Oracle Exadata Machine Customer Experience

Exadata Customer Experience
From technical pre-sales to production
Olivier Granges, Groupe Mutuel Assurances
Emiliano Fusaglia, Trivadis
Swiss BI-Day – Thursday APRIL 3, 2014

Agenda
 Initial Customer Environment (BI)
 Technical pre-sales
 Proof of Concepts
 Data Replication
 Rollout Exadata on production
 Feedback after one year
experience

Initial Customer Environment
Application context
 DWH general information
 Large Datawarehouse (1.4 TB) planned to double its size by the third quarter of
2013 (IT merge of several health companies)
 Nightly ETL jobs taking about 10 hours.
Staging from ODS, Loading, Data Quality, Cube refresh
 The workload is already tuned, and the query parallelism is maximized based the
current resources
 By design, several TB of data are read every night.
Limit for DOP comes from I/O bottleneck

Previous Infrastructure
 Main HW and Software characteristics
 IBM P595A and AIX 6.1
 8 CPUs - 16 logical CPUs
 40 GB RAM
 Storage 4.3 TB (FC and SATA), SAN 2x2Gbit
 ASM, Oracle 11.2.0.2
 Both ERP and DWH databases on same hardware

Performance
 Oracle Parallel Servers optimize the CPU utilizations
 But the main bottleneck remains the I/O
 … in addition the Storage is shared with ERP environment.
 The above picture is before the merge of IT systems which will double the
volume of data

Bottleneck
AWR Wait Event HistogramAWR Top 5 Timed Foreground Events
AWR IOStat by Filetype summary
 I/O is the main bottleneck
 Most of I/O operation takes > 8ms
 Half of direct-path read are between 32ms and 1 second
 Most of I/O are large (multiblock) reads

In October 2012 the Business
Intelligent department of the Groupe
Mutuel asked Trivadis to help
defining the “Next DWH platform”
tailored on their needs.
They also informed Trivadis that all
the retained solutions would be
evaluated in a PoC, before
proceeding with the final choice and
the implementation.
Technical pre-sales
Introduction

 Major Architectural Requirements
 No changes to the ETL and the current data model
 Investigate the possibility to reuse existing HW
 Guarantee of High Availability and scalability of the implementation
 Customer key criteria adopted during the PoC (by ranking)
 Total cost of ownership (TCO)
 Execution time of the nightly ETL jobs
 Time to market of the new architecture (from installation to production readiness
and migration)
 Scalability and Operability of the architecture
Technical pre-sales
Customer Requirements

 Optimization of the existing architecture,
based on IBM pSeries and EMC storage
 Exadata Machine X3-2 1/8 RACK
 Two Cisco UCS460 and EMC SAN VNX5300
Technical pre-sales
Architectures proposed by Trivadis

Technical pre-sales
Optimization IBM pSeries EMC
Initial Architecture

Technical pre-sales
Optimization IBM pSeries EMC
Solution based on the optimization of the existing infrastructure

Technical pre-sales
Exadata Machine X3-2 1/8 RACK

Technical pre-sales
Two Cisco UCS460 and EMC

After an internal review, the Groupe Mutuel decided to retain only the Exadata
proposal, replacing the two other alternatives with the following options:
 One server Cisco UCS 460 (equipped with 4 sockets Intel Xeon, for a total of 40
Cores and 512GB RAM) attached to a Violin Memory 6232
 One IBM POWER 730 (equipped with 15 POWER7+ processor, 60 LCPUs and
256GB RAM) attached to a Violin Memory 6232
Technical pre-sales
Architectures proposed by GMA IT

Technical pre-sales
Cisco UCS and Violin 6232

Technical pre-sales
IBM POWER 730 and Violin 6232

 The PoC for all three evaluated architectures consisted in performing
the following tasks:
 Multiple runs of the ETL nightly jobs.
 Generation of several customer’s reports.
 Execution of ad hoc queries defined by the BI department.
 Each PoC result was evaluated using the already mentioned criteria
 Total cost of ownership (TCO)
 Execution time of the nightly ETL jobs
 Time to market of the new architecture (from installation to production readiness
and migration)
 Scalability and Operability of the architecture
Proof of Concept
Introduction

 The first PoC has been performed on IBM Power 730 Violin 6232
architecture.
 Key information
 Average execution time of the ETL nightly jobs  3h 10’
 Average CPUs utilization  60%
 I/O per second  2GB during all heavy load operations (which is the MAX
available throughput with the setup in place 8 FC 2Gb each)
Proof of Concept
IBM POWER 730 and Violin 6232

 The second PoC has been performed on Trivadis’s Exadata Machine
X3-2 1/8 RACK.
 Key information
 Average execution time of the ETL nightly jobs  2h 40’
 I/O per second  600MB during all heavy load operations (Thanks to the SMART
SCAN and HCC Functionalities)
Proof of Concept
Exadata Machine X3-2 1/8 RACK

 The third PoC has been performed on Cisco UCS Violin 6232
architecture.
 Key information
 Average execution time of the ETL nightly jobs  4h (Not fully optimized because
the initial setup took too long)
 I/O per second  2GB during all heavy load operations (which is the MAX
available throughput with the setup in place 8 FC 2Gb each)
Proof of Concept
Cisco UCS and Violin 6232

Key figures measured during the PoC
Proof of Concept
Summary

…..and the winner is
Proof of Concept
The Winner

 Oracle Streams
 Endianness not compatible between AIX and Linux platforms
 ERP running on Oracle 10.2.0.5
 DWH running on 11.2.0.2, compatible 10.2.0.5
Data Replication
Introduction

Data Replication
Previous solution
ERP
AIX
Oracle 10.2.0.5
ODS
AIX
Oracle 11.2.0.2
Compatible
10.2.0.5
Oracle Streams

Data Replication
New solution
ODS
AIX
Oracle 11.2.0.2
Compatible
10.2.0.5
ERP
AIX
Oracle 10.2.0.5
ABCD
ABCD
Oracle Streams
ABCD

 Freeing resources for ERP before migration
 Team members on holiday
 Integrating new technologies for IT Teams
 Endianness between AIX and Linux environments
 Data replication from ERP to Exadata
Rollout Exadata on production
Few chalenges

 Good team organization
 Who does what and when
 Communication between people
 Everybody refers to only one single coordinator
 Using a temporary database before Exadata delivery
 Training people for the D-Day
 Setting up database objects in an Exadata-like environment
 Applying settings done during the PoC
The way to success

 Done in less than two weeks
 10.06.2013: Exadata delivered on site by Oracle
 18.06.2013: Exadata ready for use
• Oracle needs a few days to set it up before allowing us to use it
 19.06.2013 (office closure): old environment disconnected
 20.06.2013 - public holiday : Data migration
• Data Pump over DB-Link to avoid RMAN data conversion
 21.06.2013: Exadata running in production
 Minimizing service interruption: done during a public holiday
 Monitoring activity during two weeks after migration
Success
Mon Tue Wed Thu Fri Sat Sun Mon Tue Wed Thu Fri
10.06.2013
11.06.2013
12.06.2013
13.06.2013
14.06.2013
15.06.2013
16.06.2013
17.06.2013
18.06.2013
19.06.2013
20.06.2013
21.06.2013
Oracle setup
Customisation
Migration
Exadata Go Live

 Facts
 Storage usage decreasing with HCC
 Optimization
 Maintanance
Feedback
Introduction

 Before Exadata
 DWH (stars facts)
• 148 stars
• 169 GB
• 1’420’351’040 rows
 ODS
• 651 tables
• 765 GB
 Daily Load
• 10h30
• Time window fully used
Feedback
Facts
 With Exadata - Today
 DWH (stars facts)
• 229 stars (+ 55 %)
• 291 GB (+ 72 %)
• 4’081’389’649 rows (+ 187 %)
 ODS
• 1’506 tables (+ 131 %)
• 1’305 GB (+ 71 %)
 Daily Load
• 5h30 (- 47 %)
• 5 hours margin

Feedback
Storage usage decreasing with HCC
 HCC: Hybrid Columnar Compression
 Most efficient with high redundancy
tables
 Compression factor: > 70%
 Various compression level depending on
data usage:
 optimized for query performance:
COMPRESS FOR QUERY [LOW | HIGH]
 optimized for maximum storage savings:
COMPRESS FOR ARCHIVE [LOW | HIGH]

Feedback
Optimization
 Increasing parallelism degree
 Enabling data compression (HCC)
 70 % less disk used
 Smart Flash Cache
 KEEP activated on large tables
 3.6 GB / sec

Feedback
Maintanance
 Before Exadata
 A lot of resources working for
delivering Daily Load in time and to
get the most efficiency of the system
• IT Teams
• DBA
• DWH
• Trivadis
 With Exadata - Today
 Standard support from IT Teams
 Oracle Platinum Support

Questions ?

Oracle Exadata Machine Customer Experience

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Oracle Exadata Machine Customer Experience