> select ... cume(daily_total) as running_total
>The syntax for your database may be different.

indeed

what database are you using, dan? i've never heard of "cume"
before, but it sure sounds useful

any examples you could share?

rudy
***********************************

I work on the data warehouse team and we have data warehouse software
instead of database software.  The product name is Redbrick Warehouse, the
current owner is IBM, and it ain't cheap.

But, here is an example of how cume works with real data.  Note that the
queries will not yield useful results, I just chose something with a
numeric primary key,

select service_code, service, cume(service_code)
from service where service_code between 10 and 20;


11 ALLERGY                                  11
    12 CARDIOLOGY                               23
    13 DERMATOLOGY                              36
    14 ENDOCRINOLOGY                            50
    15 GASTROENTEROLOGY                         65
    16 NEPHROLOGY                               81
    17 NEUROLOGY                                98
    18 RESPIROLOGY                             116
    19 RHEUMATOLOGY                            135
    20 PAEDIATRICS                             155


Here is a moving sum of the same data

select service_code, service, movingsum(service_code, 3)
from service where service_code between 10 and 20;

11 ALLERGY                                 NULL
    12 CARDIOLOGY                              NULL
    13 DERMATOLOGY                               36
    14 ENDOCRINOLOGY                             39
    15 GASTROENTEROLOGY                          42
    16 NEPHROLOGY                                45
    17 NEUROLOGY                                 48
    18 RESPIROLOGY                               51
    19 RHEUMATOLOGY                              54
    20 PAEDIATRICS                               57

Or a moving average:

select service_code, service, movingavg(service_code, 2)
from service where service_code between 10 and 20;

11 ALLERGY                                           NULL
    12 CARDIOLOGY                               11.5000000000
    13 DERMATOLOGY                              12.5000000000
    14 ENDOCRINOLOGY                            13.5000000000
    15 GASTROENTEROLOGY                         14.5000000000
    16 NEPHROLOGY                               15.5000000000
    17 NEUROLOGY                                16.5000000000
    18 RESPIROLOGY                              17.5000000000
    19 RHEUMATOLOGY                             18.5000000000
    20 PAEDIATRICS                              19.5000000000

Our Cold Fusion work, for the most part, concerns reporting on data that is
already there as opposed to inserting records from some sort of form input.




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