I've got a database with a star schema and I'm kind of confused about
what the optimizer is doing with my queries.  I've got a fact table
(about 24 M rows), which I'm joining to 3 dimensions.  Each dimension
ID in the fact has it's own index.

No matter what I do, I've been unable to get the optimizer to choose a
star join (IXAND or the like).  It always just picks one of the
dimensions and does a nested loop join and then HSJOINs in the rest.
To be clear the queries I've tried are like this:

select a.field, b.field, count(*)
from fact f, dim1 a, dim2 b, dim 3 c
where
f.dim1_key = a.dim1_key and
f.dim2_key = b.dim2_key and
f.dim3_key = c.dim3_key and
a.field like 'Data%' and
b.field like 'Data%' and
c.field like 'Data%'
group by a.field, b.field

The really odd-ball thing is that I've got another dimension, which has
absolutely no selectivity -- i.e. All the items in the fact are in a
single dimension.  (I know this seems stupid, but it's a test
database).  If I join in this dimension (in queries similar to the one
above), in many of my queries, the optimizer will actually choose this
dimension to drive the NLJOIN with the fact.  How it could ever use
that dimension over anything else is beyond me as the result is
essentially a full table scan.

So, what I'm wondering is 2 things:

1)  Can anyone point me to a good reference about how star joins work
or offer any advice regarding gettting the optimizer to use a star
join?
2)  Does anyone have any idea why the optimizer would choose worst
possible index under any circumstances?

Oh, by the way, the stats are all up-to-date.

Thanks,
Greig Wise
DB2 DBA
Press Ganey Associates