CareerCup

Simply, since each query has a count, we build array of ranges and each range represent a query, then we use rand()%countSum , where countSum is the sum of all counts for all queries, after that we do binary search to see this fits in which range and we return the query that represent this range !

here is the code, O(N)

class Range : public pair<int,int>{
public:
	int queryIndex;

	Range(int f, int s, int qindex=0) : pair<int, int>(f, s), queryIndex(qindex){}



};


int binarySearch(vector< Range >& rangesList,int value, int L, int R){
	
	if (L <= R)
	{

		int m = (L + R) / 2;

		if (rangesList[m].first <= value && value <= rangesList[m].second)
			return m;
		else
		if (value > rangesList[m].second){
			return binarySearch(rangesList, value, m + 1, R);
		}
		else{
			return binarySearch(rangesList, value, L, m - 1);
		}
	}

	return -1;
}

string getRandomQuery(const vector< pair<string, int> >& queries){

	vector< Range > rangesList;

	int rangeCount = 0;

	int countSum = 0;

	for (int i = 0; i < queries.size(); i++){
		Range range(rangeCount, rangeCount + queries[i].second - 1, i);
		rangesList.push_back(range);

		countSum += queries[i].second;

		rangeCount += queries[i].second;
	}

	int randomValue = rand() % countSum;

	int index = binarySearch(rangesList, randomValue, 0, rangesList.size() - 1);

	return queries[index].first;
}

input - 
query - count
q1 	- 	3
q2 	-	5
q3	-	2
sum = 10; ( sum of all counts)

for(int i=0;i<k;i++) {
	int r = rand()%sum;
	if( !( r/count1) )
		select = q1; count1--;
	else if ( !(r/count1+count2) )
		select= q2; count2--;
	else
		select= q3; count3--;
	sum--;
	print select;
}

If I understand the answer properly, we will be getting a frequency of each query and we will use that as weighting for which query to return. In Python, I have made the assumption that the data is formatted as a list of tuples where the tuple contains the query and the count. E.g. [('dog', 5), ('cat', 7), ('cow', 2)]

from random import randint


def rand_query(queries):
    data = []
    x = 0
    for query in queries:
        data.append((query, x, x+query[1]))
        x += (query[1] + 1)

    max = sum(x[1] for x in queries)
    rand = randint(0, max)

    for entry in data:
        if rand >= entry[1] and rand <= entry[2]:
            return entry[0][0]


if '__main__' == __name__:
    print(rand_query([('dog', 5), ('cat', 7), ('cow', 2)]))

function QueryGenerator(queries) {
    
    //calculate total of all scores
    var sum = queries
        .map(function(x){return x[1];})
        .reduce(function(a,x) { return a+x;});

    var score = {};
    var scoreSum = 0;

    return function getQuery() {

        while (true) {

            if (scoreSum === sum) {
                //invalidate score
                score = {};
                scoreSum = 0;
            }

            var rand = Math.round(Math.random() * (queries.length - 1));

            var query = queries[rand][0];
            var freq = queries[rand][1];

            if (score[query] === undefined) {
                score[query] = 1;

                scoreSum++;
                return query;
            }
            else if (score[query] < freq) {
                score[query]++;

                scoreSum++;
                return query;
            }
        }
    }
}

similar to shuffling a deck of cards. However, in this case you have counts associated with each 'card/query'.