I'm building a data warehouse. Each fact has it's timestamp
. I need to create reports by day, month, quarter but by hours too. Looking at the examples I see that dates tend to be saved in dimension tables.
(source: etl-tools.info)
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 efficient than using date/time functions in SQL
.
What are your opinions/solutions ?
(I'm using Infobright)
To fill a Time Dimension table – Right-click on the Time Dimension object and select the Fill Time Dimension Table option. Astera Data Warehouse Builder would automatically fill values in the provided database table.
One of the major dimensions in every multidimensional data warehouse is the time dimension. The time dimension contains descriptive temporal information, and its attributes are used as the source of most of the temporal constraints in data warehouse queries (Kimball, 1996).
Typically dimensions in a data warehouse are organized internally into one or more hierarchies. "Date" is a common dimension, with several possible hierarchies: "Days (are grouped into) Months (which are grouped into) Years", "Days (are grouped into) Weeks (which are grouped into) Years"
Kimball recommends having separate time- and date dimensions:
design-tip-51-latest-thinking-on-time-dimension-tables
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.
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.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With