KSCOPE 2013: Exadata Consolidation Success Story

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Exadata Consolidation Success Story Getting the kids to play nice with each other… 1 Presented by: Karl Arao

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Transcript of KSCOPE 2013: Exadata Consolidation Success Story

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Exadata Consolidation Success Story

Getting the kids to play nice with each other…

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Presented by: Karl Arao

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whoami

Karl Arao• Senior Technical Consultant @ Enkitec• Performance and Capacity Planning Enthusiast

7 years DBA experienceOracle ACE, OCP-DBA, RHCE, OakTableBlog: karlarao.wordpress.comWiki: karlarao.tiddlyspot.comTwitter: @karlarao

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100+

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Agenda

• Architecture • Tools and Methodology

– Simple consolidation scenario– Provisioning workflow and the worksheet

• War Stories

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General Architecture

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Primary Site Standby Site

Production

Test & Dev Disaster Recovery

Future Growth

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General Architecture

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The Stats

Three Half Rack Exadata clusters with High Cap. drivesCluster #1

36 Dev/Test Databases

Cluster #211 Production Databases

Cluster #313 Dev/Test Databases6 Standby Databases

Still more databases to come…

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Why Consolidate?

Primary drivers for consolidation center around cost savings•Reduces Oracle software licensing•3rd party products such as backup agents, ETL tools, etc…•More efficient use of system resources•Soft Costs

– Floor space– Power & Cooling– Administration, Staffing Costs

(training, etc.)

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7 Databases

A Simple Consolidation Example

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For example, the first row should read… Database ‘A’ requires 4 CPU’s and will run on nodes 1 and 2 (2 CPU’s each)

Let’s say we have the following databases to migrate on Exadata:

Cluster Level Utilization

A Simple Consolidation Example

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Let’s say we have the following databases to migrate on Exadata:

Per compute node Utilization

For example, the first row should read… Database ‘A’ requires 4 CPU’s and will run on nodes 1 and 2 (2 CPU’s each)

A Simple Consolidation Example

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Cluster Level

Utilization = 29.2%Per compute node Utilization

25% 42% 33% 17%

A Simple Consolidation Example

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Cluster Level

Utilization = 29.2%Per compute node Utilization

8% 83%83% 17% 8%

A Simple Consolidation Example

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• Gather Utilization Metrics (usage history)• Create Provisioning Plan• Implement Plan• Audit Your Implementation

Tools And Methodology

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Provisioning Worksheet

• Capacity Planning

• Communication Tool

• Hand off

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**Supplement to existing Exadata installation tools:• Site planning checklist• Configuration Worksheet• Exadata Configurator sheet• CheckIP• OneCommand

Utilization = Requirements / Capacity

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Capacity

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2 = quarter rack4 = half rack8 = full rack

SPECint_rate2006http://goo.gl/doBI5

CPU_COUNT, threads, & cores

http://goo.gl/CunHN

96 to 144GB(frequency of the memory DIMMs

drops to 800 MHz from 1333 MHz)

Space will also depend on:•ASM redundancy•DATA/RECO allocation

http://goo.gl/I3fjn

Query Low (4x)Query High (6x)Archive Low (7x)

Archive High (12x)

Smart

Scans!

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CPU Core Comparison

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Source

chip efficiency factor = source SPEC rating / Exadata SPEC rating = 16/26 = .6154 EXA cores requirement = source host cores * utilization * chip efficiency factor = 32 * .7 * .6154 = 13.78

* offload factor * .5 --------- 6.89

Sun Fire X4170 M2 [email protected]

Destination

how much of the source CPU cores

are being used

multiplier for equivalent database

machine cores

amount of CPU resources that will be offloaded to the

storage cells

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The Perfect Storm(Peoplesoft HR)

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Month-end Processing+ Weekly Time Entry

+ SQL Plan Change------------------------------------

Uh-oh!

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CPU Allocation

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DB Uniq Name DB Namenode1

node2

node3

node4

    4 instance 5 instance 4 instance 3 instance

    47% cpu used 75% cpu used 47% cpu used 18% cpu used

  49% mem used 66% mem used 71% mem used 54% mem used

BIPRDDAL biprd   P P  

DBFSPRD DBFSPRD P P P P

HCMPRDDAL hcmprd P P    

MTAPRD11DAL mtaprd11     P P

PAPRDDAL paprd P P    

RMPRDDAL rmprd P P    

dbm dbm F F F F

Fsprddal fsprd     P P

= Preferred = Failover

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Load Map(our first stop…)

Users Complaint: HR time entry and OBIEE reports painfully slow…

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Top Activity - HCMPRD

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Instance Activity – HCMPRD2

HCMPRD Caged at 12 CPU’s

SQL Profile Installed to lock in good plan.

Problem: A single SQL stmt. overwhelming CPU resources.

Node 2

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Memory Exhaustion(OBIEE)

“1 Report = 1 SQL query, right?”

WRONG!

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Overlapping workloads of three databases across 3 nodes.

BIPRD, HCMPRD, and MTAPRD

Overlapping workloads of three databases across 3 nodes.

BIPRD, HCMPRD, and MTAPRD

Node 1

Node 2

Node 3

Node 4

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Node Layout Revisited…

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Notice what happens to CPU waits and the system load average when this report is run.

Notice what happens to CPU waits and the system load average when this report is run.

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PGA Memory SpikesPGA Memory Spikes

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Storage Cell Saturation(OBIEE)

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I/O Intensive Workload

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Smart Scans as seen in Grid Control

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25 Sessions Doing Smart Scans

…as seen in gv$sql

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Smart Scan in Action. The cells are scanning 1T but only returning 144G…***That’s on each of the highlighted row source below…

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The databases on other nodes see the contention as “System I/O”Without I/O resource management even critical processes are affected (CKPT, LGWR, …)

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Inter-database IORM Plan(only kicks in when needed)

I/O requests from critical processes like CKPT, LGWR, LMON get priority automatically.Without IORM I/O requests from these important processes receive the same priority as any other process.

*Side Benefit (automatic when IORM is enabled)

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IORM Plan Definition(on each storage cell)

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Wrap up!

Provisioning Methodology & Tools– Workflow– Provisioning Spreadsheet

Success Stories– CPU resource management– Tuning and provisioning adjustments– I/O resource management

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