Fastest way for this query (What is the best strategy) given a date range

Question

I have a table A that has a startDate and an end dateDate as 2 datetime columns besides some more other columns. I have another table B that has one datetime column call it

Answer 1

I have worked at two companies (both doing time and attendance management systems) that have lots of times with startDate and endDate columns. In my experience there is no good indexes that always works with date ranges.

Try indexes like (startDate, -endDate) and (-endDate, startDate) to see if they help, a lot depends on what the data in the table is like. E.g if you tend to have lots of old rows with an endDate before the dates you are looking for, forcing Sql to use an index based on (endDate, startDate) may help.

Also try using an index that covers all columns that are in your “where” statement, so sql does not need to read the main table until it has worked out what rows to return.

You may have to use index hints, as it is unlikely that the query processor knows enough about the data to make a good choose of indexes – this is one of very few cases when I have had to consider index hints.

Expanding the data, so you have a table that contains (date, rowed) with a row for each date within the date range may be needed. However keeping the "index" table updated is a pain.

If you know that some of your date ranges don't overlap, have a look at Using CROSS APPLY to optimize joins on BETWEEN conditions (E.g an employee's sickness records may not be allowed to overlap)

At the end of the day if you only have several thousand records, a full table scan is not to bad.

Quassnoi subjects using SPATIAL indexes, I have no experience with ”abusing” spatial indexes in this way, but I think it is worth trying. However be very careful if you will have to every support multiply database vendors, as spatial index are rather new. Also you may still need the date columns for reporting tools etc.

(Sooner or later will need to be able to find all rows that overlaps a date range, then it become even harder to get indexes that returns good results.)