AFP Fast Parser™ - High speed AFP to PDF converter

AFP Fast Parser™ converts your AFPDS data or Host generated IPDS data streams into PDF, PostScript (PS2 & PS3) or image file formats (BMP, TIFF...). It is an essential component for viewing, printing, archiving and Web Presentation systems.

Up to 30 000 pages per minute

AFP Fast Parser™ is designed for the conversion of large volumes of digital data and to fulfill the needs of today’s High Speed Production and On-Demand environments. Fast Parser’s AFP to PDF and IPDS to PDF conversion engine is capable of speeds in excess of 30,000 pages per minute. This performance is achieved by taking advantage of production multi processor/multi server architecture.

Several working modes

AFP Fast Parser™ can run in batch mode or in server mode on Multiple Operating Systems (Windows, Linux, AIX, Unix, Solaris...). When running in server mode it can communicate with application servers for Web applications.

.NET (DotNET) & Java APIs are available to help you integrate the Fast Parser into your production solution.

AFP Batch mode

The Batch program launches the MPI Parser executable with parameters (AFP file to transform….)
MPI Parser converts the input file to an output file, returns a status and exits.

AFP Server Mode 1

The MPI Parser runs as a server. The Batch program launches the Fast Parser client with user-defined parameters.
Fast Parser client forwards the request to MPI Parser which runs the transform. When the transform is completed, MPI Parser returns the status to the batch through the Fast Parser client.

AFP Server Mode 2 (send AFP File)

Same as previous, except the Fast Parser client transfers the AFP File to the MPI parser along with the transform request.

AFP Server Mode 3 (receive result of transform)

Same as previous, except the Fast Parser client receives the result of the transform as a stream which can be stored on the disk or forwarded to the application program which initiated the request.

IPDS server

MPI Parser runs as an IPDS printer. It receives IPDS over TCP/IP and generates the Outputs.

Multi-Server architecture

MPI Parser parses and then distributes the input data to several MPI Drawer servers. Each MPI Drawer server then takes advantage of the local Multi processor server architecture to process the input data. MPI Parser controls the whole process.

Filters : document modification

AFP Fast Parser™ provides a way to modify the documents, to apply a pre-process on incoming data or a post-process on transformed data. This mechanism is performed through the filters. The filters action is described with a xml configuration file which can be activated at Fast Parser startup or which can be dynamically invoked for specific treatments.

• When the filter is defined as an input filter, it invokes an external program at reception of the AFP input file before any Fast Parser treatment. This program can for instance modify the AFP data before Fast Parser processes it.
• When the filter is defined as an internal filter, many actions can be performed on the data itself (add or suppress pages or elements in the page…). The Internal filter operates during the transform process.
• When the filter is defined as an output process, it invokes an external program when the transform is completed.

With the help of filters, the following elements can be added to the document :
- Overlays
- OMR
- Barcodes
- Images

Indexing : extract useful data when parsing

Having to handle huge AFP files and generating a great amount of PDF files often makes it more difficult to find & retrieve relevant data they contain.

For example, you might need to extract a list of recipients, or invoice numbers to be provided to the postal service or your own mailing solution.

• If your AFP file contains NOP and/or TLE metadata, AFP Fast Parser will provide native indexing facilities by providing an XML index output file including those NOP / TLE Metadata.
• If your AFP File does not contain any NOP or TLE metadata, ScopIndex™ can work alongside AFP Fast Parser™ to help you with that matter.