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Epic Clarity Running on Exadata
- 1. Optimize the Performanceof 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
- 2. Agenda • Introductions • Whyoptimize? • 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 © 2013 Oracle Corporation 2
- 3. Exadata Delivers HigherValue 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? © 2013 Oracle Corporation • • • • • 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
- 4. Business Users WillRealize 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 © 2013 Oracle Corporation 4
- 5. Customers Confirm HigherBusiness 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 © 2013 Oracle Corporation Research Finance Education Provide financial reports to analysts sooner for regular reporting periods 5
- 6. Oracle Exadata Extreme OLTP/DWPerformance © 2012 Oracle Corporation 6
- 7. Exadata Unified WorkloadTransformation Single Machine for… • OLTP • Data Warehousing • ETL • Query parallelism OLTP with Analytics and Parallelism of Warehousing Warehousing with Interactivity, Availability, and Security of OLTP © 2013 Oracle Corporation 7
- 8. Exadata Innovations • HybridColumnar 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 © 2013 Oracle Corporation uncompressed compress primary DB standby test dev backup 8
- 9. Oracle Exadata: ExtremePerformance 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) © 2013 Oracle Corporation 9
- 10. Compression Ratio ofReal-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 © 2013 Oracle Corporation 10 20 30 10
- 11. Secure Database Machine • Movesdecryption from software to hardware • Over 5x faster • • © 2013 Oracle Corporation Near zero overhead for fully encrypted database Queries decrypt data at hundreds of Gigabytes/ second 11
- 12. Epic Clarity onExadata Benchmark 1 Details © 2012 Oracle Corporation 12
- 13. Observations - EpicClarity 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 © 2013 Oracle Corporation 13
- 14. Epic Clarity onExadata 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 © 2013 Oracle Corporation 14
- 15. Query Execution • Customersupplied 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 © 2013 Oracle Corporation 15
- 16. Results – QueryExecution Average Performance Improvement – 91x © 2013 Oracle Corporation 16
- 17. Epic Clarity onExadata Benchmark 2 Details © 2012 Oracle Corporation 17
- 18. Epic Clarity onExadata 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 © 2013 Oracle Corporation 18
- 19. Results – QueryExecution 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 © 2013 Oracle Corporation 19
- 20. Results – QueryExecution 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 © 2013 Oracle Corporation 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
- 21. Results – HCCCompression 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 © 2013 Oracle Corporation 3 to 1 10 to 1 21
- 22. Demo and Conclusions ©2013 Oracle Corporation 22
- 23. Conclusions 1• Epic Clarityworkload 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 © 2013 Oracle Corporation 23
- 24. Epic Clarity TargetPlatforms Epic • Target platform definition • Supported platforms • Customer demand • Industry trends • Exadata in-house at Epic © 2013 Oracle Corporation 24
- 25. Summary and NextSteps © 2012 Oracle Corporation 25
- 26. Summary What can YOUdo 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 © 2013 Oracle Corporation 26
- 27. Next Steps Join usat 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 © 2013 Oracle Corporation 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
- 28. Q&A © 2012 OracleCorporation 28
- 29. For More Information • • • • • Visit: Read: Join: Follow: Call: ©2013 Oracle Corporation Oracle Healthcare Website Oracle Healthcare Solutions Oracle Healthcare on Facebook Oracle Healthcare on Twitter Oracle Healthcare Representative 29
- 30. © 2013 OracleCorporation 30
- 31. Appendix – QueryExecution 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. © 2013 Oracle Corporation 31
- 32. Appendix – QueryExecution 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. © 2013 Oracle Corporation 32
- 33. Appendix – AdditionalTuning • 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). © 2013 Oracle Corporation 33