FLUC Element interface
The element interface (access method) for original data was introduced with FLAM version 5 and is the counterpart of the FLAM element interface. It is the basis for the conversion of original data with both the utility and the subprogram. It also constitutes an access method into plain or compressed and/or encrypted files for individual elements (data block, data record, colums of tables, XML elements or particular types such as bank-ID, account number, etc.) while supporting all open standards and data formats that are vital for exchanging data in the world today. Via his interface (API), applications can read and write back data (type lenth, value) irrespective of the platform. The reading routines save additional attributes that can be evaluated for proper formatting with writing. The element interface accepts not only records for processing but any type of data elements which allows handling and converting logical file contents.
- Binary and platform-independent reading and writing of arbitrary elements (type, length, data) and their attributes from various platform-specific data formats.
- The API is implemented like a n I/O access thus allowing easy integration into existing applications (put=elmput).
- Same universal local or remote access to any physical and logical data types.
- Decoding, decrypting, decompressing, converting character sets, and element parsing in one step, thus relieving CPU, saving many temporary files, and - above all - slashing runtime.
- May be extended by as many additional methods as desired.
- Customer requests for specific data formats can be deployed fast and easy.
- Implemented as an API (interface call).
- Opening and closing of units (usually files, possibly tables) in a directory, archive system, or database on the local or a remote (per SSH) system.
- API calls for reading and writing of individual elements in plain or compressed and/or encrypted data.
- Uniformly available for many platforms and for different programming languages.
- An unlimted amount of conversions may be parametrized and the executed in one run.
- Preload architecture for maximum performance with bulk data processing