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The following editor will bring you an article about java concurrent programming_how to use thread pool (detailed explanation). The editor thinks it’s pretty good, so I’ll share it with you now and give it as a reference. Let’s follow the editor to take a look. 1. Implicit coupling between tasks and execution strategies Executor can decouple task submission and task execution strategies. Only tasks of the same type and little difference in execution time can achieve maximum performance. , otherwise, if you put some long-consuming tasks and short-consuming tasks in a thread pool, unless the thread pool is very large, it will cause deadlock and other problems 1. Thread starvation deadlock is similar to: submitting two tasks to A single-threaded pool, and the two tasks are interdependent. If one task waits for another task, a deadlock will occur; the pool is not well defined: a task must wait for the running results of other tasks in the pool, and starvation may occur. Deadlock 2. Thread pool size Note: The size of the thread pool is also subject to other restrictions, such as other resource pools: database connection pool. If each task is a connection, then the size of the thread pool is subject to the size of the database connection pool 3 .Configure the ThreadPoolExecutor thread pool instance: 1. Through the factory method of Executors
1. Detailed explanation of how to use the thread pool in java concurrent programming
Introduction: The following editor will bring you an article on java concurrent programming_how to use thread pools (detailed explanation). The editor thinks it’s pretty good, so I’ll share it with you now and give it as a reference. Let’s follow the editor to take a look
2. Python concurrent programming thread pool/process pool
Introduction: Introduction The Python standard library provides us with threading and multiprocessing modules to write corresponding multi-threading/multi-process code. However, when the project reaches a certain scale, it is frequently created/destroyed. Processes or threads consume a lot of resources. At this time, we have to write our own thread pool/process pool to trade space for time. But starting from Python3.2, the standard library provides us with the concurrent.futures module
3. Python concurrent programming thread pool/process pool
Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write corresponding multi-threading/multi-process code, but when the project When reaching a certain scale, frequent creation/destruction of processes or threads is very resource intensive. At this time, we have to write our own thread pool/process pool to trade space for time. But starting from Python 3.2, the standard library provides us with the concurrent.futures module, which provides two classes, ThreadPoolExecutor and ProcessPoolExecutor, to implement thr..
##4. Detailed introduction to thread pool/process pool of Python concurrent programming
## Introduction: Introduction: The Python standard library is We provide threading and multiprocessing modules to write corresponding multi-thread/multi-process code. However, when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-consuming. At this time, we have to write our own thread pool/process. Pool, trading space for time. But starting from Python 3.2, the standard library provides us with the concurrent.futures module, which provides two classes: ThreadPoolExecutor and ProcessPoolExecutor, which implements thr..
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.NET Programming Thread Pool Insider#Introduction: Thread pool, as the name suggests, is a thread object pool. Both Task and TPL use thread pools, so understanding the inside story of thread pools can help you write better programs. Due to limited space, here I will only explain the following core
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