How to Diagnose Memory Leaks
Performance of your Java application is dependent on the stability of your memory, so click more to learn more about keeping your memory secure.
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Memory leaks don’t have to be a hard/scary/tedious problem to solve if we can follow below mentioned 3 simple steps:
Step 1: Capture Baseline Heap Dump
jmap-dump:format=b,file=<file-path><pid> where pid: is the Java Process Id, whose heap dump should be captured file-path: is the file path where heap dump will be written in to.
If you don’t want to use jmap for capturing heap dumps, here are several other options to capture heap dumps.
It’s always better to capture heap dump in the production environment (unless in the test environment, you can mirror the exact production traffic pattern). Traffic type and its volume play a primary role in the type and number of objects created in the memory.
Step 2: Capture Troubled Heap Dump
After doing step #1, let the application run. Before the application crashes, take another heap dump once again. Often times, it might be challenging to capture heap dumps before it crashes because we don’t know when the application will crash. Is it after 30 minutes, 3 hours, 3 days? Thus, it’s ideal to start your application with the following JVM property:
-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=<file-path> file-path: is the file path where heap dump will be written in to.
This property will trigger heap dump right when the application experiences OutOfMemoryError.
Step 3: Compare Heap Dumps
Objects which are causing memory leaks grow over the period. If you can the identify objects whose size has grown between the heap dumps captured in step #1 and step #2, then those are the objects which are causing memory leak.
Fig 1: Largest Objects reported by HeapHero.io
Fig 2: Object Tree showing children, grandchildren, great-grandchildren
You can consider using heap dump analyzer tool such as HeapHero.io for this purpose. When you load the heap dumps into HeapHero.io, it provides rich information about your application’s memory. There is a “Large Objects” section (shown in Fig 1), which reports largest objects that are sitting in the memory. Compare this section between heap dumps captured in step #1 and step #2. If you notice any abnormal growth of objects, then they are the ones which are causing memory leak in your application. You can also click on any of the largest objects to see the children, grandchildren, great-grandchildren objects present in it. Screen shot of this section is shown in Fig #2.
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