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August 2016

OOW16 – The Park Central

Some of my sessions this year at OpenWorld are at the Park Central.

So…you’ve arrived at the Moscone Center, and you’re wondering “How do I get to the Park Central ?  After all…that’s where all of the hot talks will be” Smile

Here’s my simple guide:

1) From Howard St, head up the stairs next to the Moscone Center entrance


Stop Constantly Adding Disks To Your ASM Disk Groups. Resize Your ASM Disks On All-Flash Array Storage. Adding Disks Is Really “The Y2K Way.” Here’s Why.

This blog post is centered on All-Flash Array(AFA) technology. I mostly work with EMC XtremIO but the majority of my points will be relevant for any AFA. I’ll specifically call out an array that doesn’t fit any of the value propositions / methods I’m writing about in this post.

Oracle Automatic Storage Management (ASM) is a very good volume manager and since it is purpose-built for Oracle Database it is the most popular storage presentation model DBAs use today. That is not to say alternatives such as NFS (with optional Direct NFS) and simple non-clustered file systems are obsolete. Not at all. However, this post is about adding capacity to ASM disk groups in an all-flash storage environment.

Adaptive Cursor Sharing Fail

Here is another example (besides the fact that Adaptive Cursor Sharing only gets evaluated during a PARSE call (still valid in 12c) and supports a maximum of 14 bind variables) I've recently come across at a client site where the default implementation of Adaptive Cursor Sharing fails to create a more suitable execution plan for different bind variable values.Broken down to a bare minimum the query was sometimes executed using non-existing values for a particular bind variable, but other times these values were existing and very popular. There were two suitable candidate indexes and one of them appeared to the optimizer more attractive in case of the "non-existing" value case.

Speaking at OOW 2016 on Sunday on Active Session History

Session ID: UGF3110

Advanced Active Session History Analytics
Moscone West—3020
09/18/16, 03:30:00 PM – 04:15:00 PM



The Rosetta Stone of Database Platforms

This is a living document that I will continue to update and will add new database platforms to as I go along in my career.  I spend a lot of time translating database platforms I’ve worked in for all tiers of the technical business.  It just seems natural that we might need a location on the web where that information is kept.

A bumper OpenWorld 2016 for me…

My first OpenWorld was in the Australia in ..well… I’m not sure when Smile but it might have even been the late 1990’s.  Time flies.

But 2016 will be my first OpenWorld as an Oracle employee…and hence, I’ll be busy Smile

Hopefully you can come along to some or all of the sessions I’m involved in…or you can probably catch me during the week at the OTN lounge.

I’ll blog more shortly on how I can think you can have an awesome OpenWorld….because I know will !


OmniFocus and AppleScript

I’m new to Mac, but most know that anything you give me, I’m looking to automate any task that I can get my hands on.  As busy as my life is with demands, if I can get a computer to do the work for me, I will.  Disaster strikes when anything is too manual in my life-

Basicfile LOBs 2

There are probably quite a lot of people still using Basicfile LOBs, although Oracle Corp. would like everyone to migrate to the (now default) Securefile LOBs. If you’re on Basicfile, though, and don’t want (or aren’t allowed) to change just yet here are a few notes that may help you understand some of the odd performance and storage effects.

Host I/O Queue Depth with XtremIO and SLOB Session Count. A Granular Look.

In my recent post about aggregate host I/O queue depth I shared both 100% SQL SELECT and 20% SQL UPDATE test results (SLOB) at varying LUN (ASM disk) counts. The LUNs mapped to XtremIO volumes but the assertions in that post were really applicable in most All-Flash Array situations.

I received quite a bit of email from readers about the granularity of session counts shown in the charts in that post. Overwhelmingly, folks asked to see more granular data. It so happens that the charts in that post were a mere snippet of the test suite results so I charted the full data set and am posting them here.

Month End

A question about parallel query and cardinality estimates appeared on OTN a little while ago that prompted me to write this note about helping the optimizer do the best job with the least effort.  (A critical point in the correct answer to the original question is that parallel query may lead to “unexpected” dynamic sampling, which can make a huge difference to the choice of execution plans, but that’s another matter.)

The initial cardinality error in the plan came from the following predicate on a “Date dimension” table: