Optimizing Geo-Query Performance and Caching Strategy in Xano

The State Changers met to discuss and resolve issues associated with their Xano project, specifically, improving the speed and accuracy of location/service data for users. The primary issues were related to a caching system, geopoint creation, and resolving scope issues in nested loops in the context of querying records from world cities.

Initially, a rather slow system had been established to query a database to return the nearest city, based on longitude and latitude values. However, this process was time-consuming (6-7 seconds) considering the database had around 28,200 rows. To make this process faster and more efficient, the State Changers reworked the process by developing a Conditional Query system within Xano that uses built-in geotracking features. This significantly improved the system, reducing the processing time to 0.61 seconds. Another topic of discussion was enabling caching, to instantly return location data for users within the same or nearby geographical area, instead of repeating the entire query. However, with the improved processing time using the new conditional query, they realized caching might not be necessary anymore. The meeting also addressed a problem with an airport lookup feature, which, initially was delivering overlapping results for different geographical areas. The problem rooted from a scoping issue in a system that was coded using a low-code platform, and was fixed by placing the area-identifying component inside the loop for cities, thus resetting it for each new lookup. The insights obtained from this meeting could be helpful to individuals looking for ways to speed up location-based queries, rectify scoping issues, or optimise data handling in low-code platforms.

(Source: Office Hours 11/2 )

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