Epic Clarity Running on Exadata

Optimize the Performance of Your
Epic Clarity Data Warehouse

Industry specific cover image

Webcast 2/14/2013

||

| Epic

Anita Salinas

Patrick O’Connor

Tim Fox

Bob Bryla

Healthcare
Bus. Dev.
Oracle

Healthcare
Sales Consultant
Oracle

Chief Technologist
Enkitec

Snr. DB Architect &
Systems Engineer
Epic

© 2013 Oracle Corporation

Agenda
•  Introductions
•  Why optimize?
•  Exadata: extreme performance for OLTP and DW
•  Customer results: Enkitec
–  Benchmark 1 results
–  Benchmark 2 results
–  Short demo

•  Epic/Clarity target platforms explained: Epic
•  Summary and next steps
•  Q&A


2

Exadata Delivers Higher Value To Epic Clarity Users
Benefits Realized In Multiple Areas
IT Value
IT Cost Advantage
•  Reduce core IT costs
•  Significant cost benefits
•  Lowest industry TCO

What if you could get
MORE information
SOONER
and USE LESS
hardware to do it?


• 
• 
• 
• 
• 

Higher operational excellence, raise IT bar
Improve service - enhance SLA metrics
Seamless DW w/OLTP environment
Higher performance, scalability, throughput
Standardized complete management tools

Business Value
Epic
Clarity on
Oracle
Exadata

• 
• 
• 
• 

Improve quality of patient care
Receive timely critical reports
Execute reports more frequently as needed
Strategic partnership IT<->Business

3

Business Users Will Realize Significant Benefits
Oracle Customers Confirm Benefits
Epic Clarity Reports: 5-100x
Performance Improvements

ADT
Prelude

Sample Set of Reports

OpTime
Surgery

• Organ donor list, heart and lung transplant reports
• Specific inpatient diagnosis/flowsheet data related to transplants

EpicCare
Inpatient

• Currently admitted inpatient data for specific counties

EpixRx
Medication

• Medication, MAR, dispensed charge data
• Orders and treatment plan data

EpicCare
Outpatient
Tapestry

Resolute
Hospital
Billing

Profess.
Billing

• Orders, results, diagnosis for ambulatory visits for specific depts
• Outpatient appointment data for a specific county
• OR logs excluding specific CPT codes including charge data
• OR logs for specific CPT codes including charge data
• ED data from the prior day based on trauma diagnosis
• ED Order data
• ED patient flowsheet data and events


4

Customers Confirm Higher Business Value
Enhanced Patient Care With Confidence
~200 Daily Reports, >300
Locations Will Benefit

Timely Transplant Reports

Admin

•  Improved patient care due to timely
information, data confidence

Other
Reports

•  Enhanced productivity for all
coordinators, supporting personnel
•  Improved IT productivity, eliminating
unnecessary running of reports

•  Improved patient care

IT
Ops

•  Significant productivity boost to clinical,
research, administrative users
•  Improved operational effectiveness and
reduced cost to keep the lights on

Clinical
Finance

New Research Reports
•  Meet new requirements due to
faster report execution


Research

Finance
Education

Provide financial reports to
analysts sooner for regular
reporting periods

5

Oracle Exadata
Extreme OLTP/DW Performance


6

Exadata Unified Workload Transformation
Single Machine for…
•  OLTP
•  Data Warehousing
•  ETL
•  Query parallelism

OLTP with Analytics and Parallelism of
Warehousing
Warehousing with Interactivity, Availability,
and Security of OLTP


7

Exadata Innovations
•  Hybrid Columnar Compression

•  Intelligent Storage
–  Scale-out InfiniBand storage
–  Smart Scan query offload

+

+

+

•  Smart PCI Flash Cache
–  Accelerates random I/O up to 30x
–  Triples data scan rate

–  10x compression for warehouses
–  15x compression for archives

Data
remains
compressed
for scans
and in Flash
Benefits Cascade
to Copies


uncompressed

compress
primary DB

standby

test

dev

backup

8

Oracle Exadata: Extreme Performance and Scale
Advantages
•  Significantly reduce query times by orders of magnitude
•  Use fewer indexes to significantly improve daily load times
–  Less space utilization
–  Reduced maintenance of index builds/rebuilds

•  Lower costs by consolidating all workloads on one platform
–  Use Exadata for simultaneous Warehouse and OLTP

•  Accelerate response times by up to 100x (or better)


9

Compression Ratio of Real-World Data
Query
Compression
Ratio

•  Compression ratio varies by
customer and table

(Average=
13x)

Healthcare

C
Healthcare

B

•  Trials were run on largest table at
10 ultra large companies

Financial

P
Financial

B
Financial

U
Financial

H

•  Average revenue > $60 BB

•  13x – Avg query compression ratio

Telecom

A
Telecom

T
Telecom

H

•  On top of Oracle’s already highly
efficient format
0


10

20

30
10

Secure Database Machine

• 

Moves decryption from software to hardware
• 

Over 5x faster

• 
• 


Near zero overhead for fully encrypted database
Queries decrypt data at hundreds of Gigabytes/
second

11

Epic Clarity on Exadata
Benchmark 1 Details


12

Observations - Epic Clarity on Exadata
•  Data model has many very wide tables but rarely are all columns in a single report
•  Data model loaded on daily / usually requires significant DB server resources
•  Thousands of reports are run against Clarity on a daily basis
•  Up to 120 reports may execute concurrently
•  Clarity customers look for database configurations which improve throughput.
Often, the result is non-default Oracle configurations
•  Customer-written report queries are often more complex than Epic-released
reports, and are challenging to tune with traditional methods


13

Epic Clarity on Exadata POC - Approach
•  1.5T Clarity database imported to Exadata X2-2 Quarter Rack (excluding audit tables)
•  One BizObj server (VM) used to generate reporting load for 40 concurrent report jobs
•  Evaluated automated reporting batches for execution time, load characteristics
•  Customer supplied specific, long-running queries tested individually on Exadata
•  Where applicable, Exadata features induced to explore performance
•  Exadata’s Hybrid Columnar Compression (HCC) not used to compress tables during
the POC, but compression tests were run on large tables
•  Tests on CLARITY_TDL_TRAN table show the following results
•  Query High HCC Compression ratio – 8x to 10x
•  Can reduce a 30GB table to 3GB

•  Query Performance of HCC Compressed data often execute faster

14

Query Execution
•  Customer supplied queries were executed under the following conditions:
•  Database configured per Customer (matches current production)
•  Reduced buffer cache to 2GB / multi-block read count = 128 / all non-PK indexes
made invisible

•  Configuration changes were made to show that Exadata performs better, for
most DW workloads, with a smaller memory footprint
•  The following page displays the results of the individual query testing done
for a Clarity customer on Enkitec’s Exadata X2-2 quarter rack


15

Results – Query Execution
Average Performance Improvement – 91x


16

Epic Clarity on Exadata
Benchmark 2 Details


17

Epic Clarity on Exadata POC – Approach
•  Customer provided 2T production Clarity database export, 20 specific queries
•  Supplied queries were run unmodified under three configurations:
*8 GB SGA (equivalent to current production) *15 GB SGA *40 GB SGA
•  PARALLEL_MAX_SERVERS =24
•  Used standard formula maximum parallel Servers = 2 * Core Count

• 
• 
• 
• 
• 
• 

Each query executed 2x to ensure at least some relevant data in buffer cache
Hybrid Columnar Compression (HCC) was not used
No tables were pinned in Exadata Smart Flash Cache
The entire POC was run on a single node Exadata Quarter Rack
Parallel slaves were confined to one node of the RAC
All serial processes were run on a single node of the RAC


18

Results – Query Execution
Currnent
System
8G SGA

Query 1
Query 2
Query 3
Query 4
Query 5
Query 6
Query 7
Query 8
Query 9
Query 10

46:13.00

58:55.00

32:24.00

06:57.00

8:45:12.00

14:04.00

04:47.00

08:33.00

6:38:10.00

19:59.00

Exadata
8G SGA

00:00.02

00:00.05

11:47.44

00:15.81

13:17.68

00:25.14

00:16.46

00:36.71

02:50.14

10:43.30

Exadata 15G
SGA

00:00.02

00:01.66

10:29.40

00:15.45

10:36.32

00:11.60

00:16.80

00:35.31

02:49.07

06:48.19

hr:min:sec:10th
sec

Exadata 40G
SGA

00:00.02

00:01.94

08:20.10

00:15.80

11:05.40

00:11.83

00:18.97

00:35.22

02:48.65

03:33.01

Parallel Degree

Exadata Improvement
Factor (based on 8G SGA)

24

24

24

24

24

24

24

12

Serial

12

138,650

70,700

3

26

40

34

17

14

140

2

Improvement factors are based on the current system compared to Exadata with an 8G SGA


19

Results – Query Execution Continued
Currnent
System
8G SGA

Query 11
Query 12
Query 13
Query 14
Query 15
Query 16
Query 17
Query 18
Query 19
Query 20


28:07

40:07

36:08

1:10:27

04:45

02:57

1:27:26

42:32

18:23

3:13:31

Exadata
8G SGA

00:13.18

01:58.41

00:12.15

09:29.83

00:13.68

01:33.33

08:05.57

02:24.66

00:05.03

00:18.39

Exadata 15G
SGA

00:13.66

01:52.75

00:13.82

03:25.33

00:13.80

00:00.46

00:13.49

01:21.20

00:14.04

00:15.75

Exadata 40G
SGA

00:14.24

01:55.74

00:11.96

00:13.52

00:13.37

00:02.14

00:13.32

00:58.96

00:13.76

00:16.67

Parallel Degree

Exadata Improvement
Factor (based on 8G SGA)

24

24

24

Serial

24

24

Serial

24

24

24

128

20

178

7

21

2

11

18

219

631

20

Results – HCC Compression Test
To test Hybrid Columnar Compression on Clarity data, the Compression
Advisor (DBMS_COMPRESSION) was used to simulate compression of
the CLARITY_TDL_TRAN table
HCC Compression Level

Compression Ratio

Query Low
Query High

6 to 1

Archive Low

8 to 1

Archive High


3 to 1

10 to 1

21

Demo and Conclusions


22

Conclusions
1•  Epic Clarity workload hits the sweet spot for Exadata
–  Large data volume, long running queries

2•  It is impossible to match Exadata’s IO capability for large table scans with any

other Oracle-capable platform

3•  Additional benefits are available
–  Hybrid Columnar Compression, Exadata Flash, and Parallelism

4•  With minimal effort, Customer can identify the business benefit of extreme

performance gains shown during this POC

5•  Exadata supports improved performance with smaller memory

–  More databases can be run on same hardware vs. custom built systems


23

Epic Clarity Target Platforms

Epic

•  Target platform definition
•  Supported platforms
•  Customer demand
•  Industry trends
•  Exadata in-house at Epic


24

Summary and Next Steps


25

Summary
What can YOU do generating MORE reports FASTER on LESS hardware?
•  Extreme Epic Clarity performance on Exadata
–  Up to 100x faster

•  Do more (reports) with less (hardware) in less (time)
–  512 reports in 12 hours vs. 1604 reports in 4 hours
–  3x # of reports completed in ¼ the time
–  Lower costs, consolidate workloads on same hardware

•  Improve care quality
–  More timely = better intelligence
–  Actionable data at your fingertips sooner and/or more often


26

Next Steps
Join us at HIMSS13!
•  Oracle and Enkitec Breakfast Briefing

Wed, March 6, 2013 7:30-9:00am
Register here

•  Continue the Conversation Reception
Wed, March 6, 2013 4.30-7.30pm
Invite forthcoming

Investigate further
–  Exadata website

–  Schedule a private consultation


Consultation
•  Assess performance of Epic Clarity DW
•  Review reports and queries to identify
opportunities that improve reporting
•  Compare system to benchmark results
•  Written performance recommendations
Contact info@enkitec.com

27

Q&A


28

For More Information
• 
• 
• 
• 
• 

Visit:
Read:
Join:
Follow:
Call:


Oracle Healthcare Website
Oracle Healthcare Solutions
Oracle Healthcare on Facebook
Oracle Healthcare on Twitter
Oracle Healthcare Representative

29


30

Appendix – Query Execution

Current
Customer
System
8488_sec_aun8fmpug9jk4

8207_sec_1vauja2xan534

6881_sec_232b9Czqbnn9

6833_sec_18mgrhn25hvk8

6827_sec_facj6p8f68drf

6820_sec_azgu4cxwvub3n

5890_sec_57rgm8v0jzpc1

5695_sec_5a02q7wg0k05x

5546_sec_at3uwh0bmvygv

03:46:17.33

06:14:16.34

06:06:15.45

02:53:32.03

01:40:23.40

00:27:34.90

00:31:11.20

00:50:19.90

00:49:20.10

Exadata per
Customer
16GB Buffer

00:55:41.50

01:23:19.67

01:22:36.91

00:49:11.32

00:28:55.56

00:10:30.08

00:04:25.41

00:25:42.47

00:06:56.32

Exadata per
Enkitec
4GB Buffer

00:50:10.97

01:06:36.11

01:05:02.66

00:30:56.22

00:25:10.01

00:01:52.60

00:13:44.35

00:23:57.29

00:07:38.94

Exadata per
Enkitec
2GB Buffer

01:08:15.80

01:19:04.93

01:15:24.70

00:35:38.72

00:26:51.30

00:02:05.00

00:12:29.06

00:23:35.28

00:07:03.25

Exadata No
Indexes
2GB Buffer

00:22:08.46

00:52:50.74

00:52:53.65

00:18:15.83

00:11:50.95

00:00:38.90

00:03:00.75

00:00:46.47

00:07:13.97

All queries improved in performance on Exadata with no tuning. No parallelism
was used. All queries were run on one node of the two node RAC.


31

Appendix – Query Execution

Current
Customer
System
5282_sec_13w3x29huvpzs

4742_sec_g6hmtqdhggcs7

4736_sec_1jkjps3basyz7

4728_sec_9fy866srqj1hz

4716_sec_1wuj2pzmdf0wk

4120_sec_3vu8b5sfmr8r6

3534_sec_fv2hr8d15q4tr

3383_sec_dvztmf02uqcya

3184_sec_gg5jrs56h19t2

3182_sec_gazv5xbhh0w5s

00:38:40.30

00:31:12.80

00:16:34.40

00:28:07.20

00:47:45.80

14:35:44.65

00:09:22.60

00:12:54.30

00:36:13.60

00:08:08.50

Exadata per
Customer
16GB Buffer

00:04:55.45

00:04:55.45

Killed

00:33:24.63

00:11:31.62

TEMP

00:11:08.64

00:00:09

00:00:00.52

00:00:52.88

Exadata per
Enkitec
4GB Buffer

00:05:05.03

00:00:01.28

Killed

00:23:31.59

00:06:15.23

TEMP

00:09:12.01

00:00:11.52

00:00:03.63

00:02:38.70

Exadata per
Enkitec
2GB Buffer

00:05:05.76

00:00:00.95

Killed

00:24:51.67

00:04:59.86

TEMP

00:09:36.35

00:00:04.15

00:00:03.52

00:02:18.52

Exadata No
Indexes

00:12:46.55

00:00:02.20

00:17:52.99

00:09:54.17

00:10:29.17

TEMP

00:00:33.87

00:00:04.57

00:00:07.08

00:01:33.66

All queries improved in performance on Exadata with no tuning with the
exception of two queries, both of which experienced plan digression due to
database version change.

32

Appendix – Additional Tuning
•  Query 4736 ran for 16 minutes at Customer. Due to execution plan changes from
10g to 11g, the query never finished on Exadata.
•  After removing all non-PK indexes, Query 4736 finished in 17 minutes on Exadata
(1 minute longer than on Customer production).
•  The largest table in the query was still using a PK index. After removing this index
(via hint) the query ran in 3 minutes 42 seconds on Exadata (5x faster).


33

Epic Clarity Running on Exadata

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

En vedette

En vedette (15)

Similaire à Epic Clarity Running on Exadata

Similaire à Epic Clarity Running on Exadata (20)

Plus de Enkitec

Plus de Enkitec (20)

Dernier

Dernier (20)

Epic Clarity Running on Exadata