Question

I have a table with around 15 columns which can be queried with different combination. The table columns for instance is UserID, LocationID, DepartmentID, CoOrdinate1, CoOrdinate2, CoOrdinate3…CoOrdinate15.

To speed up the retrieval of combination of data we have created a Computed field where we are storing the values of these columns in the format :UserID::LocationID::DepartmentID::CoOrdinate1:…:CoOrdinate15: – a sample value would look like :1:100:20:22:39:94:29:..:9:

While this is fine for retrieving data where the index key matches (= operator) we are exploring the best method to fetch combinations.

For instance if the user queries for UserID = 1 and CoOrdinate = 15 we plan to build a Like condition ‘%:1::%::%::%::%::%::%::%::%::15:%’.

SQL Server is doing an Index Scan to retrieve the data. From a performance point of view – is there a better way to approach this problem.

Answer 1

let me sum this up:

• when query a table, in your where clause you can have an arbitrary combination of the columns
• you could create an individual index on each column, but only one of them would be used for your query, as normal b-tree indexes cannot be combined
• you could create composite indexes on certain combination of columns but these indexes would only be used by those queries that have a where clause that matches the columns in the composite index; also, having many wide composite indexes would incur big maintenance overhead
• Since you want to filter against arbitrary combination of the columns in your queries, composite indexes are not an option: you cannot create a composite index for all possible combination of columns

In general, the solution to this problem is having bitmap indexes on each columns, because bitmap indexes can be combined. Unfortunately SQL Server does not support bitmap indexes but I’ve heard it has some similar feature. I suggest you look into that:

http://msdn.microsoft.com/en-us/library/bb522541.aspx
(This article discuss the usage of bitmap indexes when joining tables, but dont let that confuse you, they can be useful in your use case as well, when you query a single table.)