Currently, I am developing a product that does fairly intensive calculations using MS SQL Server 2005. At a high level, the architecture of my product is based on the concept of ‘runs’ where each time I do some analytics it gets stored in a series of run tables (~100 tables per run).
The problem I’m having is that when the number of runs grows to be about 1,000 or so after a few months, performance on the database really seems to drop off, and specifically simple queries like checking for the existence of tables or creating views can take up to a second to two.
I’ve heard that using multiple filegroups, which I’m not currently doing, could help. Is this true, and if so, why/how would that help? Also, if there are other suggestions, even ones like, use fewer tables, I’m open to them. I just want to speed the database up and hopefully get it in a state where it will scale.
In terms of performance, the big gain in using separate files/filegroups is that it lets you spread your data across multiple physical disks. This is beneficial because with several disks, multiple data requests can be handled simultaneously (parallel is generally faster than serial). All other things being equal, this would tend to benefit performance, but the question of how much depends on your particular data set and the queries you’re running.
From your description, the slow operations you’re concerned about are creating tables and checking for the existence of tables. If you are generating 100 tables per run, then after 1000 runs you have 100,000 tables. I don’t have much experience with creating that many tables in a single database, but you may be pressing the limits of the system tables that track the database schema. In this case, you might see some benefit by spreading your tables across more than one database (these databases could still all live within the same instance of SQL Server).
In general, the SQL Profiler tool is the best starting point for finding slow queries. There are data columns which indicate the CPU and IO cost of each SQL batch, which should point you to the worst offenders. Once you have found the problem queries, I would use the Query Analyzer to generate query plans for each of these queries, and see if you can tell what’s making them slow. Do this by opening a query window, entering your query, and hitting Ctrl+L. A complete discussion of what might be slow would fill an entire book, but good things to look for are table scans (very slow for large tables) and inefficient joins.
In the end, you may be able to improve things simply by rewriting your queries, or you may have to make more broad changes to the table schema. For instance, maybe there’s a way to create only one or a few tables per run, instead of 1000. More specifics about your particular setup would help us give a more detailed answer.
I also recommend this website for lots of tips on how to make things faster:
http://www.sql-server-performance.com/