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Though Trident and Summingbird implicitly support sliding window operation, they do not provide a window operator with which user can operate on tuples collected during arbitrary time intervals conveniently.
So we devise WINDOW operator to deal with time window operation.
From left to right: An image is first smoothed using GRAB window operator.
Obviously, it improves the reconstruction performance from the aspect with window operator.
The WINDOW operator first accumulates a certain amount of tuples in a specified time interval.
Remark 3. Explanations of window operator: For the GS-type approach with window function in Algorithm 1, we present some trivial explanations why window operator w is helpful to improve the reconstruction performance.
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At its core, LARS formulas extend propositional logic with generic window operators and additional controls to handle temporal information.
Besides, there are several recent works about window operators and their functions.
To cope with the volume of data, query languages often extend existing approaches for static data by means of window operators that return snapshots of recent data.
In other words, the operator di−1 has a right inverse Π i modulo class I Open image in new window operators on solutions to d i u=0.
As a final note, we observe that modern SPEs consider windows as special operators in their processing graph and can use multiple window operators in the same graph see Fig. 1.
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Justyna Jupowicz-Kozak
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