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将判题控制器由多线程修改为多进程
我一定是sb了，使用Python的多线程跑cpu密集型的应用。 由于Python的GIL的存在，导致在cpu上每次只能有一个线程在运行。如果一个线程运行，而且cpu时间是3秒的话，那实际运行时间将大约3秒。如果两个线程同时在进行，那总运行时间几乎要翻倍。 而换用多进程之后，单个进行运行实际时间只是稍微大于cpu时间，两个进程同时运行的时候，总的时间也是cpu时间稍微增加。 同时Python2在多进程之间运行类方法的时候存在bug，使用了 http://stackoverflow.com/questions/1816958/cant-pickle-type-instancemethod-when-using-pythons-multiprocessing-pool-ma/7309686#7309686 的方法进行patch。然后不同进程之间共享的时候，要防止循环依赖，参考 http://stackoverflow.com/questions/25382455/python-notimplementederror-pool-objects-cannot-be-passed-between-processes
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virusdefender
parent
b43dfe37c8
commit
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@ -2,11 +2,32 @@
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import json
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import time
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import commands
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from Queue import Queue
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from thread_pool import ThreadPool
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from multiprocessing import Pool
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from settings import max_running_number, lrun_gid, lrun_uid, use_tmpfs
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from consts import Language, Result
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from copy_reg import pickle
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from types import MethodType
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# 下面两个函数告诉Python怎么pickle类实例中的方法，否则Python2会报错，是Python2的已知bug
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def _pickle_method(method):
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func_name = method.im_func.__name__
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obj = method.im_self
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cls = method.im_class
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return _unpickle_method, (func_name, obj, cls)
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def _unpickle_method(func_name, obj, cls):
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for cls in cls.mro():
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try:
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func = cls.__dict__[func_name]
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except KeyError:
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pass
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else:
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break
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return func.__get__(obj, cls)
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class JudgeClientException(Exception):
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pass
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@ -15,24 +36,25 @@ class JudgeClientException(Exception):
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class JudgeClient(object):
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def __init__(self, language, exec_file_path, max_cpu_time,
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max_real_time, max_memory, test_case_dir):
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# 语言 c cpp 或者 java
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"""
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:param language: 语言，见consts.py
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:param exec_file_path: 可执行文件路径
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:param max_cpu_time: 最大cpu时间，单位ms
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:param max_real_time: 最大执行时间，单位ms
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:param max_memory: 最大内存，单位MB
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:param test_case_dir: 测试用户文件夹路径
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:return:返回结果list
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"""
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self.language = language
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# 可执行文件路径，比如 /root/1/a.out /root/1/Main.class
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self.exec_file_path = exec_file_path
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# 最大的cpu时间 单位ms
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self.max_cpu_time = max_cpu_time
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# 最大实际运行时间 单位ms
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self.max_real_time = max_real_time
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# 最大cpu占用，注意不要小于500000 单位byte
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self.max_memory = max_memory
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# 测试用例文件路径，比如/root/testcase/1/
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self.test_case_dir = test_case_dir
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# 判题结果队列
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self.result_queue = Queue()
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# 线程池
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self.thread_pool = ThreadPool(size=max_running_number,
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result_queue=self.result_queue)
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self.thread_pool.start()
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# 进程池
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self.pool = Pool(processes=max_running_number)
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# 结果数组
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self.results = []
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# 测试用例配置项
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self.test_case_info = self.load_test_case_info()
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@ -67,9 +89,9 @@ class JudgeClient(object):
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# todo 系统调用白名单 chroot等参数
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# fixme 时间的单位问题
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command = "lrun" + \
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" --max-cpu-time " + str(self.max_cpu_time) + \
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" --max-real-time " + str(self.max_real_time) + \
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" --max-memory " + str(self.max_memory) + \
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" --max-cpu-time " + str(self.max_cpu_time / 1000.0) + \
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" --max-real-time " + str(self.max_real_time / 1000.0) + \
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" --max-memory " + str(self.max_memory * 1000 * 1000) + \
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" --network false" + \
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" --uid " + str(lrun_uid) + \
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" --gid " + str(lrun_gid)
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@ -98,6 +120,8 @@ class JudgeClient(object):
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"CPU_TIME": "cpu_time",
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"REALTIME": "real_time",
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"REAL_TIME": "real_time",
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"TERMSIG": "term_sig",
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"SIGNALED": "siginaled",
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"EXITCODE": "exit_code",
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"EXCEED": "exceed"}
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for line in lines:
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@ -112,6 +136,10 @@ class JudgeClient(object):
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result[translate[name]] = float(value) * 1000
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elif name == "EXITCODE":
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result[translate[name]] = int(value)
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elif name == "TERMSIG":
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result[translate[name]] = int(value)
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elif name == "SIGNALED":
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result[translate[name]] = int(value)
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elif name == "EXCEED":
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if value == "none":
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result[translate[name]] = None
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@ -130,7 +158,7 @@ class JudgeClient(object):
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run_result["test_case_id"] = test_case_id
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# 如果返回值非0，代表非正常结束
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if run_result["exit_code"]:
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if run_result["exit_code"] or run_result["term_sig"] or run_result["siginaled"]:
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run_result["result"] = Result.RUNTIME_ERROR
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return run_result
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@ -148,22 +176,30 @@ class JudgeClient(object):
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run_result["result"] = Result.ACCEPTED
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return run_result
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def collect_result(self, result):
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self.results.append(result)
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def run(self):
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# 添加到任务队列
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for i in range(self.test_case_info["test_case_number"]):
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self.thread_pool.append_job(self.judge_one, i + 1)
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self.pool.apply_async(self.judge_one, args=(i + 1, ),
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callback=self.collect_result)
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self.pool.close()
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self.pool.join()
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print self.results
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self.thread_pool.join()
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self.thread_pool.stop()
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for i in range(self.test_case_info["test_case_number"]):
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print self.result_queue.get(block=False)
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def __getstate__(self):
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# 不同的pool之间进行pickle的时候要排除自己，否则报错
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self_dict = self.__dict__.copy()
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del self_dict['pool']
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return self_dict
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pickle(MethodType, _pickle_method, _unpickle_method)
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client = JudgeClient(language=Language.C,
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exec_file_path="/var/judge/a.out",
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max_cpu_time=1000,
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max_real_time=2000,
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max_memory=600000,
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max_cpu_time=1000000,
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max_real_time=200000,
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max_memory=1,
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test_case_dir="/var/test_case/1/")
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client.run()
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