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550

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3

I'm buildind an data warehouse. Each fact has it's timestamp. I need to create reports by day, month, quater but by hours too. Loking at the examples I see that dates tend to be saved in dimension tabels. alt starexample

But I think, that it makes no sense for time. The dimension table would grow and grow. On the other hand JOIN with date dimension table is more efficent than using date/time functions in SQL.

What are your opinions/solutions ?

(I'm using Infobright)

+3  A: 

Time should be a dimension on data warehouses, since you will frequently want to aggregate about it. You could use the snowflake-Schema to reduce the overhead. In general, as I pointed out in my comment, hours seem like an unusually high resolution. If you insist on them, making the hour of the day a separate dimension might help, but I cannot tell you if this is good design.

Space_C0wb0y
If date is a dimension for 10 years it has only about 3650 records. Hour-by-hour reports are very useful here - we need to compare days: monday to monday, tuesday to tuesday and hours monday 11:00-12:00 to tuesday 11:00-12:00.Do you think that snowflake is more useful/efficent than star ?
peperg
Snowflake can help reduce the redundancy in the dimension-tables, but if that helps you performance- or memory-wise in your particular case I cannot say.
Space_C0wb0y
A date dimension with 10 years and hours is still small: 87,660 rows. Further, you can summarize old data to reduce the time resolution. After 10 years, how much relevance can 10AM on Thursday actually have?
S.Lott
+4  A: 

Kimball recommends having separate time- and date dimensions:

http://www.kimballgroup.com/html/designtipsPDF/KimballDT51LatestThinking.pdf

In previous Toolkit books, we have recommended building such a dimension with the minutes or seconds component of time as an offset from midnight of each day, but we have come to realize that the resulting end user applications became too difficult, especially when trying to compute time spans. Also, unlike the calendar day dimension, there are very few descriptive attributes for the specific minute or second within a day. If the enterprise has well defined attributes for time slices within a day, such as shift names, or advertising time slots, an additional time-of-day dimension can be added to the design where this dimension is defined as the number of minutes (or even seconds) past midnight. Thus this time-ofday dimension would either have 1440 records if the grain were minutes or 86,400 records if the grain were seconds.

davek
+1 for quoting someone smart.
Space_C0wb0y
Agree, this is a good solution.
Paul James
+2  A: 

My guess is that it depends on your reporting requirement. If you need need something like

WHERE "Hour" = 10

meaning every day between 10:00:00 and 10:59:59, then I would use the time dimension, because it is faster than

WHERE date_part('hour', TimeStamp) = 10  

because the date_part() function will be evaluated for every row. You should still keep the TimeStamp in the fact table in order to aggregate over boundaries of days, like in:

WHERE TimeStamp between '2010-03-22 23:30' and '2010-03-23 11:15' 

which gets awkward when using dimension fields.

Usually, time dimension has a minute resolution, so 1440 rows.

Damir Sudarevic