This example illustrates a simple use of the HPSUMMARY procedure to summarize using the grid in distributed mode. The following DATA step creates a data set that consists of test scores:
data gridlib.grades; input Name $ 1-8 Gender $ 11 Status $13 Year $ 15-16 Section $ 18 Score 20-21 FinalGrade 23-24; datalines; Abbott F 2 97 A 90 87 Branford M 1 98 A 92 97 Crandell M 2 98 B 81 71 Dennison M 1 97 A 85 72 Edgar F 1 98 B 89 80 Faust M 1 97 B 78 73 Greeley F 2 97 A 82 91 Hart F 1 98 B 84 80 Isley M 2 97 A 88 86 Jasper M 1 97 B 91 93 ; run;
The following statements read this data set and analyze the data for the two-way combination of CLASS variables and across
all observations. To run these statements successfully, you need to set the macro variables GRIDHOST
and GRIDINSTALLLOC
to resolve to appropriate values, or you can replace the references to the macro variables in the example with the appropriate
values.
proc hpsummary data=gridlib.grades; performance host="&GRIDHOST" install="&GRIDINSTALLLOC"; var Score; class Status Year; types () status*year; output out=gridlib.result; run; proc print data=gridlib.result; run;
Figure 9.1 displays the table produced by the HPSUMMARY procedure. The “Performance Information” table shows that PROC HPSUMMARY was executed alongside the database in distributed mode.
Figure 9.1: HPSUMMARY Output
Performance Information | |
---|---|
Host Node | your grid host |
Execution Mode | Distributed |
Grid Mode | Symmetric |
Number of Compute Nodes | 16 |
Number of Threads per Node | 24 |
Obs | status | year | _TYPE_ | _FREQ_ | _STAT_ | score |
---|---|---|---|---|---|---|
1 | 0 | 10 | N | 10.0000 | ||
2 | 0 | 10 | MIN | 78.0000 | ||
3 | 0 | 10 | MAX | 92.0000 | ||
4 | 0 | 10 | MEAN | 86.0000 | ||
5 | 0 | 10 | STD | 4.7140 | ||
6 | 1 | 97 | 3 | 3 | N | 3.0000 |
7 | 1 | 97 | 3 | 3 | MIN | 78.0000 |
8 | 1 | 97 | 3 | 3 | MAX | 91.0000 |
9 | 1 | 97 | 3 | 3 | MEAN | 84.6667 |
10 | 1 | 97 | 3 | 3 | STD | 6.5064 |
11 | 1 | 98 | 3 | 3 | N | 3.0000 |
12 | 1 | 98 | 3 | 3 | MIN | 84.0000 |
13 | 1 | 98 | 3 | 3 | MAX | 92.0000 |
14 | 1 | 98 | 3 | 3 | MEAN | 88.3333 |
15 | 1 | 98 | 3 | 3 | STD | 4.0415 |
16 | 2 | 97 | 3 | 3 | N | 3.0000 |
17 | 2 | 97 | 3 | 3 | MIN | 82.0000 |
18 | 2 | 97 | 3 | 3 | MAX | 90.0000 |
19 | 2 | 97 | 3 | 3 | MEAN | 86.6667 |
20 | 2 | 97 | 3 | 3 | STD | 4.1633 |
21 | 2 | 98 | 3 | 1 | N | 1.0000 |
22 | 2 | 98 | 3 | 1 | MIN | 81.0000 |
23 | 2 | 98 | 3 | 1 | MAX | 81.0000 |
24 | 2 | 98 | 3 | 1 | MEAN | 81.0000 |
25 | 2 | 98 | 3 | 1 | STD | . |