pool

Python: How to use Value and Array in Multiprocessing pool

由 。_饼干妹妹 提交于 2019-12-03 13:36:04
问题 For multiprocessing with Process , I can use Value, Array by setting args param. With multiprocessing with Pool , how can I use Value, Array. There is nothing in the docs on how to do this. from multiprocessing import Process, Value, Array def f(n, a): n.value = 3.1415927 for i in range(len(a)): a[i] = -a[i] if __name__ == '__main__': num = Value('d', 0.0) arr = Array('i', range(10)) p = Process(target=f, args=(num, arr)) p.start() p.join() print(num.value) print(arr[:]) I am trying to use

Profiling a python multiprocessing pool

由 柔情痞子 提交于 2019-12-03 13:13:45
问题 I'm trying to run cProfile.runctx() on each process in a multiprocessing pool, to get an idea of what the multiprocessing bottlenecks are in my source. Here is a simplified example of what I'm trying to do: from multiprocessing import Pool import cProfile def square(i): return i*i def square_wrapper(i): cProfile.runctx("result = square(i)", globals(), locals(), "file_"+str(i)) # NameError happens here - 'result' is not defined. return result if __name__ == "__main__": pool = Pool(8) results =

The best alternative for String flyweight implementation in Java

由 穿精又带淫゛_ 提交于 2019-12-03 10:39:17
问题 My application is multithreaded with intensive String processing. We are experiencing excessive memory consumption and profiling has demonstrated that this is due to String data. I think that memory consumption would benefit greatly from using some kind of flyweight pattern implementation or even cache (I know for sure that Strings are often duplicated, although I don't have any hard data in that regard). I have looked at Java Constant Pool and String.intern, but it seems that it can provoke

Python, multithreading too slow, multiprocess

由 风流意气都作罢 提交于 2019-12-03 10:09:00
问题 I'm a multiprocessing newbie, I know something about threading but I need to increase the speed of this calculation, hopefully with multiprocessing: Example Description: sends string to a thread, alters string + benchmark test, send result back for printing. from threading import Thread class Alter(Thread): def __init__(self, word): Thread.__init__(self) self.word = word self.word2 = '' def run(self): # Alter string + test processing speed for i in range(80000): self.word2 = self.word2 + self

How to get the amount of “work” left to be done by a Python multiprocessing Pool?

由 独自空忆成欢 提交于 2019-12-03 07:08:09
问题 So far whenever I needed to use multiprocessing I have done so by manually creating a "process pool" and sharing a working Queue with all subprocesses. For example: from multiprocessing import Process, Queue class MyClass: def __init__(self, num_processes): self._log = logging.getLogger() self.process_list = [] self.work_queue = Queue() for i in range(num_processes): p_name = 'CPU_%02d' % (i+1) self._log.info('Initializing process %s', p_name) p = Process(target = do_stuff, args = (self.work

Difference between pool and cluster

由 泪湿孤枕 提交于 2019-12-03 06:29:08
From a purest perspective, they kind of feel like identical concepts. Both manage sets of reosurces/nodes and control their access from or by external components. With a pool, you borrow and return these resources/nodes to and from the pool. With a cluster, you have a load balancer sitting in front of the resources/nodes and you hit the load balancer with a request. In both cases you have absolutely no control over which resource/node your request/borrow gets mapped to. So I pose the question: what's the fundamental difference between the "pool" pattern and a load-balanced cluster? A pool is

What is the difference between maxTotal and maxIdle in Apache Commons Pool 2?

由 六眼飞鱼酱① 提交于 2019-12-03 06:25:11
问题 I'm using the Apache Commons Pool 2 implementation to have object pool mechanism for my application. As of now, I have set the default value of maxTotal() and maxIdle() as 10 in my code. But I am not able to understand what is the difference between them ? What if I set the maxIdle() as a value very small (let's say 0) or very large (equal to maxTotal() ) ? Note: Apache classes internally recommends a default value of 8 to both of the above configs. 回答1: A connection pool is a technique for

To Pool or not to Pool java crypto service providers

由 一个人想着一个人 提交于 2019-12-03 05:15:42
问题 Solution MessageDigest => create new instances as often as needed KeyFactory => use a single shared instance SecureRandom => use a StackObjectPool Cipher => use a StackObjectPool Question I face a regular dilemna while coding security frameworks : "to pool or not to pool" Basically this question is divided on two "groups" : Group 1 : SecureRandom because the call to nextBytes(...) is synchronized and it could become a bottleneck for a WebApp / a multi-threaded app Group 2 : Crypto service

Python: How to use Value and Array in Multiprocessing pool

由 倖福魔咒の 提交于 2019-12-03 03:30:56
For multiprocessing with Process , I can use Value, Array by setting args param. With multiprocessing with Pool , how can I use Value, Array. There is nothing in the docs on how to do this. from multiprocessing import Process, Value, Array def f(n, a): n.value = 3.1415927 for i in range(len(a)): a[i] = -a[i] if __name__ == '__main__': num = Value('d', 0.0) arr = Array('i', range(10)) p = Process(target=f, args=(num, arr)) p.start() p.join() print(num.value) print(arr[:]) I am trying to use Value, Array within the code snippet below. import multiprocessing def do_calc(data): # access num or #

what's the difference between boost::pool<>::malloc and boost::pool<>::ordered_malloc, and when should I use boost::pool<>::ordered_malloc?

由 守給你的承諾、 提交于 2019-12-02 23:00:21
I'm using boost.pool, but I don't know when to use boost::pool<>::malloc and boost::pool<>::ordered_malloc ? so, what's the difference of boost::pool<>::malloc and boost::pool<>::ordered_malloc ? when should I use boost::pool<>::ordered_malloc ? First, we should know the basic idea behind the Boost Pool library: simple_segregated_storage , it is similar to a singly linked list, and responsible for partitioning a memory block into fixed-size chunks: A memory pool keeps a free list of memory chunks. So we mentioned blocks and chunks: the memory pool uses new or malloc to allocate a memory block
订阅 pool