What is Best Fit Retrieval used for?

Best Fit Retrieval is a technique employed primarily to optimize the performance and efficiency of queries when working with large datasets in systems like AVEVA Historian Server. It is specifically designed to divide the total query time into subperiods, which allows for more manageable and focused data retrieval. By segmenting the time frame into smaller intervals, this method improves the server's ability to handle requests and reduces the overall response time, making it particularly effective for time-series data analysis.

This approach enhances the precision of the results by targeting specific time frames within the larger dataset, rather than attempting to retrieve all points at once, which can lead to increased load and slower performance. Consequently, using Best Fit Retrieval optimally balances the demand for data with the capacity of the historian server, ensuring that queries are resolved quickly and efficiently.

Other methods, such as returning all data points or aggregating data by averages, do not specifically utilize the concept of dividing query time into subperiods and may not optimize query performance as effectively as Best Fit Retrieval. Additionally, displaying real-time data does not involve this particular mechanism, as real-time data typically pertains to ongoing measurements rather than historical data segmentation.