Many applications are able to read and write files containing so-called “comma separated values”. Such files generally contain tabular data where the columns are separated by commas and the rows by line feed and/or carriage return characters. Although record sets are not tables, tables can be easily emulated using records having the same fields in the same order. For example:
a: value b: value c: value a: value b: value c: value ...
In several respects records are more flexible than tables:
It is evident that records, such as those in recfiles, are a more
general structure than comma separated values.
This means that when converting from csv files to recfiles, certain
decisions need to be made.
rec2csv utility (see rec2csv)
implements an algorithm to deal with this problem
and generate a table that the user expects.
The algorithm works as follows:
where n is a number in the range
2..inf and is the “index” of
the field in its containing record plus one.
For example, consider
the following record set:
a: a1 b: b11 b: b12 c: c1 a: a2 b: b2 d: d2
The corresponding list of headers being:
a b b_2 c a b d
a b b_2 c d
In the above example the result would be
"a","b","b_2","c","d" "a1","b11","b12","c1", "a2","b2",,,"d2"
Note that missing fields are implemented as empty columns in the generated csv.