Question

I’m working in SQL Server 2008 R2

As part of a complete schema rebuild, I am creating a table that will be used to store advertising campaign performance by zipcode by day. The table setup I’m thinking of is something like this:

CREATE TABLE [dbo].[Zip_Perf_by_Day] (
[CampaignID] int NOT NULL,
[ZipCode] int NOT NULL,
[ReportDate] date NOT NULL,
[PerformanceMetric1] int NOT NULL,
[PerformanceMetric2] int NOT NULL,
[PerformanceMetric3] int NOT NULL,
and so on... )

Now the combination of CampaignID, ZipCode, and ReportDate is a perfect natural key, they uniquely identify a single entity, and there shouldn’t be 2 records for the same combination of values. Also, almost all of my queries to this table are going to be filtered on 1 or more of these 3 columns. However, when thinking about my clustered index for this table, I run into a problem. These 3 columns do not increment over time. ReportDate is OK, but CampaignID and Zipcode are going to be all over the place while inserting rows. I can’t even order them ahead of time because results come in from different sources during the day, so data for CampaignID 50000 might be inserted at 10am, and CampaignID 30000 might come in at 2pm. If I use the PK as my clustered index, I’m going to run into fragmentation problems.

So I was thinking that I need an Identity ID column, let’s call it PerformanceID. I can see no case where I would ever use PerformanceID in either the select list or where clause of any query. Should I use PerformanceID as my PK and clustered index, and then set up a unique constraint and non-clustered indexes on CampaignID, ZipCode, and ReportDate? Should I keep those 3 columns as my PK and just have my clustered index on PerformanceID? (<- This is the option I’m leaning towards right now) Is it OK to have a slightly fragmented table? Is there another option I haven’t considered? I am looking for what would give me the best read performance, while not completely destroying write performance.

Some actual usage information. This table will get written to in batches. Feeds come in at various times during the day, they get processed, and this table gets written to. It’s going to get heavily read, as by-day performance is important around here. When I fill this table, it should have about 5 million rows, and will grow at a pace of about 8,000 – 10,000 rows per day.

Answer 1

In my experience, you probably do want to use another INT Identity field as your clustered index key. I would also add a UNIQUE constraint to that one (it helps with execution plans).

A big part of the reason is space – if you use a 3 field key for your clustered index, you will have all 3 fields in every row of every non-clustered index on that table (as your clustered index row identifier). If you only plan to have a couple of indexes that isn’t a big deal, but if you have a lot of them it can make a big difference. The more data per row, the more pages needed and the more IO you have.

Fragmentation is a very real issue that can cause major performance problems, especially as the table grows.

Having that additional cluster key will also mean writes will be faster for your inserts. All new rows will go to the end of your table, which means existing rows won’t be touched or rearranged.

If you want to use those three fields as a FK in other tables, then by all means have them as your PK.

For the most part it doesn’t really matter if you ever directly reference your clustered index key. As long as it is narrow, increasing, and unique you should be in good shape.

EDIT:

As Damien points out in the comments, if you will be filtering on single fields of your PK, you will need to have an index on each one (or always use the first field in the covering index).