Consolidating databases on oracle exadata key learnings at intel
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Gagan Singh Intel Corporation Subhadra Sampathkumaran Intel Corporation James Harding Oracle America. Consolidating Databases on Oracle Exadata: Key Learnings at Intel . Agenda. Intel – Database Environment Overview Legacy Environment overview & Configuration

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Consolidating databases on oracle exadata key learnings at intel

  • Gagan Singh

  • Intel Corporation

  • Subhadra Sampathkumaran

  • IntelCorporation

  • James Harding

  • Oracle America

Consolidating Databases on Oracle Exadata: Key Learnings at Intel


Agenda

Agenda

  • Intel – Database Environment Overview

  • Legacy Environment overview & Configuration

  • Limitations of Legacy Architecture

  • Goals of Migration to Exadata

  • Proof of Concept

  • ExadataSolution Architecture

  • Value

  • Key Learnings & Challenges

  • Summary


Intel database environment overview

Intel – Database Environment Overview

  • Highly automated factories with 100’s of complex integrated systems

  • Goals include -Yield analysis, process improvement, failure mode analysis and test time reduction

  • Geographically distributed independent systems

  • Monitoring and Availability is key

  • 24 x 7 uptime

  • Strict reporting SLA’s

  • Support (DSS) and OLTP Setup


Legacy environment overview

Legacy Environment Overview

  • DB size ranges from a few GB’s to ~ 80 TB per site (6 month retention)

  • Large data growth projected.

  • Reliability, Availability and Performance - High priority

  • Application tier includes 3rd party products and in-house apps

  • Robust Backup and Recovery though lacks performance

  • Long MTTR for Disaster Recovery

  • Monitoring – Oracle Grid control 10.2.x


Legacy configuration

Legacy Configuration

  • Each site hosts independent RAC with SAN storage.

  • Database: Oracle10.2.x Windows2003 x64

  • GigE with Jumbo Frames for interconnect

  • >80 TB on ASM External Redundancy

  • RMAN incrementally merged backup to FRA  Tape

  • Application tier – OCI, ODP.Net, OLEDB, ODBC

EMC DMX-414 Racks


Consolidating databases on oracle exadata key learnings at intel

Limitations of Legacy Architecture


Goals of migration to exadata

Goals of Migration to Exadata


Exadata proof of concept requirements

Exadata Proof of Concept Requirements

  • Run Data Warehouse queries with atleast 2x improvement

  • Run OLTP Read (small queries) and Read-Write (loader) workload with 40% performance improvement

  • Achieve a 5x reduction in data size with the use of Advanced and Hybrid Columnar Compression

  • Demonstrate backup and restore improvement of 2x

  • Meet or beat current RAP targets as defined by Intel


Executing the proof of concept

Executing The Proof Of Concept

Less Risk, Better Results

  • Validating the success criteria

    • Performance: Data Warehouse Queries, Data Loaders

    • Data Compression

    • Backup/Recovery w/ZFS Storage Appliance

    • Reliability, Availability and Performance

  • Exadata/ZFS pre-delivery process

  • Exadata/ZFS Delivery

  • Data Migration

  • Execute test plan and capture data

Ready- to-Run


Exadata solution architecture

Exadata – Solution Architecture


Exadata performance

Exadata- Performance

  • RMAN Backup

    • Disk backup increased to 8 TB/Hour

    • Restore Time7.2 TB/Hour

  • Write back Flash Enabled

  • Availability

    • Application not impacted under various failure scenarios

  • Storage reduction

    • Achieved by index reduction and data compression

    • Query Performance

      • 2x Improvement

      • Application tuned to leverage 11.2 DB features

  • Compression

    • Up to 10x HCC compression

      • 5x typical

    • Current data using OLTP compression

    • Archival Data – HCC (Query High)

  • Data Loading Times

    • Faster by 40%


  • Contd

    -contd

    • Resource Management

      • DBRM & IORM configured

    • High, medium and low consumer groups defined

      • Resource limits for CPU, IO and parallelism configured for each group

    • Users categorized into consumer groups based on services used to connect

  • Monitoring & tuning

    • Oracle 12c Grid Control

    • SQL Monitoring used extensively for tuning queries

  • Efficient Setup and startup time

    • HW/OS/Storage/DB Setup to Best Practices

    • ~70% less time than conventional infrastructure startup

  • Support

    • Leverage Platinum support

    • ~50% reduction in Infrastructure+DBA operational calls


  • Application changes key learnings

    Application Changes – Key Learnings

    • Leverage 11g R2 features

      • Tuning queries from 10g to 11g – Used 12c SQL monitoring

    • Changes for Exadata

      • Smart Scan, compression (OLTP for most recent data and HCC for older data)

      • Minimize indexes to enable offload to storage

    • Optimizer

    • Parallelization & partitioning

    • Globalization with GMT

      • Date/time values stored in TIMESTAMP WITH LOCALTIMEZONE columns

      • Date/time retrieved based on client time zone settings – managed using services and logon trigger

    • Centralized DB

      • Site specific schemas

      • 1 global core schema for common functionalities


    Key challenges

    Key Challenges

    • Query performance

      • Adapt from 10g->11g optimizer + Exadata specific features

      • Significant effort to tune queries as legacy system had embedded SQL hints

  • Storage reduction

    • Identifying indexes to reduce – Several still needed to support OLTP queries

    • Testing with varying levels of compression models

  • Globalization using GMT

    • Date/time from sources distributed geographically stored in the DB

    • Geographically distributed users require data retrieved in local time zone.

  • Centralization

    • Large DB size – Manageability

    • Resource management – Thousands of adhoc users


  • Contd1

    -Contd

    • Data migration

      • Two approaches

        • AS-IS for certain existing data domains – Load from raw source files on empty schema

        • Complete re-architect – Incrementally load historical data from existing legacy systems

        • Data loading 24x7 – does not follow conventional batch loading with DW

    • Application cut-over

      • Phased approach


    Support

    Support

    • Single vendor support

      • One number to call for all components.

      • No triage time – single vendor for servers, storage, networking, OS, DB

    • Platinum Services

      • Platinum Gateway

      • Quarterly Rolling patching

      • Automated Service Requests

      • Grid Control Monitoring

    • Single patch set

      • 40% savings in patching time

      • Single application validation - Reduced time for application validation


    Exadata value summary

    Exadata Value Summary


    Thank you

    Thank You


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