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Table of contents
In some configurations for session persistence or replication, sessions are periodically persisted or replicated on a WebSphere background thread. Although such threads are not application threads, WebSphere is simply serializing or replicating application sessions, so the underlying issue is still most likely proximately related to application data rather than WebSphere.
Review the resulting heapdump produced by the OOM to understand which application is driving it and which particular session keys and values:.
The first thread is usually the one that caused the OOM. Review the "Retained Heap" column to understand how much memory each thread is retaining. If there is a single large session, then the first thread will likely be much larger than the others. If many large sessions across threads contributed to the OOM, then you will probably see many pretty large retained heap sizes. Expand the large retained heap size rows and explore the stack frame locals on the thread.
In particular, find frames such as "com. Note that the "Retained Heap" column of sessions or their values may not be very meaningful because they have inbound references from the ObjectOutputStream. Application code analysis is sometimes required.
The top two stack frames are often in java. It will work with all dump types, including PHDs. If a dump is gathered manually outside of OOM conditions, if there is no session persistence or replication at the time of the dump, then the retained sizes of sessions will be more meaningful and the distribution of session sizes may be analyzed. In the above example, the reason why WebSphere was serializing this session into more than MB is that the session included an application object which had a value that had an instance field reference to its org. Serializing the actual servlet object will serialize a very large object graph.
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