Time-series data aggregation query method, system, device and storage medium
A time series data and query method technology, applied in the field of data processing, can solve the problem of not allowing one-by-one comparison, and achieve the effect of shortening the processing time
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[0057] The invention belongs to the technical field of data processing, and specifically judges query options submitted by users; judges the linear monotonicity of input expressions; divides each sub-expression to form a linear inequality group composed of linear inequalities; proposes For the coefficients of linear inequalities, call Hatchyan's algorithm to judge whether the linear inequalities have a solution; through the linear monotone judgment of complex query expressions, it solves how to judge the correctness of the expression grammar and how to judge the expression in the expression Whether it is linear is judged, different situations are separated for processing, and the processing time is shortened; the application of the Hatchyan algorithm in the present invention is optimized to shorten the processing time.
[0058] to combine figure 1 As shown, the first object of the present invention is to provide an aggregate query method for time series data, the specific meth...
Embodiment
[0072] Such as Figure 1-2 As shown, the aggregation query method of time series data, the specific method includes:
[0073] Provide historical data query and calculation functions under complex conditions, and input query conditions in the form of expressions;
[0074] Query and count the historical values of the target measuring points under the condition that the value range of multiple measuring points is satisfied, for example, the average boiler efficiency in the last 30 days under the condition that the calculated active power is not less than 300MW and the plant power consumption rate is less than 9%. value;
[0075] Query and count the historical values of the target measuring points in multiple time intervals, such as calculating the average power consumption rate of the previous working week and the previous working week, and the data that occurred on weekends during the period is not within the statistical range;
[0076] The arithmetic mean value of multipl...
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