pool

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 providers like MessageDigest , Signature , Cipher , KeyFactory , ... (because of the cost of the

Is there a way to use both ThreadPool and Pool in python to parallelise a loop by specifying the number of CPUs and cores you wish to use? For example I would have a loop execute as: from multiprocessing.dummy import Pool as ThreadPool from tqdm import tqdm import numpy as np def my_function(x): return x + 1 pool = ThreadPool(4) my_array = np.arange(0,1e6,1) results = list(tqdm(pool.imap(my_function, my_array),total=len(my_array))) For 4 cores but it I wanted to spread these out on multiple CPUs as well, is there a simple way to adapt the code? You are confusing between a core and a CPU.

I have googled a fair bit on this, but not been able to find an exact answer. We are seeing the following errors in our logs: Timeout expired. The timeout period elapsed prior to obtaining a connection from the pool. This may have occurred because all pooled connections were in use and max pool size was reached. Stack Trace: at MySql.Data.MySqlClient.MySqlPool.GetConnection() at MySql.Data.MySqlClient.MySqlConnection.Open() I can monitor client connections on the MySQL server (and they appear fine), but the error is occurring in the ASP application. There is nothing obvious in my code, so I

I have a python function funz that returns every time a different array of length p. I need to run this function different times and then to compute the mean of each value. I can do this with a for loop but it takes a lot of times. I am trying to use the library multiprocessing but I get into an error. import sklearn as sk import numpy as np from sklearn.base import BaseEstimator, TransformerMixin from sklearn import preprocessing,linear_model, cross_validation from scipy import stats from multiprocessing import Pool class stabilize(BaseEstimator,TransformerMixin): def __init__(self,sim=3,n

From ： http://www.codeweblog.com/hibernate-using-c3p0-connection-pooling/ c3p0是开源JDBC连接池，Hibernate的发布版也有此功能。这篇文章描述怎样使用Hibernate来配置从c3p0。C3p0连接池配置很简单，只需要添加如下内容到 hibernate.cfg.xml文件：（ 原文： c3p0 for open source's JDBC connection pool, with the release hibernate. This article describes how to use the hibernate configuration in c3p0. c3p0 connection pool configuration is very simple, only needs to increase in hibernate.cfg.xml: ） <property name="hibernate.c3p0.max_size"> 20 </ property> <! - The smallest number of connections -> <property name="hibernate.c3p0.min_size"> 5 </ property> <! - Get

I read this Questions about Java's String pool and understand the basic concept of string pool but still don't understand the behavior. First: it works if you directly assign the value and both s1 and s2 refer to the same object in the pool String s1 = "a" + "bc"; String s2 = "ab" + "c"; System.out.println("s1 == s2? " + (s1 == s2)); But then if I change the string s1+="d", then the pool should have a string object "abcd"? then when I change the s2+="d", it should find the string object "abcd" in the pool and should assign the object to s2? but it doesn't and they aren't referred to the same