Race conditions and visibility in Java are critical concepts in multithreading. Understanding when to prefer or avoid them can significantly impact the performance and correctness of your application.
Race conditions occur when two or more threads access shared data and try to change it at the same time. This can lead to unpredictable behavior and bugs that are difficult to trace. Here are some scenarios where you should avoid race conditions:
In some cases, you may prefer to accept race conditions for the sake of performance. These situations typically involve:
Using synchronized blocks can help manage race conditions and ensure data visibility:
synchronized (lock) {
// critical section
sharedVariable++;
}
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?