If there is data cache, how can you determine that the cause of OOM is specifically due to it?

To understand whether the Out Of Memory (OOM) issue is specifically caused by the data cache, several diagnostic steps should be taken:

1. Memory Monitoring: Use memory profilers (e.g., VisualVM, YourKit, JProfiler) to analyze heap dumps. If most of the memory is occupied by cache-related objects, this is a clear sign.

2. Heap dump: Take a memory dump when approaching OOM and analyze which objects occupy the most space. If these are cache objects, then the cache is likely the culprit.

3. Logging and metrics: If the cache has counters or metrics (e.g., number of elements, size), compare them with peak memory values.

4. Temporary cache disablement: If possible, temporarily disable the cache or reduce its size and see if the OOM problem disappears.

5. Check cache eviction policy: Ensure that the cache is properly cleared (e.g., LRU, TTL). If the cache grows without limits, it can lead to OOM.

Example of using VisualVM to analyze heap dump:

// Launch the application with parameters to collect heap dump
// Open the heap dump in VisualVM and observe memory distribution by classes
// If the CacheEntry class or similar occupies most of the memory — the problem is in the cache

Thus, combining profiling, heap dump analysis, and cache logic checks will help accurately identify the cause of OOM.