![]() ![]() Only the leader node can perform any useful date calculations.If a full table scan is required and each record needs to be calculated for the date function it can make queries extremely expensive.Īlthough Redshift is advertised as having almost the same features as PostgreSQL there is one big missing feature that make it very difficult to generate a date dimension table: Once you start performing date calculations it’s very unlikely the database will be able to make optimisations or smart decisions that allow it to use an index.Date calculations are complicated in the easiest cases and making sure you handle all the edge cases is very complicated and error prone.Trying to do these date calculations in your queries raises a few problems: All days except the last day of each month.How would you go about handling reports that needed to filter or summarise (group) on? Let’s say we have a table that contains sales information lot’s of it. Used in combination the date dimension table these two integer indexes represent an exact second for any date.Įach will have their own separate table that contains the date/time ID and any information about that particular day or second. Usually picking a date at or slightly before the earliest records in your database is a good choice.Ī time dimension table is similar in that it will assign an index to individual seconds for one day (but have no date component). Where that starting point is depends on how far back you will need to go. It is common practice in data warehousing and reporting to use date and time dimension tables.Ī date dimension table assigns an index to each day from an arbitrary starting point. Photo by Estée Janssens on Unsplash What Is It? ![]()
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