Logging algorithms

This appendix describes the various logging algorithms that can be selected for a tag. These determine which of the points (timestamp value pairs) that were written to a tag get passed on to the on-disk tag log. Some logging algorithms take extra parameters that can be tuned to determine how frequently points are dropped or retained. Note that logging algorithms do not filter nor average. When required, signals should be filtered before they are written to tags. The following index lists the algorithms.

The objective of tuning a logging algorithm should be to reduce the amount of disk-space required by a log without causing significant differences between the interpolated values of the logged and buffered data. Whether this can be achieved depends on the details of the tag data: sampling frequency, signal bandwidth, noise level, jumps, spikes, and so on. To review the performance of the selected algorithm and its parameterisation, use the "Tag Graph" user interface while the tag is being written to. This allows the buffered and logged points to be compared. When in doubt, err on the side of caution and select the "everything" algorithm. Disk space is cheap.

A special condition arises when a not a number (NaN) value is written to a number tag. All but the nothing and everything logging algorithm will log only the first point in a series of NaN-valued points. In addition, the last point with a non-NaN value prior to that series as well as the first point with a non-NaN value after that series are always logged.


nothing

No points will be logged. Select this algorithm to disable logging for a tag. Applicable to all types of tag. This algorithm does not mind how many parameters are specified even though it does not require any. This allow those logging algorithms that do require parameters to be disabled and re-enabled without having to clear and re-enter their parameterisation.

changes

Log only points whose value has changed relative to the previously logged point. Can only applied to tags of set&hold temporal type. Note that interpolating the logged data yields the same results as interpolating the buffered data. This does not imply that one should always select this algorithm for set&hold tags: sometimes the time at which the tag is written to might be of interest to later queries even though that value does not change. If so, the everything algorithm is the proper choice.

everything

Log all points written to a tag. This is the safest choice. Applicable to all types of tag.


The remaining logging algorithms applicable only to number tags of sample temporal type.

every Nth (N)

Log every Nth point. N must be an integer. Can be used for over-sampled signals acquired at a known fixed sampling rate.

time threshold (t)

Log a point whenever its timestamp is higher than the timestamp of the last logged point by an amount equal to or exceeding the set time threshold parameter. Can be used for over-sampled signals. Note that the logged points will be spaced unevenly in time when the sampling period is close to the threshold.

value threshold + prior (v)

Log a point and the prior point whenever the absolute difference between its value and the value of the last logged point exceeds the set value threshold. Can be used for tags that jumps between discrete levels that are further apart than the set value threshold. E.g. a TTL signal.

t or v threshold (t, v)

Log a point when either its timestamp is higher than the timestamp of the last logged point by an amount equal to or exceeding the set time threshold or the absolute difference between its value and the value of the last logged point exceeds the set value threshold. Can be used for signals without jumps or spikes that can change both slowly and quickly. Typically, the value threshold is set a bit higher than the noise level.

t or v threshold + prior (t, v)

Log a point and the prior point whenever the absolute difference between its value and the value of the last logged point exceeds the set value threshold. Log a point without the prior point when the value threshold is not exceeded but instead the timestamp is higher than the timestamp of the last logged point by an amount equal to or exceeding the set time threshold. Can be used for signals that included steep jumps or spikes. Typically, the value threshold is set a bit higher than the noise level. 


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