Why Oracle Engineered systems - 2013
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The document discusses the benefits of engineered systems over traditional puzzle piece integration. Specifically, it notes that engineered systems allow for cross-domain expertise to work together better by integrating components. It also provides examples of how Exadata storage servers function as smart storage to offload processing from database servers. The document contrasts row and column database formats and how engineered systems allow both formats to coexist and remove tradeoffs.
Why Oracle Engineered systems - 2013
- 1. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.1
- 2. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.2 Why Engineered Systems Oracle Database 12c Cary Millsap and Thomas Kyte http://..... http://asktom.oracle.com/
- 3. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.3 In a Warehouse environment – how many DBA’s can tell you how many GB’s/sec they can transfer from disk to server?
- 4. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.4 In an OLTP environment, what would happen if log writes on a busy system went from an average of 3- 5ms to 7-10ms (or longer)?
- 5. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.5 In a Warehouse environment – how do you “size” your storage? By gigabytes or gigabytes/second?
- 6. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.6 In an OLTP environment, what do you probably wait on more than anything?
- 7. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.7 Puzzle Pieces to be integrated, vs Engineered System
- 8. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.8 Getting cross domain expertise to work together…
- 9. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.9 Exadata is Smart Storage Database Servers – Perform complex database processing such as joins, aggregation, etc. Exadata Storage Servers – Storage Server is smart storage, not a DB node – Search tables and indexes filtering out data that is not relevant to a query – Cells serve data to multiple databases enabling OLTP and consolidation – Simplicity, and robustness of storage appliance Compute and Memory Intensive Processing Data Intensive Processing
- 10. Copyright © 2012, Oracle and/or its affiliates. All rights reserved.10 Until Now Must Choose One Format and Suffer Tradeoffs Row Format Databases vs. Column Format Databases Row Transactions run faster on row format – Example: Insert or query a sales order – Fast processing few rows, many columns Column Analytics run faster on column format – Example : Report on sales totals by region – Fast accessing few columns, many rows SALES SALES
- 11. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Multitenant New architecture for consolidating databases and simplifying operations 11 db1 db2 db3 Self-contained PDB for each application • Applications run unchanged • Rapid provisioning (via clones) • Portability (via pluggability) Shared memory and background processes • More applications per server Common operations performed at CDB level • Manage many as one (upgrade, HA, backup) • Granular control when appropriate
Editor's Notes
- #4: Discuss how people miss this point – the most important point – when building a warehouse. How many times do you have to move the data from disk – over the network – to the machine every day… do some simple math – a 1 GigE card really is a 100 megabyte/sec card. At 100 MB/sec, it’ll take 10 seconds to get a GB, and a thousand times that to get a terabyte (almost 3 hours). Even if you go 10x that (half hour) – it is a long time. We need 10’s of gigaBYTES (we’ll talk about filtering early later – making the 10’s of gigaBYTES even “faster”)
- #5: We would hang – or appear to hang. The LGRW would not respond for a bit – commits continue to happen, the queue builds (end users don’t stop hitting “go”). Machine goes over the edge.
- #7: Single block reads