Question

我有一个设置，其中Tornado被用作工人的传递方式。 Tornado收到请求，该请求将此请求发送给N个工作人员，汇总结果并将其发送回客户端。哪个工作正常，除非由于某种原因超时发生 - 然后我有内存泄漏。

我有一个类似于这个伪代码的设置：

workers = ["http://worker1.example.com:1234/",
           "http://worker2.example.com:1234/", 
           "http://worker3.example.com:1234/" ...]

class MyHandler(tornado.web.RequestHandler):
    @tornado.web.asynchronous
    def post(self):
        responses = []

        def __callback(response):
            responses.append(response)
            if len(responses) == len(workers):
                self._finish_req(responses)

        for url in workers:
            async_client = tornado.httpclient.AsyncHTTPClient()
            request = tornado.httpclient.HTTPRequest(url, method=self.request.method, body=body)
            async_client.fetch(request, __callback) 

    def _finish_req(self, responses):
        good_responses = [r for r in responses if not r.error]
        if not good_responses:
            raise tornado.web.HTTPError(500, "\n".join(str(r.error) for r in responses))
        results = aggregate_results(good_responses)
        self.set_header("Content-Type", "application/json")
        self.write(json.dumps(results))
        self.finish()

application = tornado.web.Application([
    (r"/", MyHandler),
])

if __name__ == "__main__":
    ##.. some locking code 
    application.listen()
    tornado.ioloop.IOLoop.instance().start()

我做错了什么？内存泄漏来自哪里？

Answer 1

我不知道问题的根源，似乎gc应该可以照顾它，但是你可以尝试两件事。

第一种方法是简化一些引用（看起来在RequestHandler完成时仍可能引用responses）：

class MyHandler(tornado.web.RequestHandler):
    @tornado.web.asynchronous
    def post(self):
        self.responses = []

        for url in workers:
            async_client = tornado.httpclient.AsyncHTTPClient()
            request = tornado.httpclient.HTTPRequest(url, method=self.request.method, body=body)
            async_client.fetch(request, self._handle_worker_response) 

    def _handle_worker_response(self, response):
        self.responses.append(response)
        if len(self.responses) == len(workers):
            self._finish_req()

    def _finish_req(self):
        ....

如果这不起作用，您可以随时手动调用垃圾收集：

import gc
class MyHandler(tornado.web.RequestHandler):
    @tornado.web.asynchronous
    def post(self):
        ....

    def _finish_req(self):
        ....

    def on_connection_close(self):
        gc.collect()

Answer 2

代码看起来不错。泄漏可能在龙卷风内部。

我只是偶然发现了这条线：

async_client = tornado.httpclient.AsyncHTTPClient()

你知道这个构造函数中的实例化魔法吗？来自文档：

"""
The constructor for this class is magic in several respects:  It actually
creates an instance of an implementation-specific subclass, and instances
are reused as a kind of pseudo-singleton (one per IOLoop).  The keyword
argument force_instance=True can be used to suppress this singleton
behavior.  Constructor arguments other than io_loop and force_instance
are deprecated.  The implementation subclass as well as arguments to
its constructor can be set with the static method configure()
"""

实际上，你不需要在循环中执行此操作。（在另一它，它不应该造成任何伤害。）但是你实施的是哪一个使用CurlAsyncHTTPClient还是SimpleAsyncHTTPClient？

如果是SimpleAsyncHTTPClient，请注意代码中的此注释：

"""
This class has not been tested extensively in production and
should be considered somewhat experimental as of the release of
tornado 1.2. 
"""

您可以尝试切换到CurlAsyncHTTPClient。或者按照 Nikolay Fominyh的建议并跟踪对__callback（）的调用。

断开的连接上的龙卷风内存泄漏

2 个答案: