kscope14 - real-time data warehouse upgrade - success stories

www.rittmanmead.com [email protected] @rittmanmead

Real-Time Data Warehouse Upgrade - Success StoriesNick 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 : [email protected] 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

http://www.rittmanmead.com/blog/


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




•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


t0

Link Found

Primary event


Link Lifecycle

Time

Deleted / Matching

t0+tn

Link Correction

Cease & Desist

t1 = t0+tn

Link Actioned

Optional events


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


t0

Link Found

Primary event


Process Flow / Dataset

Event DetectedETL

Cleansing

De-duping

SummariesDashboards

Fact table representation

Time Found Link New Unique File Unique Link Actioned Taken-down4/10/14 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

http://www.4shared.com/rar/-6ebvl89/Justin_Bieber_-_All_Around_The.html

http://www.4shared.com/mp3/-2J4lahU/Nickel_Back_-_If_Everyone_Care.htm

http://www.4shared.com/rar/-6ebvl89


Process Flow / Dataset

Fact table representation

Time Found Link New Unique File Unique Link Actioned Taken-down4/10/14 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

http://www.4shared.com/rar/-6ebvl89/Justin_Bieber_-_All_Around_The.html

http://www.4shared.com/mp3/-2J4lahU/Nickel_Back_-_If_Everyone_Care.htm

http://www.4shared.com/rar/-6ebvl89

http://www.4shared.com/mp3/-qXkFru8/Kanye_West__Jay-Z_Bingo_Player.html


Pre-Upgrade Architecture

EDWOBIEE

Dashboards

ODSSubscriber 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) andconfiguration 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

EDWOBIEE

Dashboards

2-node RACOLTP (source)

ODSJ$ 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


Reference A

rchitecture - Mashup

Sour

ces

Staging Data Layer Performance Layer

Foundation Layer

refresh intervalETL interval

timeframe

Tim

e

latency

Que

ry performance


Reference A


Sour

ces

Staging Data Layer

OLT

P

Performance LayerR

efer

ence

DW

Arc

hite

ctur

e M

ashu

p

Foundation Layer

Standard EDW (Star)

In-m

emor

y M

ater

ializ

ed V

iews

O

LAP

Temporary Structures


timeframe

Tim

e

latency

Que

ry performance


Reference A


Sour

ces

Staging Data Layer

OLT

P

Performance LayerR

efer

ence

DW

Arc

hite

ctur

e M

ashu

p

Foundation Layer

Federated OLTP+EDW

Standard EDW (Star)

In-m

emor

y M

ater

ializ

ed V

iews

O

LAP



timeframe

Tim

e

latency

Que

ry performance


Reference A


Sour

ces

Staging Data Layer

OLT

P

Performance LayerR

efer

ence

DW

Arc

hite

ctur

e M

ashu

p

Foundation Layer

Federated OLTP+EDW

Federated EDW+rolling hot partition

Standard EDW (Star)

In-m

emor

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ater

ializ

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iews

O

LAP



timeframe

Tim

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ry performance


Hybrid LayerExtreme Real-time

EDW

Reference A


Sour

ces

Staging Data LayerO

LTP

vola

tility

dep

th

Performance LayerR

efer

ence

DW

Arc

hite

ctur

e M

ashu

p

Foundation Layer

Federated OLTP+EDW

Federated EDW+rolling hot partition

Standard EDW (Star)

In-m

emor

y M

ater

ializ

ed V

iews

O

LAP



timeframe

Tim

e

latency

Que

ry performance


Conclusion

•This was not a sales pitch!•Real-time DW/BI inevitable•Upgrade now•Share your thoughts & experiences: •[email protected] •[email protected]

kscope14 - real-time data warehouse upgrade - success stories

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