Solutions

Prerequisites

Before attempting this problem, you should be comfortable with:

Hash Maps - Using dictionaries to group and track maximum values by key
Sorting - Sorting values to find the top k elements efficiently
Heaps/Priority Queues - Maintaining the k largest elements using a min-heap of fixed size

1. Hash Map

Intuition

We need to pick three indices with distinct x-values and maximize the sum of their corresponding y-values. For each unique x-value, we only care about the maximum y-value associated with it, since choosing a smaller y-value for the same x would never be optimal.

After collecting the best y-value for each distinct x, we simply need the three largest values. If there are fewer than three distinct x-values, the answer is -1.

Algorithm

Build a hash map where each key is an x-value and the value is the maximum y-value seen for that x.
If the map has fewer than 3 entries, return -1.
Extract all the y-values from the map and sort them.
Return the sum of the three largest y-values.

class Solution:
    def maxSumDistinctTriplet(self, x: List[int], y: List[int]) -> int:
        mp = {}

        for i in range(len(x)):
            if x[i] not in mp:
                mp[x[i]] = y[i]
            
            mp[x[i]] = max(mp[x[i]], y[i])

        return -1 if len(mp) < 3 else sum(sorted(list(mp.values()))[-3:])

public class Solution {
    public int maxSumDistinctTriplet(int[] x, int[] y) {
        Map<Integer, Integer> mp = new HashMap<>();
        for (int i = 0; i < x.length; i++) {
            int key = x[i], val = y[i];
            mp.put(key, Math.max(mp.getOrDefault(key, 0), val));
        }
        if (mp.size() < 3) return -1;
        List<Integer> vals = new ArrayList<>(mp.values());
        Collections.sort(vals);
        int n = vals.size();
        return vals.get(n-1) + vals.get(n-2) + vals.get(n-3);
    }
}

class Solution {
public:
    int maxSumDistinctTriplet(vector<int>& x, vector<int>& y) {
        unordered_map<int,int> mp;
        for (int i = 0; i < x.size(); i++) {
            int key = x[i], val = y[i];
            mp[key] = max(mp[key], val);
        }
        if (mp.size() < 3) return -1;
        vector<int> vals;
        vals.reserve(mp.size());
        for (auto &p : mp) vals.push_back(p.second);
        sort(vals.begin(), vals.end());
        int n = vals.size();
        return vals[n-1] + vals[n-2] + vals[n-3];
    }
};

class Solution {
    /**
     * @param {number[]} x
     * @param {number[]} y
     * @return {number}
     */
    maxSumDistinctTriplet(x, y) {
        const mp = new Map();
        for (let i = 0; i < x.length; i++) {
            const key = x[i], val = y[i];
            mp.set(key, Math.max(mp.get(key) || 0, val));
        }
        if (mp.size < 3) return -1;
        const vals = Array.from(mp.values()).sort((a, b) => a - b);
        const n = vals.length;
        return vals[n-1] + vals[n-2] + vals[n-3];
    }
}

public class Solution {
    public int MaxSumDistinctTriplet(int[] x, int[] y) {
        var mp = new Dictionary<int,int>();
        for (int i = 0; i < x.Length; i++) {
            int key = x[i], val = y[i];
            if (mp.TryGetValue(key, out var existing)) {
                mp[key] = Math.Max(existing, val);
            } else {
                mp[key] = val;
            }
        }
        if (mp.Count < 3) return -1;
        var vals = mp.Values.ToList();
        vals.Sort();
        int n = vals.Count;
        return vals[n-1] + vals[n-2] + vals[n-3];
    }
}

func maxSumDistinctTriplet(x []int, y []int) int {
    mp := make(map[int]int)
    for i := 0; i < len(x); i++ {
        key, val := x[i], y[i]
        if existing, ok := mp[key]; ok {
            if val > existing {
                mp[key] = val
            }
        } else {
            mp[key] = val
        }
    }
    if len(mp) < 3 {
        return -1
    }
    vals := make([]int, 0, len(mp))
    for _, v := range mp {
        vals = append(vals, v)
    }
    sort.Ints(vals)
    n := len(vals)
    return vals[n-1] + vals[n-2] + vals[n-3]
}

class Solution {
    fun maxSumDistinctTriplet(x: IntArray, y: IntArray): Int {
        val mp = mutableMapOf<Int, Int>()
        for (i in x.indices) {
            val key = x[i]
            val value = y[i]
            mp[key] = maxOf(mp.getOrDefault(key, 0), value)
        }
        if (mp.size < 3) return -1
        val vals = mp.values.sortedDescending()
        return vals[0] + vals[1] + vals[2]
    }
}

class Solution {
    func maxSumDistinctTriplet(_ x: [Int], _ y: [Int]) -> Int {
        var mp = [Int: Int]()
        for i in 0..<x.count {
            let key = x[i], val = y[i]
            mp[key] = max(mp[key] ?? 0, val)
        }
        if mp.count < 3 { return -1 }
        let vals = mp.values.sorted()
        let n = vals.count
        return vals[n-1] + vals[n-2] + vals[n-3]
    }
}

Time & Space Complexity

Time complexity: $O(n \log n)$
Space complexity: $O(n)$

2. Hash Map + Min-Heap

Intuition

Instead of sorting all values to find the top 3, we can use a min-heap of size 3. As we iterate through the distinct y-values, we maintain only the three largest seen so far. This avoids the overhead of sorting the entire collection.

Whenever the heap exceeds size 3, we remove the smallest element. After processing all values, the heap contains exactly the three largest y-values (if at least 3 exist).

Algorithm

Build a hash map mapping each x-value to its maximum y-value.
Initialize an empty min-heap.
For each y-value in the map:
- Push it onto the heap.
- If heap size exceeds 3, pop the minimum.
If the heap has fewer than 3 elements, return -1.
Return the sum of all elements in the heap.

class Solution:
    def maxSumDistinctTriplet(self, x: List[int], y: List[int]) -> int:
        mp = {}
        for xi, yi in zip(x, y):
            mp[xi] = max(mp.get(xi, 0), yi)

        minHeap = []
        for val in mp.values():
            heapq.heappush(minHeap, val)
            if len(minHeap) > 3:
                heapq.heappop(minHeap)

        return -1 if len(minHeap) < 3 else sum(minHeap)

public class Solution {
    public int maxSumDistinctTriplet(int[] x, int[] y) {
        Map<Integer,Integer> mp = new HashMap<>();
        for (int i = 0; i < x.length; i++) {
            mp.put(x[i], Math.max(mp.getOrDefault(x[i], 0), y[i]));
        }
        PriorityQueue<Integer> pq = new PriorityQueue<>();
        for (int val : mp.values()) {
            pq.offer(val);
            if (pq.size() > 3) {
                pq.poll();
            }
        }

        if (pq.size() < 3) {
            return -1;
        }
        int sum = 0;
        while (!pq.isEmpty()) {
            sum += pq.poll();
        }
        return sum;
    }
}

class Solution {
public:
    int maxSumDistinctTriplet(vector<int>& x, vector<int>& y) {
        unordered_map<int,int> mp;
        for (int i = 0; i < x.size(); i++) {
            mp[x[i]] = max(mp[x[i]], y[i]);
        }
        priority_queue<int, vector<int>, greater<int>> pq;
        for (auto &p : mp) {
            pq.push(p.second);
            if (pq.size() > 3) {
                pq.pop();
            }
        }

        if (pq.size() < 3) return -1;
        int sum = 0;
        while (!pq.empty()) {
            sum += pq.top();
            pq.pop();
        }
        return sum;
    }
};

class Solution {
    /**
     * @param {number[]} x
     * @param {number[]} y
     * @return {number}
     */
    maxSumDistinctTriplet(x, y) {
        const mp = new Map();
        for (let i = 0; i < x.length; i++) {
            mp.set(x[i], Math.max(mp.get(x[i])||0, y[i]));
        }
        const heap = new MinPriorityQueue();
        for (const val of mp.values()) {
            heap.enqueue(val);
            if (heap.size() > 3) {
                heap.dequeue();
            }
        }
        if (heap.size() < 3) {
            return -1;
        }
        return heap.dequeue() + heap.dequeue() + heap.dequeue();
    }
}

public class Solution {
    public int MaxSumDistinctTriplet(int[] x, int[] y) {
        var mp = new Dictionary<int,int>();
        for (int i = 0; i < x.Length; i++) {
            int key = x[i], val = y[i];
            if (mp.TryGetValue(key, out var prev)) {
                mp[key] = Math.Max(prev, val);
            } else {
                mp[key] = val;
            }
        }
        var pq = new PriorityQueue<int,int>();
        foreach (var val in mp.Values) {
            pq.Enqueue(val, val);
            if (pq.Count > 3) {
                pq.Dequeue();
            }
        }

        if (pq.Count < 3) {
            return -1;
        }
        int sum = 0;
        while (pq.Count > 0) {
            sum += pq.Dequeue();
        }
        return sum;
    }
}

func maxSumDistinctTriplet(x []int, y []int) int {
    mp := make(map[int]int)
    for i := 0; i < len(x); i++ {
        key, val := x[i], y[i]
        if existing, ok := mp[key]; ok {
            if val > existing {
                mp[key] = val
            }
        } else {
            mp[key] = val
        }
    }

    minHeap := &IntHeap{}
    heap.Init(minHeap)
    for _, val := range mp {
        heap.Push(minHeap, val)
        if minHeap.Len() > 3 {
            heap.Pop(minHeap)
        }
    }

    if minHeap.Len() < 3 {
        return -1
    }
    sum := 0
    for minHeap.Len() > 0 {
        sum += heap.Pop(minHeap).(int)
    }
    return sum
}

type IntHeap []int
func (h IntHeap) Len() int           { return len(h) }
func (h IntHeap) Less(i, j int) bool { return h[i] < h[j] }
func (h IntHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }
func (h *IntHeap) Push(x any)        { *h = append(*h, x.(int)) }
func (h *IntHeap) Pop() any {
    old := *h
    n := len(old)
    x := old[n-1]
    *h = old[0 : n-1]
    return x
}

class Solution {
    fun maxSumDistinctTriplet(x: IntArray, y: IntArray): Int {
        val mp = mutableMapOf<Int, Int>()
        for (i in x.indices) {
            val key = x[i]
            val value = y[i]
            mp[key] = maxOf(mp.getOrDefault(key, 0), value)
        }

        val pq = PriorityQueue<Int>()
        for (value in mp.values) {
            pq.offer(value)
            if (pq.size > 3) {
                pq.poll()
            }
        }

        if (pq.size < 3) return -1
        var sum = 0
        while (pq.isNotEmpty()) {
            sum += pq.poll()
        }
        return sum
    }
}

class Solution {
    func maxSumDistinctTriplet(_ x: [Int], _ y: [Int]) -> Int {
        var mp = [Int: Int]()
        for i in 0..<x.count {
            let key = x[i], val = y[i]
            mp[key] = max(mp[key] ?? 0, val)
        }

        var vals = Array(mp.values)
        vals.sort()
        if vals.count < 3 { return -1 }

        let n = vals.count
        return vals[n-1] + vals[n-2] + vals[n-3]
    }
}

Time & Space Complexity

Time complexity: $O(n)$
Space complexity: $O(n)$

3. Greedy

Intuition

We can track the top 3 candidates in constant space by maintaining a sorted list of the best 3 (x, y) pairs seen so far. For each new element, we either update an existing entry (if the x-value matches) or insert it if the y-value is large enough to make the top 3.

The key insight is that we only ever need to compare against at most 3 entries. When an x-value already exists in our top 3, we update its y-value if the new one is larger and re-sort. Otherwise, we check if the new y-value can replace the smallest of our current top 3.

Algorithm

Maintain an array best of 3 pairs (x, y), initialized with sentinel values (like negative infinity for y).
For each (xi, yi) in the input:
- If xi matches any x in best, update that entry's y-value if yi is larger, then re-sort.
- Otherwise, insert (xi, yi) into the appropriate position if yi is larger than any of the current top 3 values.
If the smallest y-value in best is still a sentinel, return -1.
Return the sum of all three y-values.

class Solution:
    def maxSumDistinctTriplet(self, x: List[int], y: List[int]) -> int:
        best = [(None, float("-inf"))] * 3
        for xi, yi in zip(x, y):
            for i, (xj, yj) in enumerate(best):
                if xi == xj:
                    if yi > yj:
                        best[i] = (xi, yi)
                        best.sort(key=lambda t: t[1], reverse=True)
                    break
            else:
                if yi > best[0][1]:
                    best = [(xi, yi), best[0], best[1]]
                elif yi > best[1][1]:
                    best = [best[0], (xi, yi), best[1]]
                elif yi > best[2][1]:
                    best[2] = (xi, yi)

        return sum(v for _, v in best) if best[2][1] > float("-inf") else -1

public class Solution {
    public int maxSumDistinctTriplet(int[] x, int[] y) {
        List<int[]> best = new ArrayList<>();
        for (int i = 0; i < 3; i++) {
            best.add(new int[]{Integer.MIN_VALUE, Integer.MIN_VALUE});
        }
        for (int idx = 0; idx < x.length; idx++) {
            int xi = x[idx], yi = y[idx];
            boolean updated = false;
            for (int i = 0; i < 3; i++) {
                if (best.get(i)[0] == xi) {
                    if (yi > best.get(i)[1]) {
                        best.get(i)[1] = yi;
                        best.sort((a, b) -> Integer.compare(b[1], a[1]));
                    }
                    updated = true;
                    break;
                }
            }
            if (updated) continue;
            if (yi > best.get(0)[1]) {
                best.add(0, new int[]{xi, yi});
                best.remove(3);
            } else if (yi > best.get(1)[1]) {
                best.add(1, new int[]{xi, yi});
                best.remove(3);
            } else if (yi > best.get(2)[1]) {
                best.get(2)[1] = yi;
                best.get(2)[0] = xi;
            }
        }
        if (best.get(2)[1] == Integer.MIN_VALUE) {
            return -1;
        }
        return best.get(0)[1] + best.get(1)[1] + best.get(2)[1];
    }
}

class Solution {
public:
    int maxSumDistinctTriplet(vector<int>& x, vector<int>& y) {
        vector<pair<int,int>> best(3, {INT_MIN, INT_MIN});
        for (int i = 0; i < x.size(); i++) {
            int xi = x[i], yi = y[i];
            bool updated = false;
            for (int j = 0; j < 3; j++) {
                if (best[j].first == xi) {
                    if (yi > best[j].second) {
                        best[j].second = yi;
                        sort(best.begin(), best.end(),
                             [](auto &a, auto &b){ return a.second > b.second; });
                    }
                    updated = true;
                    break;
                }
            }
            if (updated) continue;
            if (yi > best[0].second) {
                best.insert(best.begin(), {xi, yi});
                best.pop_back();
            } else if (yi > best[1].second) {
                best.insert(best.begin()+1, {xi, yi});
                best.pop_back();
            } else if (yi > best[2].second) {
                best[2] = {xi, yi};
            }
        }
        if (best[2].second == INT_MIN) return -1;
        return best[0].second + best[1].second + best[2].second;
    }
};

class Solution {
    /**
     * @param {number[]} x
     * @param {number[]} y
     * @return {number}
     */
    maxSumDistinctTriplet(x, y) {
        let best = [
            [null, -Infinity],
            [null, -Infinity],
            [null, -Infinity]
        ];
        for (let i = 0; i < x.length; i++) {
            const xi = x[i], yi = y[i];
            let updated = false;
            for (let j = 0; j < 3; j++) {
                if (best[j][0] === xi) {
                    if (yi > best[j][1]) {
                        best[j][1] = yi;
                        best.sort((a, b) => b[1] - a[1]);
                    }
                    updated = true;
                    break;
                }
            }
            if (updated) continue;
            if (yi > best[0][1]) {
                best = [[xi, yi], best[0], best[1]];
            } else if (yi > best[1][1]) {
                best = [best[0], [xi, yi], best[1]];
            } else if (yi > best[2][1]) {
                best[2] = [xi, yi];
            }
        }
        return best[2][1] === -Infinity
            ? -1
            : best[0][1] + best[1][1] + best[2][1];
    }
}

public class Solution {
    public int MaxSumDistinctTriplet(int[] x, int[] y) {
        var best = new List<(int xi, int yi)> {
            (int.MinValue, int.MinValue),
            (int.MinValue, int.MinValue),
            (int.MinValue, int.MinValue)
        };
        for (int i = 0; i < x.Length; i++) {
            int xi = x[i], yi = y[i];
            bool updated = false;
            for (int j = 0; j < 3; j++) {
                if (best[j].xi == xi) {
                    if (yi > best[j].yi) {
                        best[j] = (xi, yi);
                        best = best.OrderByDescending(t => t.yi).ToList();
                    }
                    updated = true;
                    break;
                }
            }
            if (updated) continue;
            if (yi > best[0].yi) {
                best = new List<(int,int)> { (xi, yi), best[0], best[1] };
            } else if (yi > best[1].yi) {
                best = new List<(int,int)> { best[0], (xi, yi), best[1] };
            } else if (yi > best[2].yi) {
                best[2] = (xi, yi);
            }
        }
        return best[2].yi == int.MinValue
            ? -1
            : best[0].yi + best[1].yi + best[2].yi;
    }
}

func maxSumDistinctTriplet(x []int, y []int) int {
    const minInt = -1 << 31
    best := [][2]int{{minInt, minInt}, {minInt, minInt}, {minInt, minInt}}

    for i := 0; i < len(x); i++ {
        xi, yi := x[i], y[i]
        updated := false
        for j := 0; j < 3; j++ {
            if best[j][0] == xi {
                if yi > best[j][1] {
                    best[j][1] = yi
                    sort.Slice(best, func(a, b int) bool {
                        return best[a][1] > best[b][1]
                    })
                }
                updated = true
                break
            }
        }
        if updated {
            continue
        }
        if yi > best[0][1] {
            best = [][2]int{{xi, yi}, best[0], best[1]}
        } else if yi > best[1][1] {
            best = [][2]int{best[0], {xi, yi}, best[1]}
        } else if yi > best[2][1] {
            best[2] = [2]int{xi, yi}
        }
    }

    if best[2][1] == minInt {
        return -1
    }
    return best[0][1] + best[1][1] + best[2][1]
}

class Solution {
    fun maxSumDistinctTriplet(x: IntArray, y: IntArray): Int {
        var best = mutableListOf(
            intArrayOf(Int.MIN_VALUE, Int.MIN_VALUE),
            intArrayOf(Int.MIN_VALUE, Int.MIN_VALUE),
            intArrayOf(Int.MIN_VALUE, Int.MIN_VALUE)
        )

        for (i in x.indices) {
            val xi = x[i]
            val yi = y[i]
            var updated = false
            for (j in 0 until 3) {
                if (best[j][0] == xi) {
                    if (yi > best[j][1]) {
                        best[j][1] = yi
                        best.sortByDescending { it[1] }
                    }
                    updated = true
                    break
                }
            }
            if (updated) continue
            if (yi > best[0][1]) {
                best = mutableListOf(intArrayOf(xi, yi), best[0], best[1])
            } else if (yi > best[1][1]) {
                best = mutableListOf(best[0], intArrayOf(xi, yi), best[1])
            } else if (yi > best[2][1]) {
                best[2] = intArrayOf(xi, yi)
            }
        }

        return if (best[2][1] == Int.MIN_VALUE) -1
               else best[0][1] + best[1][1] + best[2][1]
    }
}

Time & Space Complexity

Time complexity: $O(n)$
Space complexity: $O(1)$

Common Pitfalls

Not Taking Maximum Y for Each X

When multiple indices share the same x-value, only the maximum corresponding y-value matters. Using any y-value instead of tracking the maximum for each distinct x leads to suboptimal triplet selections.

Forgetting to Handle Fewer Than Three Distinct X-Values

If there are fewer than 3 distinct x-values in the input, no valid triplet exists. Failing to check this condition before computing the sum causes index-out-of-bounds errors or returns an invalid result instead of -1.