Do Exception and Compression Settings Matter for ACE Tags?

Understanding Exception and Compression Settings in ACE Tags

In the world of process data management, PI System by OSIsoft plays a crucial role in capturing and analyzing real-time data. Advanced Computing Engine (ACE) is a component that offers real-time data processing and analysis through scripting or coding, often leveraging technologies such as PI-API, PI SDK, or AFSDK. However, a recurring question for users of ACE is whether the exception and compression settings utilized in standard PI tag processing also apply to ACE tags.

Exception and Compression: A Brief Overview

Before diving into ACE specifics, let’s review what exception and compression settings mean in the PI System.

• Exception Testing: Exception testing is a filtering mechanism applied at the data collection stage to determine whether a data point should be sent for archiving based on predefined deviation thresholds. This helps in reducing the volume of redundant or trivial data.

• Compression Testing: Compression is applied post-exception testing, primarily during the archiving process, to further reduce data storage by removing data points that fall within a defined deviation range between two recorded points. This assures that only significant changes in data values are stored.

Exception and Compression in ACE Tags

ACE's primary function is to perform complex calculations in real-time, generating new datasets, or modifying existing datasets. A few points of distinction when it comes to ACE tags:

1. Exception and Compression Testing: ACE applications traditionally inherit the exception and compression settings from their configured PI tags. However, depending on how data is written in ACE (for example, using PI SDK or similar methods directly), these checks might be bypassed. This means all computed values might get archived, regardless of the deviation thresholds set.

2. Version Variability: The treatment of exception testing in ACE can vary across different ACE versions. Older versions might not engage in exception testing while newer releases integrate more closely with the PI System's filtering mechanisms. It’s this variability that sometimes results in behaviors like archiving values even within the exception deviation.

3. Disabling Compression and Exception in Practice: Many practitioners opt to disable exception and compression settings for ACE tags, especially if the input tags have already undergone these tests. This approach ensures the transparency of calculated results without additional data filtration, making it easier for analysts to correlate ACE output directly with their input data computations.

4. Criticality of Snapshot Values: When using ACE, it's important to note that trigger mechanisms often rely on snapshot values - the latest transient value of a tag before archiving. Therefore, care must be taken to validate whether a snapshot, which initiates a process logic, is actually archived if using compressed post processing.

Conclusion

Understanding the interplay of exception and compression settings in ACE tags is crucial for robust implementation. The discretion of applying or bypassing exception and compression settings depends on the application's requirements. For users observing unusual archiving patterns with ACE tags, it’s essential to review how ACE applications write data and the version-specific features of their ACE install. Disabling compression and exception ensures clarity and validation ease but may lead to larger data storage requirements.

In practice, effective ACE implementations balance between computational needs and system efficiency, ensuring both accurate real-time analytics and optimal data storage.