The function evaluates the numeric value for each element of the set and returns the sum of those values.
Example
First, the following query shows values of three measures for the members of the aged.decade level:
SELECT {MEASURES.[%COUNT],MEASURES.[encounter count],MEASURES.[avg test score]} ON 0,
birthd.decade.MEMBERS ON 1 FROM patients
Patient Count Encounter Count Avg Test Score
1 1910s 80 5,359 75.17
2 1920s 227 12,910 74.20
3 1930s 567 33,211 74.67
4 1940s 724 38,420 73.39
5 1950s 1,079 46,883 73.72
6 1960s 1,475 57,814 74.16
7 1970s 1,549 49,794 74.35
8 1980s 1,333 35,919 74.13
9 1990s 1,426 29,219 74.79
10 2000s 1,406 20,072 74.95
11 2010s 134 1,346 73.55
Next, the following query shows the sums for these measures for the members of this level:
SELECT {MEASURES.[%COUNT],MEASURES.[encounter count],MEASURES.[avg test score]} ON 0,
SUM(birthd.decade.MEMBERS) ON 1 FROM patients
Patient Count Encounter Count Avg Test Score
SUM 10,000 330,947 817.08
Here, each value is the sum of the values in a column in the preceding query. For example, the Patient Count value is the sum of the Patient Count values in the preceding query. The Avg Test Score value is the sum of the average test scores and is probably not a useful value.
For another example, we use the second argument for SUM:
SELECT SUM(birthd.decade.MEMBERS, MEASURES.[%COUNT]) ON 0 FROM patients
SUM
10,000
For additional, similar examples, see AVG.
