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Java Dumps Uncovered: When to Use Thread Dump, Heap Dump, or Core Dump

Choosing the Right Dump for the Right Problem:

Knowing which dump to use in a given situation provides a significant advantage while debugging. In this blog, we’ll explore the differences between Thread Dump, Heap Dump, and Core Dump, how to capture them, and when to use them effectively.

Understanding Java Threads and Memory:

When a simple Java class with a main method runs, it creates a single thread named "main", which executes the program. In many cases, this single thread is sufficient. However, for applications handling multiple tasks simultaneously, multiple threads are necessary.

For example, a web server like Tomcat would be ineffective if it handled all requests using a single thread. Instead, it creates multiple threads to manage concurrent requests. Alongside threads, Java runtime also requires memory to execute programs, which includes components like the Method Area, Heap, Stack, etc.

When to Take a Thread Dump?

Imagine running a Tomcat server, and a specific request takes an unusually long time without responding. In such cases, a thread dump helps determine whether the threads are still running or stuck.

Thread dumps are useful for diagnosing:
* Thread Deadlocks – When multiple threads block each other.
* High CPU Usage – To identify threads consuming excessive processing power.
* Application Freezes or Performance Issues – When an app becomes unresponsive.
* Thread Pool Exhaustion – When all threads are in use, preventing new tasks from executing.

To confirm if a thread is stuck, capturing multiple thread dumps at short intervals helps. If a particular thread remains in the same state across all dumps, it is likely stuck.

Example:
A request to an external service without a proper timeout may cause the thread to remain in a waiting state. If the request takes 5 minutes, any thread dump taken within that time will show the thread stuck at the response waiting step. In such cases, reviewing the application’s timeout settings is necessary, along with checking if other threads are stuck.

When to Take a Heap Dump?

Heap dumps should be captured under specific conditions to diagnose memory-related issues effectively. Here are some key scenarios, but not limited to, when you should take a heap dump:

* Memory Leaks – When objects are not being garbage collected.
* Excessive Memory Usage – To analyze which objects consume the most memory.
* Frequent Garbage Collection Pauses – Causing slow performance.

Example : If your Tomcat server experiences delays and thread dumps show that threads are not stuck, but frequent GC (Garbage Collection) pauses occur, or an Out of Memory (OOM) error appears, a heap dump is required.

Capturing a heap dump allows developers to analyze memory usage and pinpoint issues leading to memory exhaustion.

When to Take a Core Dump?

A core dump is useful when an application crashes unexpectedly, and logs do not provide enough details. For example, if Tomcat crashes before it even initializes logging, no logs will be available to debug the issue. In such cases, a core dump helps determine the exact cause of the crash.

Core dumps are essential for diagnosing:
* Low-Level Errors – Segmentation faults, memory corruption, etc.
* JVM Crashes – Especially due to native code or internal JVM failures.
* Deadlocks and Memory Corruption – When issues involve native memory management.

Thread Dump vs. Heap Dump vs. Core Dump

  • Thread dumps and heap dumps are ideal for Java-level issues like deadlocks, memory leaks, and performance bottlenecks, without requiring a crash.
  • Core dumps are more suited for JVM crashes, segmentation faults, and memory corruption—typically in cases involving native code or mixed-language applications.

Conclusion

Using the right dump at the right time can significantly speed up debugging and troubleshooting. Thread dumps help diagnose slow or stuck threads, heap dumps assist in analyzing memory-related issues, and core dumps are invaluable when dealing with crashes and low-level failures. Understanding their differences ensures a more efficient debugging process and a better grasp of application performance.


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