gistfile1.txt

//precalc all distances to major research cities after import and store to respondents database/elastic
function precalcDistance(respondents, majorCities) {

    return respondents.map((respondent) => {
            let distances = majorCities.reduce((memo, {location}) => {
                let distance = haversine(location.location, respondent);
                memo[location.city] = distance;
                return memo;
            }, {});
            
            return { ...respondent, distances };
        })
}

//assuming respondents have the precalculated 'distances' property, we can run search over and over without unnecessary recalulcating.
function byDistance(respondents, researchCities, range) {
    
    return respondents
        .filter(respondent => researchCities.some(city => range > respondent.distances[city.location.city]))
        .sort((a, b) => a.firstName.toLowerCase() > b.firstName.toLowerCase());
}