I wanted to mention my company KPI Partners’ blog site at www.kpipartners.com/blog. Several of my collegues post articles there on a variety of topics in their expertise, plus its used as a vehicle for announcing a heavy does of webinars. In fact, I’m giving my BI Apps Performance Layer talk on Wed April 24th.
Please stop by and check it out, or even better yet – subscribe.
Ok so I put a provocative title on this post for a reason. This post will explore why some of Kimball’s concepts may be out dated when newer query generation or database capabilities are taken into account. Specifically, I’m going to discuss the OBI concept of Nested Aggregation, also known as Dimension Based Aggregation, in detail. Using this OBI Modeling technique you can relax a bit on one of the Kimball Dimensional Modeling rules. I’ll show how it works in a simplified manner, plus identify some things to be careful with and how it does not alleviate you from doing real modeling work. Read the rest of this entry
I thought I’d post my presentation on QA (testing) that I delivered this week at the BIWA Summit near Oracle HQ in California. The preso is based off of the recent QA posts I did, with a bit more silly graphics on top of it. The one take away from the preso is that some people prefer the term testing as opposed to QA. Good to know. Anyway, enjoy!
BTW, the event focused heavily on the future of BI and Data Warehousing. Essentially, whatever we are doing now is going to radically change to include many new types of data from different places and sources, plus what kinds of analysis we do will also be greatly enhanced. OBI is layering on top of a whole plethora of Oracle’s Analytical technologies, including: Essbase, EPM, HCM, OLAP, RTD, Endeca and R. The OBI server or UI will have hooks into just about everything you can think of, making some advanced capabilities available to dashboard users. We’ll see how it actually plays out, but in the future some pretty heavy stuff will be available in the dashboard.
I’ll be presenting at the Oracle BIWA Summit on Thursday of this week in Redwood Shores CA near Oracle HQ. I’ll be discussing boring old QA. The presentation is based on the articles I recently did below on QA. Not sure how this will go over as this preso is less technical than a lot of the other content. However, in my opinion it is very useful stuff to know – everyone needs to go through a QA cycle, right?
Anyway, stop by and bug me if you like.
I’ve been spending a lot of time recently working on performance tuning projects. Sometimes the BI apps are slow, sometimes it’s custom, sometimes it’s a mix. I’ve gotten the chance to see what works in both Oracle and SQL Server.
My conclusion about both of these databases is that they are like a cat or dog that gets fooled when you play hide the ball; they aren’t very smart sometimes. The only way you can really truly ensure database engines, even modern advanced ones, do things the right way to is to make it as simple and easy for them to understand as possible. I guess this is nothing new; the KISS principle comes from Kelly Johnson of The Lockheed Skunk Works, the guys who created the SR-71 Blackbird spy plane. I think he knew a few things about complexity in systems and how they tend to break or become difficult to maintain. (BTW more on that topic as it pertains to OBI and the BI Apps at a later date.)
As I’ve been looking at performance tuning many reports and queries over these days, I find that a lot of time is spent trying to get the database to do the smart thing. Too much time in fact. Usually this is due to some small piece of non-simple SQL that causes the problem. In more unusual cases I’ve seen something on one table completely break down the query plan, even something that should be trivial and very innocuous.
<Vent>For example, not being able to use an index on a table with 2,000 records should not radically alter the query plan, but in fact it will do that on you. After you spend hours upon hours with it, after you’ve called up the DBA for help to dig into the extreme nitty-gritty details of the query plan, you make a change it works for that one query but not any others. Then you decide to write this article because you’ve spend 10 hours on something so minuscule that in the end doesn’t even work consistently. If only the query had been clean to begin with…</Vent>
In this brief article I’m just going to lay out a few things to consider to help make you system simpler for the database engine to understand and therefore do a better, faster job in answering a query.
In this post I am going to explore some performance issues related to OBI’s time series functions. Released back in OBI 10g, the ToDate() and Ago() functions brought a significant improvement to the process of easily creating a variety of time series metrics. In older versions of Siebel Analytics, creating time series was a very manual effort involving a lot of aliases and special joins that could at time become a little confusing to the developer. They did have a wizard called the Time Series Wizard to assist, but if you are like me you never use wizards J. The Time series functions however solved that; using them is a piece of cake, requiring only a minor enhancement to the Date dimension.
All is rosy with the world then, correct? Well not so fast. The reality is that these functions do some very strange things behind the scenes in order for them to work properly. So strange in fact that the database engine typically has some difficulty figuring out what to do. One thing I’ve learned over the years when it comes to database engine performance – keep it simple if you want it to run fast.
As it turns out these strange things that OBI does for the Time Series functions in fact cause a decent performance hit when compared with the old technique. This short post will discuss this in more depth. Read the rest of this entry
The fall means lots of things to lots of people. To me it means baseball playoffs, football and Oracle Open World. I’m not presenting this year – I was just too swamped on a long project to put anything together, so I’ll just enjoy some of the sessions. I’m going to be heavy on the performance stuff, whether its database features, Exadata and of course Exalytics. In any event, I’ll spend some time with my KPI Partners colleagues at the booth in Moscone South, @2315. Hope to see some of you there!
The BI Apps from Oracle present customers with a nice head start to getting their BI environment up and running. Financial Analytics, HR Analytics, Supply Chain Analytics, etc. all come pre built with much of the code and reports you’ll need to build to support your business. But for many customers they just are too slow for their user community while running dashboards, reports and ad-hoc queries. In an era where an internet search engine can give you what you want in one second, reports running for a minute or more are just not acceptable.
In this post I’ll discuss some of the inherent performance limitations in the BI Apps and what you should do about it. Note the vast majority of customers really don’t have a performance problem with their system, but you can always deliver reporting content faster. If you are running at 15 seconds per page, wouldn’t 5 seconds be that much better? The performance problem really lies with some large customers with larger data volumes. It is here where the BI Apps design can be enhanced with more performance in mind.
I’ve written about OBI performance a few times in the past, and I’m sure there will be more to come. As a refresher, here are a few other posts to take a look at:
- Achieving Good Performance with OBIEE
- OBI Performance Preso
- Performance Tuning Financial Analytics
- Stitch Joins