foundation Layer
Federated OLTP+EDW
Standard
EDW
(Star)
In-memory
MaterializedViews
OLAP
timeframe
Time
latency
Query
performance

Sources
Staging Data Layer
OLTP
Performance Layer
Foundation Layer
Federated OLTP+EDW
Federated EDW
+rolling hot partition
Standard
EDW
(Star)
In-memory
MaterializedViews
OLAP
timeframe
Time
latency
Query
performance

Hybrid Layer
Extreme Real-time
EDW
Sources
Staging Data Layer
OLTP
volatilitydepth
Performance Layer
Foundation Layer
Federated OLTP+EDW
Federated EDW
+rolling hot partition
Standard
EDW
(Star)
In-memory
MaterializedViews
OLAP
timeframe
Time
latency
Query
performance

Conclusion
•This was not a sales pitch!
•Real-time DW/BI inevitable
•Upgrade now
•Share your thoughts & experiences:
•nick.hurt@ifpi.org
•michael.rainey@rittmanmead.com

KScope14 - Real-Time Data Warehouse Upgrade - Success Stories

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