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Historians: Read Tag List

This article provides starter solutions that can be used to create a list of historian points or tags.

What Does This Article Cover?

This article introduces points and tags in historians and explains why some Intelligence Hub historian-related data pipeline solutions begin by building a list of points or tags.  The article describes starter solutions by historians.

 

An overview of points and tags 

In historians, a single measurement or data stream (temperature, pressure, flow, motor current, etc.) is a point or tag. Vendors use the terms differently, but both refer to a time-series variable stored in the historian.

Why start with a list? The scope of an Intelligence Hub pipeline is typically a subset of the historian’s points or tags. One of the first steps is therefore to obtain the list of in-scope points or tags that downstream Connection Inputs will use.

 

General Intelligence Hub design considerations for obtaining a list of tags 

Use this checklist when you're constructing the list your solution will operate on. 

  1. Define scope 
    1. Decide exactly which points or tags are in scope for the solution (area, unit, line, system).
  2. Decide how you'll query
    1. Use naming conventions or filters. Check the historian's syntax and filtering options. If a client tool exists (e.g., PI System Explorer), test your queries there first.
  3. Start small and then scale 
    1. Begin with tens or hundreds of points or tags to observe the query duration.  Aim for a query duration of few seconds. 
  4. Consider adding Connections or increasing resources
    1. If one Input is too slow, use multiple Connection Inputs and possibly multiple Connections. Also, increase host and agent host resources if needed. 
  5. Multiple Connections
    1. Consider how a new Connection Input will affect other Inputs using the same Connection. Stagger schedules to avoid parallel queries or use multiple parallel Connections.
  6. Plan for edits and growth 
    1. If points or tags are added or edited often, set a refresh strategy. Tune the Cache Interval so changes appear when you need them without creating excess query load.
  7. Shape results  
    1. Determine the output format.  It is typically a comma-separated list or an array.  Consider the required format for the downstream Connection Input.

 

AVEVA PI System Data Archive: design considerations for obtaining a list of points 

These considerations pertain to obtaining a list of PI Point names from PI Data Archive. 

  • The Intelligence Hub PI Connection PI Point-related Inputs allow specific PI Points to be used as a Reference.
    • Often, an Intelligence Hub data pipeline processes solution many PI Points that need to be obtained first.
    • An Input Reference is an array PI Point names.
  • It is typically best to use the PI Connection Point Browse Input Type to obtain the list of PI Points to use in the downstream Connection Input Reference.
  • When obtaining a list of PI Points for a Connection Input Reference, do not use the Include Metadata option.

Navigate to the interactive demonstration [here].

 

 

 

AVEVA PI System Asset Framework: design considerations for obtaining a list of points 

These considerations pertain to obtaining a list of PI Point Names using Asset Framework Assets. 

  • Some solutions require PI Point values in the context of an Asset Template or Asset.
  • Often, an Intelligence Hub data pipeline processes many PI Points, and they need to be obtained first.  The PI Connection PI Point related Inputs allow a Reference (an array of PI Point names) to be specified.  
  • It is typically best to use the PI Connection Asset Metadata Input Type for obtaining the list of PI Points per Asset Template or Asset for use in the downstream Connection Input Reference.  The Asset Metadata Input Type query can be time-consuming, and it may be necessary to use paging to obtain the PI Points. 
  • The PI Points need to be extracted from this payload using an Intelligence Hub Pipeline JavaScript Stage.  The JavaScript for the JavaScript Stage is provided in the Intelligence Hub User Guide [here].

Navigate to the interactive demonstration [here].

 

 

 

Canary Historian design considerations for obtaining a list of tags

These considerations pertain to obtaining a list of tags from Canary Historian. 
  • An Intelligence Hub REST Client Connection is used to obtain data from Canary Historian.
  • The Canary Historian Views Service API does allow filtering to be performed when reading values, but some Intelligence Hub data pipeline solutions may require tag names to be obtained independently of the Input to obtain values.  For example, the Views Service API getTagData method accepts an array of tag names in the response body. 
  • The Views Service API browseTags method can be used to obtain an array of tag names.
  • An Intelligence Hub Pipeline JavaScript Stage can be used to format the tags obtained by the getTagData method. 

Navigate to the interactive demonstration [here].

 

 

 

Aspen InfoPlus.21 design considerations for obtaining a list of tags

These considerations pertain to obtaining a list of tags from IP.21. 

  • The IP.21 Connection Input can filter tags in query, but many pipelines first query tags, then use that list in downstream value queries
  • A query can be written to obtain a list of tag names.
  • An Intelligence Hub Pipeline JavaScript Stage can be used to format the tags for the values query. 

Navigate to the interactive demonstration [here].

 

Summary

Use these considerations to design and implement a robust solution with the Intelligence Hub.  Start by defining the list, validate query cost and duration, tune cache and resource settings to match change rates, and shape the output for downstream processing. 

 

Additional Resources