4. How Did We Get Here?
Exadata V1 - September 2008
•
HP Hardware / Data Warehouse only
•
Saw it, decided to wait
Exadata V2 - September 2009
•
Local Customer Purchased V2 Full Rack
•
Working with customer, saw the awesome potential
•
Six months later, purchased our V2 Quarter Rack
Exadata X2 - September 2010
•
Upgraded our V2 Quarter with an X2 Quarter
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5. Proofs of Concept
POC’s are very popular
Results are often too good…
Exadata has an Acceptance Cycle:
•
Denial
•
Anger
•
Depression
•
Acceptance
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6. How is Exadata being Used?
•
39 Companies
•
Range from Non-Rac to 16 Node RAC
•
Baby Exadata to X2-2 Full and X2-8 / X3-8 Full
•
More High Capacity Drives than High Performance
Data ERP Mixed
Consolidation Warehouse eBiz DW / OLTP OLTP
Peoplesoft
5% 40% 13% 33% 9%
Retail, Energy, Marketing, Healthcare, etc
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7. Organizational Challenges
Who Should Manage The Beast
•
General Thinking is DBA’s (DMA’s ?)
•
Patching Requires More Knowledge Than Most DBAs Currently Have
-
Linux
-
Network
-
Hardware
-
Storage
•
Best Approach for Most is Combination of DBA / Sysadmin
•
SAN Guys are Out of the Picture
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8. Top 4 reasons for Choosing Exadata
•
Consolidation
•
Performance
•
High Availability
•
Implementation Platform
-
Rapid Instantiation
-
Number of instances
-
Fast clones
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9. Top Apps running on Exadata
•
Custom Data Warehouse / OLTP
•
PeopleSoft
•
EBS
•
OBI Apps
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10. Alternatives Considered
•
Netezza
•
Teradata
•
Roll your own
-
Traditional Hardware / Storage
-
Solid state disk
-
InfiniBand
-
Flash cache
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11. Common Configurations
•
¼ Rack – High capacity drives
•
Auto DOP – Off
•
Buffer Cache– Smaller than on non-Exadata
•
Flash – Popular tables pinned
•
Huge Pages – Enabled (no AMM)
•
Backups – RMAN to RECO then to tape
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12. Common Migration Strategies
Logical
•
Data Pump
•
exp / imp
•
Golden Gate
•
CTAS Across DBLink
Physical
•
RMAN
•
Transportable Tablespaces
•
Dataguard Physical Standby
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13. Typical Performance Results
Current Exadata Exadata Exadata Parallel Exadata
System 8G SGA 15G SGA 40G SGA Degree Improvement
8G SGA Factor (based on
8G SGA)
Query 1 46:13.00 00:00.02 00:00.02 00:00.02 24 138,650
Query 2 58:55.00 00:00.05 00:01.66 00:01.94 24 70,700
Query 3 32:24.00 11:47.44 10:29.40 08:20.10 24 3
Query 4 06:57.00 00:15.81 00:15.45 00:15.80 24 26
Query 5 8:45:12.00 13:17.68 10:36.32 11:05.40 24 40
Query 6 14:04.00 00:25.14 00:11.60 00:11.83 24 34
Query 7 04:47.00 00:16.46 00:16.80 00:18.97 24 17
Query 8 08:33.00 00:36.71 00:35.31 00:35.22 12 14
Query 9 6:38:10.00 02:50.14 02:49.07 02:48.65 Serial 140
Query 10 19:59.00 10:43.30 06:48.19 03:33.01 12 2
Improvement factors are based on the current system
Compared to the Exadata with an 8G SGA
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14. Indexing Strategies
•
Single Row Access (OLTP) Needs Indexes
•
Challenge is to Use Indexes When
Appropriate
•
You Probably Need Fewer Indexes
•
You May Have to Get Creative
-
optimizer_use_invisible_indexes
-
db_multi_block_read_count
-
optimizer_index_cost_adj
-
system stats (Exadata mode) ???
•
Normal plan control mechanisms
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15. Typical Compression Strategies
•
HCC Provides Exceptional Compression Ratios
-
10X is pretty good guess
-
6X – 60X in Practice
•
Oddly Enough Many are Not Using HCC
•
HCC Not Appropriate for Active Data
•
HCC Complements Partitioning
-
Requires Direct Path Loads
-
Update Move
-
Single Row Update Locks Entire CU
-
Falls Back to OLTP
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