Pythian Group

What: Sydney Oracle Meetup #8 — Exadata Extravaganza

When: Friday, July 17, 2009 5:30 PM (please, make sure to RSVP yes/no/maybe)

Where: Sydney CBD Join meetup for the detailed location.

The topic for this meetup is quite exciting – Oracle Exadata and everything about it. David Centellas, Senior Database Consultant from Oracle will do technical presentation on Exadata and, after the break, we will have a open forum discussion where two Oracle’s Enterprise Architects, Tim Rubin and Chris Jones, will answer our questions and share thir real-world experience.

Schedule:

• 5:30pm – 6:00pm — Networking with food and refreshments
• 6:00pm – 7:00pm — Presentation on Exadata by David Centellas
• 7:00pm – 7:30pm — Break and informal networking
• 7:30pm – 8:30pm — Open Forum based on real-world Exadata experience with David Centellas, Tim Rubin and Chris Jones
• post even — optional gathering in the nearby pub – it’s Friday night in the end!

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At the March Boston MySQL User Group meeting, Jacob Nikom of MIT’s Lincoln Laboratory presented “Optimizing Concurrent Storage and Retrieval Operations for Real-Time Surveillance Applications.” In the middle of the talk, Jacob said he sometimes calls what he did in this application as “real-time data warehousing”, which was so accurate I decided to give that title to this blog post.

The slides can be downloaded in PDF format (1.3 Mb) at http://www.technocation.org/files/doc/Concurrent_database_performance_02.pdf.

This talk discussed how to do real-time retrieval operations while doing concurrent high volume insertion, including:

• How to keep up with 1.5 Mb/second per server incoming data stream
• server hardware comparison between a multi-core AMD Opteron and a multi core Intel Xeon
• MySQL/Postgres comparison
• schema design
• design of the storage/retrieval benchmark
• tuning MySQL

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For those of you who didn’t see the Larry Ellison’s keynote here it is courtesy to Sheeri.

We cut out the HP part but I don’t think anyone will complain. It’s not the best angle but we didn’t get there early in advance to secure the right location for the camera.

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Pythian has a full-featured Oracle Exadata Practice complete with successful implementations and reference customers.

*Updated* see comments.
Exadata — the smart storage server. I am definitely excited about this product, but my point of view is a bit different.

It’s fast, and much faster than anything out there right now. But how many shops will actually need this? How many shops can spend 2.2 million dollars on hardware and equipment?

What are the products, in a nutshell? The Oracle Exadata Storage Server (Data Sheet, PDF):

• 2U Storage “unit” with either 1 TB SAS or 3.3 TB SATA redundant capacity. There is a query processor in the box that can “offload” tasks from the main database server. Primary filtering, decompression, joins, backups.
• Storage units linked to database servers via dual Infiniband offering 20 Gbit/s (2.5 GBytes/sec) bandwidth

The Database Machine (Data Sheet, PDF):

• A standard 42U rack with 8 database servers and 12 Exadata storage servers.
• Pre-installed Linux and Oracle. Pre-configured.
• In 8 servers — a total of 256GB RAM, 64 Intel cores @ 2.66 Ghz, InfiniBand-ed and gigabit-switched.

The cost for one Database Machine: $2.33M ($650,000 + $1,680,000 in software) as grabbed from Larry’s keynote (thank chet) I called the “call us now” phone mentioned on the Oracle Exadata website to ask them for pricing. They had no idea what I was asking about, and I’m still waiting on a salesperson to call me back. (Hint for Oracle — educate your sales staff about new products, just in case I decide to buy one the day after you announce it.)

You have to realize how “cheap” this is. It comes down to $25,000 per core for Oracle EE, RAC, and Partitioning! And extra “free” CPUs for decompressing, filtering and joining, and backups. That’s a good deal. Oh, did I mention you can interconnect several 42U racks?

Back to the main question, what problems does this product solve?

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This article will discuss how to make many-to-many relationships in data warehousing easily queried by novice SQL users using point-and-click query tools.

This is a big problem with Oracle Discoverer-like tools where the metadata layer is basically a set of pre-joined tables from which the user simply clicks on columns and hits the run button. You can create custom complex queries that they can run, but then every query is custom, which defeats the purpose of the tool in the first place.

The design goal is to create a structure that is simple for the end user and which normally translates to something as flat as possible. This article will go through the different methods of implementing many-to-many relationships, and look at their effect on query complexity, especially for someone who use a tool that hides the SQL.

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