根据列中的值将单行转换为多行

Figured out the solution I was thinking of, but yes, it does require dynamic SQL to get the relevant column names to feed into the UNPIVOT:

declare @sql varchar(max)
set @sql = 
    'select Person, EventName
    from EventAttendees
    unpivot
    (
        Attended for EventName in (' + (select
                                        stuff((
                                            select ',' + QUOTENAME(c.[name])
                                            from sys.columns c
                                            join sys.objects o on c.object_id = o.object_id
                                            where o.[name] = 'EventAttendees'
                                            and c.column_id > 1
                                            order by c.[name]
                                            for xml path('')
                                        ),1,1,'') as colList) + ')
    ) unpiv
    where unpiv.Attended = ''x''
    order by Person, EventName'

exec (@sql)

在这个例子中，我假设事件列从表中的第二列开始，但显然我可以在子查询中使用一些不同的逻辑来识别相关列.

In this example, I am making the assumption that the Event columns are from the second column in the table onwards, but obviously I could use some different logic within the subquery to identify the relevant columns if necessary.

在我的示例数据上，这给出了所需的结果:

On my example data, this gives the desired result:

/---------------------------\
| Person        | EventName |
|---------------|-----------|
| Jane Doe      | Event B   |
| Jane Doe      | Event C   |
| John Smith    | Event A   |
| Phil White    | Event A   |
| Phil White    | Event C   |
| Sarah Jenkins | Event A   |
| Sarah Jenkins | Event B   |
| Sarah Jenkins | Event C   |
\---------------------------/

我想我更喜欢这个而不是使用游标，尽管我实际上还没有确认这两种动态方法之间有什么性能差异(如果有的话).

I think I prefer this to using a cursor, although I haven't actually confirmed what performance difference (if any) there is between the two dynamic approaches.

感谢大家对这个问题的帮助和建议，一如既往地非常感谢！

Thanks for everyone's help and suggestions on this question though, greatly appreciated as always!

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