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Copyright © 2015, Oracle and/or its affiliates. All rights reserved.
Exadata Smart Scan
What is so smart about it?
presented by
Uwe Hesse
Senior Principal Instructor
Oracle University
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 2
@UweHesse
Exadata Quarter Rack – Hardware Viewpoint
Full
Rack
Half
Rack
Quarter
Rack
Multiple
Racks
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 3
@UweHesse
Technical Specifications
They change rapidly
X5-2 is now current
See here:
http://www.oracle.com/technetwork/database/exa
data/overview/index.html
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 4
@UweHesse
Exadata Quarter Rack – Database Viewpoint
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 5
@UweHesse
Database Viewpoint is unchanged
•Competitor: “Exadata is still Oracle!”
•Right – that is actually a good thing because:
•No change is needed for the Database Design
•No change is needed for the Application Code
•Migration to Exadata is relatively easy therefore
•DBA knowledge remains valid
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 6
@UweHesse
Exadata in the Marketplace
Rapid adoption in all geographies and industries
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 7
@UweHesse
Classic Database I/O and SQL Processing Model
SELECT customer_id
FROM orders
WHERE order_amount>20000;
Extents identified
I/O issued I/O executed:
10 GB returned
SQL processing:
2 MB returned
Rows returned
1
2
3 4
5
6
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 8
@UweHesse
Exadata Smart Scan Idea
• “The fastest way of doing something is not to do it”
• Do not deliver the whole Data Volume up to the DB Layer!
• Instead, filter resp. project already on the Storage Layer!
• We want DB Intelligence built into the Storage Layer ...
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 9
@UweHesse
Remove the Storage Network Bottleneck
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 10
@UweHesse
Exadata Smart Scan Model
SELECT customer_id
FROM orders
WHERE order_amount>20000;
iDB command
constructed
and sent to Exadata cells
SQL processing
in Exadata cells
2 MB returned
to server
Consolidated result
set built from all
Exadata cells
Rows returned
1
2
3 4
5
6
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 11
@UweHesse
Exadata Smart Scan
• Predicate filtering:
– Only the requested rows are returned to the database server
rather than all the rows in a table.
• Column filtering:
– Only the requested columns are returned to the database
server rather than all the columns in a table.
– For example:
SQL> SELECT col1,col2 FROM t WHERE condition;
http://uhesse.com/2011/01/19/exadata-part-i-smart-scan/
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 12
@UweHesse
Smart Scan Prerequisites
• Smart Scan is only possible for Full Table Scans or Full
Index Scans.
• Smart Scan can only be used for Direct-Path Reads:
• Direct-path reads are automatically used for parallel queries.
• Direct-path reads may also be used for serial queries.
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 13
@UweHesse
Exadata Smart Scan
• Join processing:
– Star join processing is performed within Exadata Storage
Server
• Scans on TDE encrypted data
• Scans on HCC compressed data
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 14
@UweHesse
Reduced Warehouse Size
Better Performance
Exadata Hybrid Columnar Compression:
Overview
Warehouse Compression
• 10x average storage savings
• 10x scan I/O reduction
• Optimized for query performance
Archival Compression
• 15x average storage savings
– Up to 50x on some data
• Greater access overhead
• For cold or historical data
Optimized for Speed
Can mix compression types by partition for
Information Life Cycle Management
Optimized for Space
Reclaim Disks
Keep Data Online
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 15
@UweHesse
Exadata Hybrid Columnar Compression
Data Organization
• A compression unit is a logical structure spanning multiple
database blocks.
• Each row is self-contained within a compression unit.
• Data is organized by column during data load.
• Each column is compressed separately.
• Smart Scan is supported.
Compression Unit
Block Header
CU Header
C1
C2
Block Header
C2
C3
C4
C5
Block Header
C5
C6
Block Header
C8C7
http://uhesse.com/2011/01/21/exadata-part-iii-compression/
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 16
@UweHesse
Exadata Storage Index Idea
•“The fastest way of doing something is not to do it”
•Even faster than offload scanning to the Storage
Layer:
•Exclude areas from scanning when we know
the requested Data can‘t be there
http://uhesse.com/2011/01/20/exadata-part-ii-storage-index/
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 17
@UweHesse
Storage Index with Partitions: Example
• Queries on SHIP_DATE do not benefit from ORDER_DATE
partitioning:
– However, SHIP_DATE is highly correlated with ORDER_DATE.
• Storage index enhances performance for queries on
SHIP_DATE:
– Takes advantage of the ordering created by partitioning
ORDER# ORDER_DATE
(Partition Key)
SHIP_DATE ITEM
1 2007 2007
2 2008 2008
3 2009 2009
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 18
@UweHesse
Smart Scan related Statistics & Wait-Events
Important Statistics:
cell physical IO interconnect bytes
cell physical IO interconnect bytes returned by smart scan
cell physical IO bytes saved by storage index
Important Wait-Events:
cell smart table scan
cell smart index scan
cell single block physical read
cell multiblock physical read
http://uhesse.com/2011/07/06/important-statistics-wait-events-on-exadata/
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 19
@UweHesse
Benefits Multiply
Less with Exadata
Hybrid Column
Compression
Multiple terabytes of user
data normally require
multiple terabytes of I/O.
Even less with
partition pruning
Storage index skips
worthless I/O.
Smart Scan filters the
remaining Candidate
Data and reduces the
Data Volume sent to
the Database Layer.
Results in
real-time on
Database
Machine
Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 20
@UweHesse
The smartest thing about Smart Scan
If you ask me:
Smartest thing is that it works transparently together
with the same Oracle Database Code
as used on Non-Exadata platforms
Transparently except that it is 10 times faster
„Exadata is still Oracle!“ Love it :-)

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Exadata Smart Scan - What is so smart about it?

  • 1. Copyright © 2015, Oracle and/or its affiliates. All rights reserved. Exadata Smart Scan What is so smart about it? presented by Uwe Hesse Senior Principal Instructor Oracle University
  • 2. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 2 @UweHesse Exadata Quarter Rack – Hardware Viewpoint Full Rack Half Rack Quarter Rack Multiple Racks
  • 3. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 3 @UweHesse Technical Specifications They change rapidly X5-2 is now current See here: http://www.oracle.com/technetwork/database/exa data/overview/index.html
  • 4. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 4 @UweHesse Exadata Quarter Rack – Database Viewpoint
  • 5. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 5 @UweHesse Database Viewpoint is unchanged •Competitor: “Exadata is still Oracle!” •Right – that is actually a good thing because: •No change is needed for the Database Design •No change is needed for the Application Code •Migration to Exadata is relatively easy therefore •DBA knowledge remains valid
  • 6. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 6 @UweHesse Exadata in the Marketplace Rapid adoption in all geographies and industries
  • 7. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 7 @UweHesse Classic Database I/O and SQL Processing Model SELECT customer_id FROM orders WHERE order_amount>20000; Extents identified I/O issued I/O executed: 10 GB returned SQL processing: 2 MB returned Rows returned 1 2 3 4 5 6
  • 8. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 8 @UweHesse Exadata Smart Scan Idea • “The fastest way of doing something is not to do it” • Do not deliver the whole Data Volume up to the DB Layer! • Instead, filter resp. project already on the Storage Layer! • We want DB Intelligence built into the Storage Layer ...
  • 9. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 9 @UweHesse Remove the Storage Network Bottleneck
  • 10. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 10 @UweHesse Exadata Smart Scan Model SELECT customer_id FROM orders WHERE order_amount>20000; iDB command constructed and sent to Exadata cells SQL processing in Exadata cells 2 MB returned to server Consolidated result set built from all Exadata cells Rows returned 1 2 3 4 5 6
  • 11. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 11 @UweHesse Exadata Smart Scan • Predicate filtering: – Only the requested rows are returned to the database server rather than all the rows in a table. • Column filtering: – Only the requested columns are returned to the database server rather than all the columns in a table. – For example: SQL> SELECT col1,col2 FROM t WHERE condition; http://uhesse.com/2011/01/19/exadata-part-i-smart-scan/
  • 12. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 12 @UweHesse Smart Scan Prerequisites • Smart Scan is only possible for Full Table Scans or Full Index Scans. • Smart Scan can only be used for Direct-Path Reads: • Direct-path reads are automatically used for parallel queries. • Direct-path reads may also be used for serial queries.
  • 13. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 13 @UweHesse Exadata Smart Scan • Join processing: – Star join processing is performed within Exadata Storage Server • Scans on TDE encrypted data • Scans on HCC compressed data
  • 14. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 14 @UweHesse Reduced Warehouse Size Better Performance Exadata Hybrid Columnar Compression: Overview Warehouse Compression • 10x average storage savings • 10x scan I/O reduction • Optimized for query performance Archival Compression • 15x average storage savings – Up to 50x on some data • Greater access overhead • For cold or historical data Optimized for Speed Can mix compression types by partition for Information Life Cycle Management Optimized for Space Reclaim Disks Keep Data Online
  • 15. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 15 @UweHesse Exadata Hybrid Columnar Compression Data Organization • A compression unit is a logical structure spanning multiple database blocks. • Each row is self-contained within a compression unit. • Data is organized by column during data load. • Each column is compressed separately. • Smart Scan is supported. Compression Unit Block Header CU Header C1 C2 Block Header C2 C3 C4 C5 Block Header C5 C6 Block Header C8C7 http://uhesse.com/2011/01/21/exadata-part-iii-compression/
  • 16. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 16 @UweHesse Exadata Storage Index Idea •“The fastest way of doing something is not to do it” •Even faster than offload scanning to the Storage Layer: •Exclude areas from scanning when we know the requested Data can‘t be there http://uhesse.com/2011/01/20/exadata-part-ii-storage-index/
  • 17. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 17 @UweHesse Storage Index with Partitions: Example • Queries on SHIP_DATE do not benefit from ORDER_DATE partitioning: – However, SHIP_DATE is highly correlated with ORDER_DATE. • Storage index enhances performance for queries on SHIP_DATE: – Takes advantage of the ordering created by partitioning ORDER# ORDER_DATE (Partition Key) SHIP_DATE ITEM 1 2007 2007 2 2008 2008 3 2009 2009
  • 18. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 18 @UweHesse Smart Scan related Statistics & Wait-Events Important Statistics: cell physical IO interconnect bytes cell physical IO interconnect bytes returned by smart scan cell physical IO bytes saved by storage index Important Wait-Events: cell smart table scan cell smart index scan cell single block physical read cell multiblock physical read http://uhesse.com/2011/07/06/important-statistics-wait-events-on-exadata/
  • 19. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 19 @UweHesse Benefits Multiply Less with Exadata Hybrid Column Compression Multiple terabytes of user data normally require multiple terabytes of I/O. Even less with partition pruning Storage index skips worthless I/O. Smart Scan filters the remaining Candidate Data and reduces the Data Volume sent to the Database Layer. Results in real-time on Database Machine
  • 20. Copyright © 2011, Oracle and/or its affiliates. All rights reserved.4 - 20 @UweHesse The smartest thing about Smart Scan If you ask me: Smartest thing is that it works transparently together with the same Oracle Database Code as used on Non-Exadata platforms Transparently except that it is 10 times faster „Exadata is still Oracle!“ Love it :-)