LastRawValue/LastRawTime Modes
Retrieves the last good raw sample value or timestamp for a given time interval.
- Value
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The value of the raw sample or zero if there are no good raw samples in the interval. The timestamp of the sample or the year 1969 if there are no good raw samples in the interval.
- Quality
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The quality is the same for LastRawValue and LastRawTime. If there are no good raw samples in the interval, then the percent good is 0. Otherwise, percent good is always 100, even if the interval contains bad quality samples.
The Raw sample has a quality of Good, Bad or Uncertain, and that is converted to a 0 or 100 percent.
- Example: Retrieving the LastRawValue/LastRawTime Values
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Import this data into Historian
[Tags]Tagname,DataType DecimatedOneHour,DoubleInteger [Data] Tagname,Timestamp,Value,DataQuality Tag1,07-05-2011 17:29:00,29,Good Tag1,07-05-2011 20:00:00,0,Good Tag1,07-05-2011 20:12:00,12,Good Tag1,07-05-2011 20:15:00,0,Bad - Using LastRawValue Calculation Mode
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set starttime='07-05-2011 17:00:00',endtime=' 07-05-2011 21:00:00' select timestamp,value,quality from ihrawdata where tagname like Tag1 and samplingmode=Calculated and CalculationMode=LastRawValue and Intervalmilliseconds=1hThe output is as follows:
Time Stamp Value Quality 07-05-201118:00:00 29 100.0000000 07-05-201119:00:00 0 0.0000000 07-05-201120:00:00 0 100.0000000 07-05-201121:00:00 12 100.0000000 In the interval from 17:00 to 18:00 the last good value is 29. The 18:00 to 19:00 has no raw samples so the quality is bad. The 20:00 sample is returned as the last good value in the 19:00 to 20:00. In the final interval, the last raw sample is bad quality so it is ignored and the previous sample is returned.
- Using LastRawTime Calculation Mode
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set starttime='07-05-2011 17:00:00',endtime=' 07-05-2011 21:00:00' select timestamp,value,quality from ihrawdata where tagname like Tag1 and samplingmode=Calculated and CalculationMode= LastRawTime and Intervalmilliseconds=1hThe output is as follows:
Time Stamp Value Quality 07-05-201117:00:00 07-05-201117:29:00 100.0000000 07-05-201118:00:00 01-01-197005:30:00 0.0000000 07-05-201119:00:00 07-05-201120:00:00 100.0000000 07-05-201120:00:00 07-05-201120:12:00 100.0000000 Note: You can also use the INCLUDEBAD query modifier to include bad quality data.