Experimental Thoughts

In the last article, I argued that:

• A schedule conflict is a typical business problem.
• The later you try to resolve a schedule conflict, the more costly it is to resolve.
• In particular, there is a big jump in the cost the moment after conflicting data is recorded.
• Therefore, it’s best for the DBMS itself to enforce the constraint, because only the DBMS can avoid the conflict effectively before the conflict is recorded.

Then, I opened up a discussion to see how people are dealing with these schedule conflicts. In the comments I received at the end of the article, as well as other anecdotes from conferences, user groups, mailing lists, and my own experience, the solutions fall into a few categories:

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I’ve been interested in temporal data and relational databases for quite some time. There are going to be at least two people talking about temporal data at PostgreSQL WEST in Seattle: Scott Bailey and me. See the talk descriptions.

In the past, I’ve worked on a temporal extension to PostgreSQL that implements the PERIOD data type. This is a data type that offers both a definite beginning and a definite end time, which is important for describing things that happen over a period of time, rather than instantaneously. Trying to use separate attributes for “start” and “end” is bad for a number of reasons, and will certainly be addressed in a subsequent blog entry. For now, I’ll just say that I believe the PERIOD data type is fundamentally important for handling all kinds of time data, which I believe is a common problem.

At WEST, I’ll be presenting my progress on temporal keys. Temporal keys are used to prevent overlapping periods of time — a schedule conflict — by using an index and following the same concurrent behavior as UNIQUE with minimal performance cost (one extra index search, to be precise).

Temporal keys cannot be expressed in PostgreSQL 8.4, unless you resort to triggers and a full table lock (ouch!). So, additional backend support is required. This is accomplished in my patch for operator exclusion constraints, which are a more general way of using arbitrary operators and index searches to enforce a constraint. I plan to do what’s required for the patch to be accepted in PostgreSQL 8.5.

Temporal modeling is a common problem. It seems like almost every PostgreSQL conference has had at least one talk on the matter, so we know there is some demand for improvement. If you’re interested, I hope you come to WEST and chat with Scott or I, and let’s see if we can come up with some real solutions.