One of the great sessions at Q Days 2010 San Diego (yesterday!) was “QlikView Under the Hood,” presented by Daniel English of the Product team.
I’m a scientist at heart and really like to know how things tick. Sure, it’s rewarding to deliver a stunning dashboard to my business partner and hear them say “wow” or “we didn’t have this type of intell before” … but, in the back of my mind I’m wondering “how much RAM is this really consuming?” Â 🙂
So, this session addressed some questions. The two big takeaways for me were:
- QV Server (QVS) caching – if you happen to be sitting around, watching the Perf Mon on your QVS machine you will likely notice RAM activity growing and growing. And then freak out that QVS is leaky. Well, it turns out, this is exactly the correct behavior for QVS. What happens is that when a document is opened, and the user starts clicking or changing tabs, each of those results (aggregations) get cached. And QVS will continue to cache until all the available RAM is consumed or the document times-out from disuse. (Or if the QVS is rebooted – duh.) If another document comes into scope, or another user starts asking different question of the same document, then QVS starts dropping cached aggregates to make room for the new stuff. (How it drops it was not specified – oldest first? or least re-used first?)
- “Associative” – what does this really mean? Is it just marketing hype? Without debating the semantics, QlikView’s model is a very unique, very novel concept. Here’s how I think of it, in good old-fashioned SQL terms… Imagine I write a SQL query with every table in my data mart – every fact, every dimension. And I have join conditions to join every table (using a full outer join). And then I start dynamically changing bits of the WHERE clause. That is what associative analysis means. And we change the WHERE clause in QlikView, figuratively speaking, by clicking on selectors.
So yeah, Associative really does mean something different than most SQL query tools. Unless of course your SQL tools allows you to query every table in your mart simultaneously 🙂