Recommended 10 common programming thread usage, welcome to download!

The following small series for everyone to bring a Java concurrent programming _ thread pool use Method (detailed). Small series feel very good, now share to everyone, also for everyone to make a reference. Let's take a look at it together. One, the implicit coupling between task and execution strategy executor can decouple the submission of a task from the execution strategy of the task only if the task is of the same type and the execution time is not very different, in order to maximize performance, otherwise, such as some time-consuming tasks and short-duration tasks in a thread pool, Unless the thread pool is large, Otherwise it will cause deadlock and other problems 1. Thread starvation Deadlock is similar to: two tasks are submitted to a single thread pool, and the two tasks are interdependent, a task waits for another task, a deadlock occurs; a task must wait for the results of other tasks in the pool, and a hunger deadlock may occur 2. Thread pool size Note: The thread pool is large Small is also subject to other constraints, such as other resource pools: Database connection Pool If each task is a connection, the size of the thread pool is constrained by the size of the database connection Pool 3. Configure the Threadpoolexecutor thread pool instance: 1. Through Executors's factory side

1. How to use the thread pool of Java concurrent programming

Introduction: The following small series for everyone to bring a Java concurrent programming _ thread pool use Method (detailed). Small series feel very good, now share to everyone, also for everyone to make a reference. Let's take a look at it with a little knitting.

2. Python thread pool/process pool for concurrent programming

Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write the corresponding multithreaded/multi-process code, but when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-intensive, At this point we are going to write our own pool of threads/processes to change the time in space. But starting with Python3.2, the standard library provides us with the Concurrent.futures module

3. Python thread pool/process pool for concurrent programming

Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write the corresponding multithreaded/multi-process code, but when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-intensive, At this point we are going to write our own pool of threads/processes to change the time in space. But starting with Python3.2, the standard library provides us with the Concurrent.futures module, which provides Threadpoolexecutor and processpoolexecutor two classes for THR.

4. Detailed description of the thread pool/process pool for Python concurrent programming

Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write the corresponding multithreaded/multi-process code, but when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-intensive, At this point we are going to write our own pool of threads/processes to change the time in space. But starting with Python3.2, the standard library provides us with the Concurrent.futures module, which provides Threadpoolexecutor and processpoolexecutor two classes for THR.

5.. NET Programming thread Pool Insider

Summary: The thread pool, as the name implies, is a pooled object. Both task and TPL are useful to the thread pool, so knowing the inside of the thread pool can help you write better programs. As space is limited, here I only explain the following core