After reading the Questions and Answers from this website about indexes, a question came to my mind.

What if, one is using a time dimension table with the lower level of granularity being the day. Where should one put the indexes ?

Randy Melder in the question : What does “index” means on RDBMS ? said :

Think of an index as "table of contents"... that is an ordered list of pointers to positions in a file, aka offsets

In the case of the time dimension, most data research might be done either for a specific day, a specific week, a specific month or a specific quarter if the time table stores all the day for a unique year.

My question is : Should one put indexes for all those fields ?

Day is suppose to be unique so for this one I understand perfectly the use of indexes. But a week id will have 7 occurences, a month id will have 30/31 occurences, a quarter id will have more or less 120 occurences.

  • Should one still put indexes for those fields ?
  • Will it still be useful?

I am asking you that because in the same question, David Spillett said :

Adding too many indexes can be a bad optimisation of course, as the extra space used to store the indexes (and the IO-load to maintain them if your DB sees many write operations) may be a worse problem than the slightly less optimal read queries, so don't over-do it.

So what would be the best considerations for the time dimension case ?

4 Answers 4


You likely won't run into the issues of write problems, as I assume this would be something created once (or once per year), and then not touched.

But using an index will likely be a hinderance if you're searching by week ... The problem is, if the index is used, it might scan that first, and then grab each record out of the table individually, which when you're pulling out more than about 5-20% of the records, it's typically faster to do a full table scan, and then drop the records you don't care about.

I don't know of any major RDBMSes that don't optimize for this when it's well-distributed data. If it's not well distributed (eg, one of the values in a column occurs 95% of the time, but there's also other possible values), you may have to compute histograms on the table and not use a placeholder for the value when searching, so that the query optimizer has the value being searched for when generating the execution plan.

I'd likely not index day of week. I'd check my database's documentation to see what their tradeoff is for indexed reads vs. full table scans to see if I'd index the day of the month or month of the year. I'd likely index DOY/day of year if present (which sounds like it's your unique index, anyway)


An index doesn't have to be unique to be useful, so the answer is it depends. If your queries benefit from the presence of the index then they may be a worthwhile addition. I don't know that there should be any special guidelines with regard to time columns. Treat them like any other columns and index them based on usefulness to queries.

  • Does anyone other than me hear Paul Randal's voice every time they say or read "it depends" with regards to databases? :p
    – AndrewSQL
    Jan 19, 2011 at 1:34

The general rule is that the more selective the index is (selectivity being defined as the number of unique values in a column divided by the number of rows in the table), the more likely it is that the engine will use the index if a query uses the column in a where clause.

If you're considering indexing a column, running a query selecting on the indexed column before and after and looking at the execution plans will tell you if the index is being used, and if so, how much the index is helping. Ideally, the query you use for the test is one that would be used by your application.


So far, my rule of thumb has been to not put any indexes into my development databases at all while I'm working on them. As the production database gets bigger, I use database logging and EXPLAIN to figure out what needs indexing, and then create only the necessary indexes. This works fine as long as database usage increases gradually, and keeps index counts low.

When analysing data in the database, I usually need to add additional indexes to speed up requests which aren't common in production. I always do this on copies of the production database, so these indexes are never added to production themselves.

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