Memory Analyzer may read memory-related information from IBM system dumps and from Portable Heap Dump (PHD) files with the IBM DTFJ feature installed. Once installed, then File > Open Heap Dump should give the following options for the file types:
For a comparison of dump types, see Debugging from dumps. System dumps are simply operating system core dumps; therefore, they are a superset of portable heap dumps. System dumps are far superior than PHDs, particularly for more accurate GC roots, thread-based analysis, and unlike PHDs, system dumps contain memory contents like HPROFs. Older versions of IBM Java (e.g. < 5.0SR12, < 6.0SR9) require running jextract on the operating system core dump which produced a zip file that contained the core dump, XML or SDFF file, and shared libraries. The IBM DTFJ feature still supports reading these jextracted zips; however, newer versions of IBM Java do not require jextract for use in MAT since DTFJ is able to directly read each supported operating system's core dump format. Simply ensure that the operating system core dump file ends with the .dmp suffix for visibility in the MAT Open Heap Dump selection. It is also common to zip core dumps because they are so large and compress very well. If a core dump is compressed with .zip, the IBM DTFJ feature in MAT is able to decompress the ZIP file and read the core from inside (just like a jextracted zip). The only significant downsides to system dumps over PHDs is that they are much larger, they usually take longer to produce, they may be useless if they are manually taken in the middle of an exclusive event that manipulates the underlying Java heap such as a garbage collection, and they sometimes require operating system configuration (Linux, AIX) to ensure non-truncation.
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The Eclipse Memory Analyser Tooling (MAT) is a set of plug-ins for the Eclipse IDE which provides tools to analyze heap dumps from Java application and to identify memory problems in the application.This helps the developer to find memory leaks and high memory consumption issues.
It is possible to instruct the JVM to create automatically a heap dump in case that it runs out of memory, i.e. in case of a OutOfMemoryError error.To instruct the JVM to create a heap dump in such a situation, start your Java application with the -XX:+HeapDumpOnOutOfMemoryError option.
The Eclipse Memory Analyzer is a fast and feature-rich Java heap analyzer that helps you find memory leaks and reduce memory consumption. Use the Memory Analyzer to analyze productive heap dumps with hundreds of millions of objects, quickly calculate the retained sizes of objects, see who is preventing the Garbage Collector from collecting objects, run a report to automatically extract leak suspects.
Do you mind cd'*** to the directory that TMP is defined as and see if there is a directory named hsperfdata_ where is your login. That is the directory where the instrumentation buffers are mapped (as shared memory files). Each time a java process starts it should create a file in that directory.
So what I understand from this is that Java was supposed to write a file to the %TMP%\hsperfdata_ folder. The file helped memory analysers detect Java processes. Lack of appropriate permissions meant that the file couldn't be written and the memory analysers couldn't detect the Java processes.
For me, I find MAT turns errororg.eclipse.mat.SnapshotException: Error getting Java processes list with 'jps'. Try to configure a JDK for the HPROF jmap provider in path MemoryAnalyzer-1.10.0.20200225-win32.win32.x86_64\mat\workspace\.metadata\.log
Check jps: open win cmd and type jps return jps not exist.
Configure the path of jps to the environment.
Analyzing and understanding the memory use of an application is challenging. A subtle logic error can result in listeners never being disposed, ultimately leading to the dreaded OutOfMemory error. Even if your application is properly disposing of all unused objects, it may still be requiring 10 or 100 times more memory than necessary.
The pie chart in the middle shows you the biggest objects by retained size. That means if we could dispose a particular instance of java.lang.Thread we would save 11.2Mb, and over 90% of the memory used in this application. While that might look interesting, java.lang.Thread is unlikely the real problem here. To get a better sense of what objects currently exist, you can use the Histogram.
The histogram shows the number of instances of a particular class and how much memory each one uses. Of course, char[], String and Object[] are unlikely the problem. To help better organize this view, you can group by classloader or package. This will allow you to focus on your Objects.
The key to understanding your retained heap, is looking at the dominator tree. The dominator tree is a tree produced by the complex object graph in your system. The dominator tree allows you to identify the largest memory graphs. An Object X is said to dominate an Object Y if every path from the Root to Y must pass through X. Looking at the dominator tree for our example, we can start to see where the bulk of our memory is leaking.
The Inspector provides detailed information about the currently selected Class or Object. In this example we can see that the currently selected ArrayList contains 100,000 elements and references an object array at memory location 0x7f354ea68.
The MAT provides reports for common memory use anti-patterns. These can be used to get an idea of where memory leaks are occurring, or by looking for some low hanging fruit which can be cleaned up to help improve performance.
The Eclipse Memory Analyzer is a powerful tool, one all Java Developers should be familiar with. Tracking memory leaks and other memory related problems is often challenging, but hopefully with the MAT you can get to the root of your problems relatively quickly.
To Do List -> More advanced topics on Java and memory allocation as this can be explained in greater detail to help confirm troubleshooting/reviews for possible/probable causes of crashes/unstable memory handling and what can be done to correct the crash.
Most developers working with Java hardly have to think about the memory footprint of their application that they wrote. The garbage collector inside the JVM will remove most waste, but what happens when not all waste can be removed or something is wrong inside the application? This may result in an exception that probably a lot of developers and system administrators have seen before: java.lang.OutOfMemoryError (OOME).There are several causes for such an exception, but the most obvious is that there is memory leak somewhere in the application.
Most of my clients run on the Sun(Oracle) JVM, so I will try to keep this post focussed on the instructions for the Sun JVM. In case your application server runs out of memory you can instruct the JVM to generate a heap dump when an OOME occurs. This heap dump will be generated in the HPROF binary format.
Now you have the heap dump and want to figure out what was inside the heap at the moment the OOME occurred. There are several Java heap dump analyzers out there, where most of them can do more then just heap analysis. The products range from commercial to open source and these are the ones that I tried with my 4Gb .hprof file:
I was surprised to see that most of the above applications were unable to handle a file of this size. Eclipse Memory Analyzer was actually the only heap dump analyzer that was able to handle a heap dump of this size on my MacBookPro. All the other analyzers were unable to handle a file of this size. Apparently some of these tools tried to load the entire file into memory. On a laptop with only 4 Gb this will not fit. Eclipse MAT was able to analyze this file within 5-10 minutes.
You may need to take the Heap dump if your Java application is taking up more memory than you expected or your Java application crashed with OutOfMemoryError. Analyzing the heap dump will lead us to the root cause of the anomaly.
Using the heap dump we can find details like the memory usage per class, number of objects per class, etc. We can also go into fine details and find out the amount of memory retained by a single Java object in the application. These details can help us pinpoint the actual code that is causing the memory leak issues.
We will be analyzing the heap dump generated by this Java application. The memory leak in the application is discussed in depth in this tutorial. And the screenshots posted below are from the MAT plugin used with Eclipse IDE.
Histogram lists all the different classes loaded in your Java Application at the time of heap dump. It also lists the number of objects per class along with the shallow and retained heap size. Using the histogram, it is hard to identify which object is taking the most memory. However, we can easily identify which class type holds the largest amount of memory. For instance, in the screenshot below byte array holds the largest amount of memory. But, we cannot identify which object actually holds that byte array.
Shallow Heap is the size of the object itself. For instance, in the screenshot below byte array itself holds the largest amount of memory. Retained Heap is the size of the object itself as well as the size of all the objects retained in it. For instance, in the screenshot below the DogShelter object itself holds a size of 16 bytes. However, it has a retained heap size of more than 305Mb which means it likely holds the byte array which contributes to the very large retained heap size.
The dominator tree of the Java objects allows you to easily identify object holding the largest chunk of memory. For instance, we can see from the snipped below that the Main Thread object holds the largest memory. On collapsing the main thread tree we can see that the instance of class DogShelter holds a hashmap holding over 300Mb of memory. 2351a5e196
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