Constant Quest for Efficiency


In last week’s blog post titled FlowForce Server Supports RaptorXML, we created a FlowForce Server job that defined a RaptorXML execution step to validate XML files, and we called that job as a step at the end of our job that processes camera GPS data, as a final check on the output. That was a quick way to demonstrate integration of FlowForce Server and RaptorXML Server, but for real-world production we would want to perform the same task more efficiently.

RaptorXML as an execution step in a FlowForce Server job

If we insert the RaptorXML validation function at the top of the job, right in front of the On error definition as shown above, we can apply the same error handling steps for failures of either the data mapping or the validation step. In other words, an error in any one of a series of steps before the On error definition forces the job to take the error path.
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FlowForce Server Supports RaptorXML


Altova FlowForce Server supports RaptorXML Server and RaptorXML+XBRL Server.

Log details of a RaptorXML job step

Altova RaptorXML is the third-generation, hyper-fast XML and XBRL processor from the makers of XMLSpy. RaptorXML is built from the ground up to be optimized for the latest standards and parallel computing environments. Now FlowForce Server jobs can include steps to validate XML, transform XML with XSLT, execute XPath and XQuery, and even perform complex XBRL operations for financial reporting including validating XBRL taxonomies, and validating XBRL instances against XBRL taxonomies with support for XBRL Dimensions and XBRL Formula, which define new, compatible functionality to extend XBRL 2.1.

For example, we can return to the FlowForce Server job described in Taming Bad Input Data with FlowForce Server and add a RaptorXML operation to validate the XML files created from raw GPS data captured by a digital camera.
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XBRL Validation and Processing Tools


When we were designing RaptorXML Server, we knew from the get-go that the engine should support XML and XBRL standards. The former standard is ubiquitous and the latter will be, as well, given increasing mandates from governments worldwide as well as adoption by enterprises for analyzing financial data in a standards-based, cost-effective manner. However, we knew that at this time a sub-set of customers would be interested in the XBRL capabilities of the engine, so we created two versions: RaptorXML Server and RaptorXML+XBRL Server.

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Let’s take a look at some of the powerful XBRL-oriented features in RaptorXML+XBRL Server.
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