Selecting Values From a table as Column Headers

You did not specify RDBMS, if you know the number of columns to transform then you can hard-code the values:

select FileId,  max(case when property = 'Name' then value end) Name,  max(case when property = 'Size' then value end) Size,  max(case when property = 'Type' then value end) Typefrom yourtablegroup by FileId

This is basically a PIVOT function, some RDBMS will have a PIVOT, if you do then you can use the following, PIVOT is available in SQL Server, Oracle:

select *from (  select FileId, Property, Value  from yourTable) xpivot(  max(value)  for property in ([Name], [Size], [Type])) p

If you have an unknown number of columns to transform, then you can use a dynamic PIVOT. This gets the list of columns to transform at run-time:

DECLARE @cols AS NVARCHAR(MAX),    @query  AS NVARCHAR(MAX)select @cols = STUFF((SELECT distinct ',' + QUOTENAME(property)                     from yourtable            FOR XML PATH(''), TYPE            ).value('.', 'NVARCHAR(MAX)')         ,1,1,'')set @query = 'SELECT ' + @cols + ' from              (                select FileId, Property, Value                from yourtable            ) x            pivot             (                max(value)                for Property in (' + @cols + ')            ) p 'execute(@query)

A version with joins that works regardless of missing rows:

SELECT      pd.FileID   , p1.Value  AS Name  , p2.Value  AS Size  , p3.Value  AS TypeFROM        ( SELECT DISTINCT FileID          FROM propertyvalues         ) AS pd    LEFT JOIN        propertyvalues AS p1            ON  p1.FileID = pd.FileID             AND p1.Property = 'Name'    LEFT JOIN        propertyvalues AS p2            ON  p2.FileID = pd.FileID             AND p2.Property = 'Size'    LEFT JOIN        propertyvalues AS p3            ON  p3.FileID = pd.FileID            AND p3.Property = 'Type' ;

If you have a table where FileID is the primary key, you may replace the DISTINCT subquery with that table.

Regarding efficiency, it depends on a lot of factors. Examples:

• Do all FileIDs have rows with Name, Size and Type and no other properties (and your table has a clustered index on (FileID, Property))? Then the MAX(CASE...) version would perform quite well as the whole table would have to be scanned anyway.

• Are there (many) more than 3 properties and a lot of FileIDs have no Name, Size and Type, then the JOIN version would work well with an index on (Property, FileID) INCLUDE (Value) as only this index data would be used for the joins.

• Not sure how efficient is the PIVOT version.

What I suggest though is to test the various versions with your data and table sizes, in your envirorment (version, disk, memory, settings, ...) before you select which one to use.

Create function [dbo].[AF_TableColumns](@table_name nvarchar(55))returns nvarchar(4000) asbegindeclare @str nvarchar(4000)    select @str = cast(rtrim(ltrim(column_name)) as nvarchar(500)) + coalesce('         ' + @str , '            ')     from information_schema.columns    where table_name = @table_name    group by table_name, column_name, ordinal_position     order by ordinal_position DESCreturn @strend--select dbo.AF_TableColumns('YourTable') Select * from YourTable