Use DDF Builder to import the file definition, and save it in data dictionary (DDF) file format.
Open the file with DDF Builder, and browse the record values to determine what information is
stored within the fields. Assign meaningful field names to the fields, modify field type or length as
necessary, and before long you have a complete DDF dictionary of your Btrieve data.
Q: Why do I need DDF Builder? Can't DDF Sniffer just read the Btrieve data file and create DDF files
A: DDF Sniffer can't determine a file's data structure with one hundred percent accuracy. DDF Sniffer
starts with raw Btrieve data. Initially, all it knows about the files it scans is the length of the records, the
number of records in the file, and the index field positions, lengths, and data types. For example,
USERS.DAT, a Btrieve data file, might contain system user information. An analysis of the file's status
information indicates that the records are 100 bytes long. There are 1000 records in the file. Indexes
defined for the file indicate that there is an integer key in the first 4 bytes of the record, followed by a
string field in the next 20 bytes. The integer and string are the only two fields that DDF Sniffer can
positively identify by position, length, and type. DDF Sniffer must make educated guesses about how the
76 bytes in the rest of the record is parsed. You'll need to view the data to determine whether the fields
parsed from the non-indexed areas of the record make sense within the context of the application which
generated the data, and you'll probably want to make a few changes.
Q: Will DDF Sniffer work with all Btrieve data?
A: No. There are several reasons that your Btrieve data may not be definable in DDF format. Btrieve
stores the data an application gives it, and retrieves that data when the application requests it. Btrieve does
not impose a structure on the data. The DDF specification was developed to define SQL-format data.
Though DDF Sniffer should work with the vast majority of Btrieve application data, non-SQL applications
may not store their data in normalized files, or they may use data types which are not supported by the
DDF standard. Other factors may affect DDF Sniffer's ability to parse a file, such as the size of the
record sample or the complexity of the record structure. That's why DDF Sniffer comes with a 30-day
money back guarantee.