Discovering common elements in various arrays of objects

Details:

record1 = [{"site": "The Blue Tiger", "zipcode": "E1 6QE"}, {"site": "Cafe Deluxe", "zipcode": "E6 5FD"}]
record2 = [{"site": "Blue Tiger", "zipcode": "E1 6QE"}, {"site": "Deluxe Cafe", "zipcode": "E6 5FD"}]
record3 = [{"site": "The Blue Tiger", "zipcode": "E1 6QE"}, {"site": "Deluxe Café", "zipcode": "E6 5FD"}]
//record1 size - 350 | record2 size - 544 | record3 size - 88

I am utilizing a fuzzy matching function to identify similar elements in the records. Currently, I merge the 3 records into one array, iterate through it twice with nested loops, and then perform fuzzy comparisons on the site field.

merged.forEach(function (a) {
        merged.forEach(function (b) {
            if (fuzz.token_sort_ratio(a.site, b.site) > 80) {
                //Actions 
            }
        });
    });

Is there a more efficient approach for this task rather than using nested loops? The total size of the combined array is 958, leading to 917,764 iterations, which doesn't seem optimal. However, due to the unpredictable nature of the site values, using the .find() function may not be suitable. Any suggestions?

javascriptnode.jsarraysperformancelogic

Answer №1

To optimize the process, consider creating a map of locations and storing the results in a quadtree data structure. JavaScript supports the use of quadtree - check out https://github.com/timohausmann/quadtree-js

I have personally utilized quadtree successfully in my work (implemented in C++). When dealing with large datasets, it proved to be at least 10 times faster than a quadratic algorithm.

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