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
BI Forum 2014

Introduction
•Michael Rainey (Rittman Mead)
‣Principal Consultant - Oracle Data Integration expert
•Nick Hurt (IFPI)
‣Solutions Developer - working on Oracle solutions since 2002
•the International Federation of Photographic Societies
‣“the voice” of the recording industry worldwide
‣represents the interests of 1,300 record companies from across the
globe
‣acquired funding for OBIEE in 2010
‣required near real-time anti-piracy analytics

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

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

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

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

Fact Table Load -
Volume and Duration

Fact Table Load -
Volume and Duration
Scheduled Job
Duration

Fact Table Load -
Volume and Duration
ETL currently
running and duration
Scheduled Job
Duration

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
•MDM project kick-off
•Contemplation of The Reference Architecture…

Reference Architecture - Hybrid Layer
•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)
•Hybrid Layer
‣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

Sources
Staging Data Layer
OLTP
refresh interval
Time
volatilitydepth
ETL interval
Performance LayerHybrid Layer
ReferenceDWArchitectureMashup
latency
Foundation Layer
Extreme Real-time
EDW
Federated OLTP+EDW
Federated EDW
+rolling hot partition
Standard
EDW
In-memory
MaterializedViews
OLAP
Temporary Structures
Query
performance timeframe

Real-time Data Warehouse Upgrade – Success Stories

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