Does the order of columns in a PK index matter?
Yes it does.
By default, the primary key constraint is enforced in SQL Server by a unique clustered index. The clustered index defines the logical order of rows in the table. There may be a number of extra index pages added to represent the upper levels of the b-tree index, but the lowest (leaf) level of a clustered index is simply the logical order of the data itself.
To be clear about it, rows on a page are not necessarily physically stored in clustered index key order. There is a separate indirection structure within the page that stores a pointer to each row. This structure is sorted by the clustered index keys. Also, each page has a pointer to the previous and next page at the same level in clustered index key order.
With a clustered primary key of
(RowNumber, DataDate), the rows are logically sorted first by
RowNumber and then by
DataDate - so all rows where
RowNumber = 1 are logically grouped together, then rows where
RowNumber = 2 and so on.
When you add new data (with
RowNumbers from 1 to n) the new rows logically belong inside the existing pages, so SQL Server will likely have to do a lot of work splitting pages to make room. All this activity generates a lot of extra work (including logging the changes) for no gain.
Split pages also start off about 50% empty, so excessive splitting can result in low page density (fewer rows than optimal per page) as well. Not only is this bad news for reading from disk (lower density = more pages to read), the lower-density pages also take up more room in memory when cached.
Changing the clustered index to
(DataDate, RowNumber) means that new data (with, presumably, higher
DataDates than currently stored) is appended to the logical end of the clustered index on fresh pages. This will remove the unnecessary overheads of splitting pages and result in faster load times. Less fragmented data also means that read-ahead activity (reading pages from disk just before they are needed for an in-progress query) can be more efficient.
If nothing else, your queries are much more likely to search on
RowNumber. A clustered index on
(DataDate, RowNumber) supports index seeks on
DataDate (and then
RowNumber). The existing arrangement only supports seeks on
RowNumber (and only then, perhaps, on
DataDate). You might well be able to drop the existing nonclustered index on
DataDate once the primary key is changed. The clustered index will be wider than the nonclustered index it replaces, so you should test to ensure that performance remains acceptable.
When importing new data with
bcp, you may get higher performance if the data within the import file is sorted by the clustered index keys (ideally
(DataDate, RowNumber)) and you specify the
-h "ORDER(DataDate,RowNumber), TABLOCK"
For best data loading performance, you might try to achieve minimally-logged inserts. For more information, see: