Time Series Database Cache Module by Automation Professionals
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This composite type extends the SeriesFragment type to omit its data during serialization. Final data delivered by the system.db.getSeriesCache() script function and by the timeSeriesCache() expression function use this type. The cache subsystem can deliver very large datasets, which are troublesome if the designer saves the entire content with the windows that contain them.

serialization behavior varies by scope. Native java serialization will always omit the row data. This includes network messaging in Ignition. In the designer, these datasets' content will not be stored in the project.


from com.automation_pros.tsdbcache import TransientSeriesFragment
seriesdata = TransientSeriesFragment(sourcedata)
for columnpresent in seriesdata.spans:
	print columnpresent


PropertyData TypeDescription
boundDateSpanReturns the smallest DateSpan that contains all of the columns "present" information.
createdDateA timestamp initialized from now() when the object was created.
expiresDateA timestamp initialized from now() plus an expiration time when the object was created, and updated in the cache whenever the time frame & one or more columns satisfy a cache consumer.
spansList<ColumnSpans>A list of ColumnSpans timelines, one for each value column, indicating what time spans have data "present". When a SeriesFragment is initialized from a simple dataset, the spans are all set to the span of the timestamp column. When the cache engine delivers a SeriesFragment, its spans will cover all successfully queried time frames, whether there were rows returned or not.


ArgumentData TypeDescription
arg0DateSpanSubject datespan
returnsvoidMerge the subject datespan into all columns "present" information.
ArgumentData TypeDescription
Subject column(s) with "present" information
returnsvoidMerge the subject "present" for the corresponding column. Ignore data for column names that aren't present in the dataset.
seriesdata.addSpans(col, spans)
ArgumentData TypeDescription
colStringColumn name
spansDateSpansData "present" information
returnsvoidMerge the "present" information for the corresponding column.
ArgumentData TypeDescription
arg0SeriesFragmentComparison subject
returnsintImplements natural ordering for SeriesFragment objects, which will sort by creation timestamp, newest first.
ArgumentData TypeDescription
arg0DateSpanSubject datespan
returnsList<ColumnSpans>Reverse the sense of the data "present" time spans in reference to the subject time span. The resulting list details the gaps in the data.
ArgumentData TypeDescription
Column selector
returnsColumnSpansThe selected column's data "present" information. Note that an integer selector is the dataset's column index, but column zero doesn't have a ColumnSpans object. The selector must be >0.
ArgumentData TypeDescription
arg0DateSpanSubject datespan
returnsbooleanTrue if any column's data "present" time spans have a gap in reference to the subject time span.
returnsSeriesFragmentProvides the reverse of toTransient() for this dataset, while retaining the other features of a series fragment.

WARNING: Datasets converted from transient to persistent by the persistent() method can be very large. If you do so, avoid saving the project when large datasets are present, or you will suffer from long serialization delays.

See the documentation for the built-in Dataset class in the User Manual, for more detail on using datasets in scripts.