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author | Haidong Ji | 2019-02-21 21:32:22 -0600 |
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committer | Haidong Ji | 2019-02-21 21:32:22 -0600 |
commit | 421f2e783af773712a5e7a799f7cbaca69ab7a21 (patch) | |
tree | 1bcc356b41444fcc03bfd84e86d5a91fa3b38c49 | |
parent | 602995c859265493dd94996d1626e6de44d512e6 (diff) |
Priority queue parallel job processing done!
Not too bad since I worked it out in Java. Good practice of heapq module in Python! A lot of fun :)
-rw-r--r-- | sources/job_queue.py | 47 | ||||
-rw-r--r-- | tests/job_queueTest.py | 28 |
2 files changed, 75 insertions, 0 deletions
diff --git a/sources/job_queue.py b/sources/job_queue.py new file mode 100644 index 0000000..8928d4a --- /dev/null +++ b/sources/job_queue.py @@ -0,0 +1,47 @@ +# python3 + +from heapq import heappush, heappop +from collections import namedtuple + +AssignedJob = namedtuple("AssignedJob", ["worker", "started_at"]) + + +def assign_jobs(n_workers, jobs): + # Naive algorithm + result = [] + next_free_time = [0] * n_workers + for job in jobs: + next_worker = min(range(n_workers), key=lambda w: next_free_time[w]) + result.append(AssignedJob(next_worker, next_free_time[next_worker])) + next_free_time[next_worker] += job + + return result + + +def assign_jobs_improved(n_workers, jobs): + result = [] + worker_priority_q = [] + for i in range(n_workers): + heappush(worker_priority_q, (0, i)) + + for j in range(len(jobs)): + pair = heappop(worker_priority_q) + result.append(AssignedJob(pair[1], pair[0])) + heappush(worker_priority_q, (pair[0] + jobs[j], pair[1])) + + return result + + +def main(): + n_workers, n_jobs = map(int, input().split()) + jobs = list(map(int, input().split())) + assert len(jobs) == n_jobs + + assigned_jobs = assign_jobs_improved(n_workers, jobs) + + for job in assigned_jobs: + print(job.worker, job.started_at) + + +if __name__ == "__main__": + main() diff --git a/tests/job_queueTest.py b/tests/job_queueTest.py new file mode 100644 index 0000000..ac95c35 --- /dev/null +++ b/tests/job_queueTest.py @@ -0,0 +1,28 @@ +import unittest + +from collections import namedtuple + +AssignedJob = namedtuple("AssignedJob", ["worker", "started_at"]) + +from sources.job_queue import assign_jobs, assign_jobs_improved + + +class MyTestCase(unittest.TestCase): + def test(self): + num_workers = 2 + jobs = [1, 2, 3, 4, 5] + result = [AssignedJob(0, 0), AssignedJob(1, 0), AssignedJob(0, 1), AssignedJob(1, 2), AssignedJob(0, 4)] + self.assertListEqual(result, assign_jobs_improved(num_workers, jobs)) + + def test1(self): + num_workers = 4 + jobs = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] + result = [AssignedJob(0, 0), AssignedJob(1, 0), AssignedJob(2, 0), AssignedJob(3, 0), AssignedJob(0, 1), + AssignedJob(1, 1), AssignedJob(2, 1), AssignedJob(3, 1), AssignedJob(0, 2), AssignedJob(1, 2), + AssignedJob(2, 2), AssignedJob(3, 2), AssignedJob(0, 3), AssignedJob(1, 3), AssignedJob(2, 3), + AssignedJob(3, 3), AssignedJob(0, 4), AssignedJob(1, 4), AssignedJob(2, 4), AssignedJob(3, 4)] + self.assertListEqual(result, assign_jobs_improved(num_workers, jobs)) + + +if __name__ == '__main__': + unittest.main() |