Oracle® OLAP DML Reference 11g Release 2 (11.2) E17122-08 |
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The ROW function returns a line of data in cells, one after another in a single row. It is identical to the ROW command, except that it returns a text value, instead of sending the text to the current outfile.
The ROW function, just like the ROW command, consists of a series of column descriptions that specify the data to be returned and, optionally, the way in which it is to be formatted. The ROW function lets you assign the returned value to a text variable, send it to your current outfile with the SHOW or REPORT command, or process it further as an argument to a character manipulation function.
See also::
ROW commandROW([attribs] [ACROSS dimension [limit-clause]:] {exp1|SKIP} -
[[attribs] [ACROSS dimension [limit-clause]:] {expn|SKIP}])
See the ROW command for a complete description of the arguments.
The ROW function without any arguments returns a blank line.
Example 8-89 Assigning Output to a Text Variable
The following assignment statement assigns three lines of output to the text variable textvar
.
textvar = ROW(OVER '-' UNDER '=' 'This is a Row.') SHOW textvar
These statements produce the following output.
-------------- This is a Row. ==============
Example 8-90 Producing Multiple Rows of Output
You can use the ROW function with JOINLINES in a program to loop over a group of dimension values and assign several rows of data to a text variable. Instead of using the SHOW command in the following program excerpt, you could use the contents of textvar
for some other purpose.
LIMIT month TO 'Jan95' 'Feb95' LIMIT district TO 'Boston' 'Atlanta' 'Chicago' textvar = NA textvar = ROW(W 8 SKIP ACROSS month: <month SKIP>) textvar = JOINLINES(textvar ROW(W 8 SKIP ACROSS month: - CENTER <'Sales' 'Plan'>)) FOR district textvar = JOINLINES(textvar ROW(W 8 district ACROSS month: - <sales sales.plan>)) SHOW textvar
These statements produce the following output.
OUTPUT: Jan95 Feb95 Sales Plan Sales Plan Boston 32,153.52 42,346.89 32,536.30 43,265.50 Atlanta 40,674.20 54,583.41 44,236.55 57,559.87 Chicago 29,098.94 36,834.37 29,010.20 37,667.66