I have a fixed-record-length data file which has "subsections" starting with a "data characteristics" record (call it a "subsection header"). One of the fields in the "subsection header" is a 2-byte zoned decimal "data length" value which identifies the number of SIGNIFICANT columns in the "data" portion of the records following the "subsection header".
What I would like to do is to blank out the NON-significant data columns in the data records that follow each "subsection header". The data records have suffered from some "data pollution" where non-significant data has been accidentally stored beyond the significant data columns. Each "subsection header" may have a different "significant data" length value for the following data records. Example INPUT data (column 1 = record type [H = header, D = data], data starts in column 3 in each record): H 05 COMMENT: "05" IS SIGNIFICANT DATA COLUMNS D 12345 XYZ ABC DEF D 45678 GHI JKL MNO H 10 D 1234567890 ABCDEFGHIJKL D 9876543210 MNOPQWRSTUVWXYZ Example OUTPUT data (column 1 = record type [H = header, D = data], data starts in column 3): H 05 COMMENT: "05" IS SIGNIFICANT DATA COLUMNS D 12345 D 45678 H 10 D 1234567890 D 9876543210 Obviously I can write a pretty simple script or program to accomplish this "data cleaning" operation, but I wondered if it would be possible using just SORT. The data volume is in the range of about 100K-200K records per file if that matters. TIA for any ideas you can offer. Peter -- ---------------------------------------------------------------------- For IBM-MAIN subscribe / signoff / archive access instructions, send email to [email protected] with the message: INFO IBM-MAIN
