Why are so many thread blocked on a very low level synchronized code block?

Hello WillWan,

When multiple threads are blocked on a very low-level synchronized code block, it typically indicates contention for a shared resource protected by that synchronization mechanism. In Java, the synchronized keyword is used to create a critical section, ensuring that only one thread can execute that code block at a time. While this mechanism is essential for maintaining data consistency and preventing race conditions, it can also lead to performance issues if not used carefully.

Here are a few reasons why threads might be blocked on a synchronized code block:

1. Contention: If multiple threads are trying to access the synchronized block simultaneously, only one thread can enter the block at a time, and others are forced to wait. This can lead to a bottleneck if the code block takes a long time to execute or if there are frequent requests to access it.

2. Long-running operations: If the synchronized block contains operations that are computationally expensive or involve I/O operations (e.g., file or network access), it can cause other threads to wait for an extended period, slowing down the overall application.

3. Lock granularity: If the granularity of the synchronization is too coarse, it can lead to unnecessary contention. For example, if a large method is synchronized, even though only a small part of it needs synchronization, it will result in more blocked threads.

4. Nested synchronization: Nested synchronization can lead to lock contention. If a thread already holds a lock and attempts to acquire another one while holding the first, it will cause a deadlock situation.

Increasing heap memory is unlikely to solve the problem of blocked threads on a synchronized code block. Heap memory is primarily used for storing objects and data dynamically during the application's runtime. The issue of blocked threads is related to thread synchronization and contention for shared resources, which are typically not directly influenced by heap memory size.

To address the problem of blocked threads, you should focus on improving the design and implementation of your code:

1. Optimize the critical section: Review the synchronized code block and try to make it as short and efficient as possible. Minimize the time spent inside the synchronized block to reduce contention.

2. Fine-grained locking: Consider using smaller, more focused synchronized blocks instead of locking entire methods or large sections. This can reduce contention by allowing multiple threads to execute non-overlapping code concurrently.

3. Use concurrent data structures: Java provides various concurrent data structures, such as ConcurrentHashMap, that are optimized for multi-threaded access and can reduce contention.

4. Avoid unnecessary synchronization: Not all data accesses need to be synchronized. Analyze which data truly requires synchronization and which can be accessed safely without it.

5. Thread pooling: Implement thread pooling to limit the number of active threads and manage their execution, which can help avoid overloading the system with too many concurrent threads.

Remember that solving thread contention issues can be complex and may require profiling, performance monitoring, and careful analysis of your specific application's behavior. The easiest way to identify the bottlenecks and areas of contention in your code. Just capture the thread dump of your application and upload it to our tool FastThread.io.