| comments | difficulty | edit_url | rating | source | tags | |||
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true |
Medium |
1797 |
Weekly Contest 237 Q3 |
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You are given n tasks labeled from 0 to n - 1 represented by a 2D integer array tasks, where tasks[i] = [enqueueTimei, processingTimei] means that the ith task will be available to process at enqueueTimei and will take processingTimei to finish processing.
You have a single-threaded CPU that can process at most one task at a time and will act in the following way:
- If the CPU is idle and there are no available tasks to process, the CPU remains idle.
- If the CPU is idle and there are available tasks, the CPU will choose the one with the shortest processing time. If multiple tasks have the same shortest processing time, it will choose the task with the smallest index.
- Once a task is started, the CPU will process the entire task without stopping.
- The CPU can finish a task then start a new one instantly.
Return the order in which the CPU will process the tasks.
Example 1:
Input: tasks = [[1,2],[2,4],[3,2],[4,1]]
Output: [0,2,3,1]
Explanation: The events go as follows:
- At time = 1, task 0 is available to process. Available tasks = {0}.
- Also at time = 1, the idle CPU starts processing task 0. Available tasks = {}.
- At time = 2, task 1 is available to process. Available tasks = {1}.
- At time = 3, task 2 is available to process. Available tasks = {1, 2}.
- Also at time = 3, the CPU finishes task 0 and starts processing task 2 as it is the shortest. Available tasks = {1}.
- At time = 4, task 3 is available to process. Available tasks = {1, 3}.
- At time = 5, the CPU finishes task 2 and starts processing task 3 as it is the shortest. Available tasks = {1}.
- At time = 6, the CPU finishes task 3 and starts processing task 1. Available tasks = {}.
- At time = 10, the CPU finishes task 1 and becomes idle.
Example 2:
Input: tasks = [[7,10],[7,12],[7,5],[7,4],[7,2]]
Output: [4,3,2,0,1]
Explanation: The events go as follows:
- At time = 7, all the tasks become available. Available tasks = {0,1,2,3,4}.
- Also at time = 7, the idle CPU starts processing task 4. Available tasks = {0,1,2,3}.
- At time = 9, the CPU finishes task 4 and starts processing task 3. Available tasks = {0,1,2}.
- At time = 13, the CPU finishes task 3 and starts processing task 2. Available tasks = {0,1}.
- At time = 18, the CPU finishes task 2 and starts processing task 0. Available tasks = {1}.
- At time = 28, the CPU finishes task 0 and starts processing task 1. Available tasks = {}.
- At time = 40, the CPU finishes task 1 and becomes idle.
Constraints:
tasks.length == n1 <= n <= 1051 <= enqueueTimei, processingTimei <= 109
First, we sort the tasks by enqueueTime in ascending order. Next, we use a priority queue (min heap) to maintain the currently executable tasks. The elements in the queue are (processingTime, index), which represent the execution time and the index of the task. We also use a variable
Next, we simulate the execution process of the tasks.
If the current queue is empty, it means there are no executable tasks at the moment. We update enqueueTime of the next task and the current time enqueueTime less than or equal to
Then, we take out a task from the queue, add its index to the answer array, and update
We repeat the above process until the queue is empty and all tasks have been added to the queue.
The time complexity is
class Solution:
def getOrder(self, tasks: List[List[int]]) -> List[int]:
for i, task in enumerate(tasks):
task.append(i)
tasks.sort()
ans = []
q = []
n = len(tasks)
i = t = 0
while q or i < n:
if not q:
t = max(t, tasks[i][0])
while i < n and tasks[i][0] <= t:
heappush(q, (tasks[i][1], tasks[i][2]))
i += 1
pt, j = heappop(q)
ans.append(j)
t += pt
return ansclass Solution {
public int[] getOrder(int[][] tasks) {
int n = tasks.length;
int[][] ts = new int[n][3];
for (int i = 0; i < n; ++i) {
ts[i] = new int[] {tasks[i][0], tasks[i][1], i};
}
Arrays.sort(ts, (a, b) -> a[0] - b[0]);
int[] ans = new int[n];
PriorityQueue<int[]> q
= new PriorityQueue<>((a, b) -> a[0] == b[0] ? a[1] - b[1] : a[0] - b[0]);
int i = 0, t = 0, k = 0;
while (!q.isEmpty() || i < n) {
if (q.isEmpty()) {
t = Math.max(t, ts[i][0]);
}
while (i < n && ts[i][0] <= t) {
q.offer(new int[] {ts[i][1], ts[i][2]});
++i;
}
var p = q.poll();
ans[k++] = p[1];
t += p[0];
}
return ans;
}
}class Solution {
public:
vector<int> getOrder(vector<vector<int>>& tasks) {
int n = 0;
for (auto& task : tasks) task.push_back(n++);
sort(tasks.begin(), tasks.end());
using pii = pair<int, int>;
priority_queue<pii, vector<pii>, greater<pii>> q;
int i = 0;
long long t = 0;
vector<int> ans;
while (!q.empty() || i < n) {
if (q.empty()) t = max(t, (long long) tasks[i][0]);
while (i < n && tasks[i][0] <= t) {
q.push({tasks[i][1], tasks[i][2]});
++i;
}
auto [pt, j] = q.top();
q.pop();
ans.push_back(j);
t += pt;
}
return ans;
}
};func getOrder(tasks [][]int) (ans []int) {
for i := range tasks {
tasks[i] = append(tasks[i], i)
}
sort.Slice(tasks, func(i, j int) bool { return tasks[i][0] < tasks[j][0] })
q := hp{}
i, t, n := 0, 0, len(tasks)
for len(q) > 0 || i < n {
if len(q) == 0 {
t = max(t, tasks[i][0])
}
for i < n && tasks[i][0] <= t {
heap.Push(&q, pair{tasks[i][1], tasks[i][2]})
i++
}
p := heap.Pop(&q).(pair)
ans = append(ans, p.i)
t += p.t
}
return
}
type pair struct{ t, i int }
type hp []pair
func (h hp) Len() int { return len(h) }
func (h hp) Less(i, j int) bool { return h[i].t < h[j].t || (h[i].t == h[j].t && h[i].i < h[j].i) }
func (h hp) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *hp) Push(v any) { *h = append(*h, v.(pair)) }
func (h *hp) Pop() any { a := *h; v := a[len(a)-1]; *h = a[:len(a)-1]; return v }