Heap Dump Analysis

1. What is a Heap Dump?

A heap dump is a snapshot of the Java Virtual Machine (JVM) heap memory at a specific point in time. It contains comprehensive information about the objects that are currently in memory, including their types, sizes, and references between them.

2. Taking a Heap Dump

Heap dumps can be captured using various methods, including tools provided by the JDK, external tools, and programmatic approaches.

Using JVisualVM

1. Start JVisualVM: This tool is included with the JDK.
2. Attach to the Application: Select the Java application process.
3. Capture Heap Dump: Click on "Heap Dump" to create the dump.

Using jmap Command

jmap -dump:live,format=b,file=heapdump.hprof <pid>        

Replace <pid> with the process ID of the Java application.

Programmatically

Heap dumps can be triggered programmatically:

import com.sun.management.HotSpotDiagnosticMXBean;
import java.lang.management.ManagementFactory;

public class HeapDump {
    public static void dumpHeap(String filePath, boolean live) throws Exception {
        HotSpotDiagnosticMXBean mxBean = ManagementFactory.getPlatformMXBean(HotSpotDiagnosticMXBean.class);
        mxBean.dumpHeap(filePath, live);
    }

    public static void main(String[] args) throws Exception {
        dumpHeap("heapdump.hprof", true);
    }
}
        

3. Analyzing Heap Dumps

Using Eclipse Memory Analyzer Tool (MAT)

Eclipse MAT is a robust tool for heap dump analysis. It offers features to identify memory leaks, locate large objects, and understand the heap structure.

Sections in MAT:

• Overview: Summarizes the heap dump, providing total heap size, object count, and garbage collection roots.
• Histogram: Displays the number of instances and memory consumption by class.
• Dominator Tree: Highlights the largest retainers in memory.
• Top Consumers: Identifies objects consuming the most memory.
• Leak Suspects: Generates a report with potential memory leaks.

4. Key Concepts in Heap Dump Analysis

Shallow Heap

The shallow heap of an object is the amount of memory allocated to store the object itself, not including any objects it references. This is essentially the direct memory footprint of the object.

Example:

• An object of class Person might have the following fields: int id, String name, int age.
• The shallow heap size includes the memory used by the Person object and its fields (int fields, which are primitive types, and the reference to the String object).

Calculation:

• For a 32-bit JVM, an int typically takes 4 bytes.
• A reference typically takes 4 bytes.
• Assuming 8-byte alignment, the shallow heap for a Person object could be 16 bytes (object header) + 4 bytes (int id) + 4 bytes (reference to String name) + 4 bytes (int age) = 28 bytes, rounded up to the nearest multiple of 8, so 32 bytes.

Retained Heap

The retained heap of an object is the total amount of memory that would be freed if the object were garbage collected, including the memory used by all objects it directly or indirectly references.

Example:

• Continuing with the Person example, if the Person object references a String object, the retained heap includes the memory of the Person object, the String object, and any other objects referenced by the String (e.g., a char[] array).

Importance:

• Identifying objects with large retained heaps helps pinpoint memory hogs that, if garbage collected, would free significant memory.

5. Java JVM Heap

The JVM heap is divided into several areas, each with a specific purpose in memory management:

• Young Generation: The Young Generation is the area of the heap where all new objects are allocated and aged. It is further divided into: Eden Space: Where new objects are initially allocated. Survivor Spaces (S0 and S1): After surviving a garbage collection, objects are moved from Eden to one of the survivor spaces. Objects that survive multiple garbage collections are eventually promoted to the Old Generation. Purpose: Efficiently manage short-lived objects and reduce the frequency of full garbage collections.
• Old Generation: The Old Generation, also known as the Tenured Generation, is where objects that have survived several garbage collection cycles are promoted. This area holds long-lived objects. Purpose: Manage long-lived objects that need to stay in memory for a longer duration. Garbage collection in this space is less frequent but takes longer compared to the Young Generation.
• Permanent Generation (PermGen) / Metaspace: In Java 8 and earlier, the Permanent Generation (PermGen) stores metadata such as class definitions and method objects. Starting from Java 8, this has been replaced by Metaspace. PermGen: Limited in size and can lead to OutOfMemoryError if it runs out of space. Metaspace: Dynamically resizes based on the application's needs and is allocated from native memory rather than the heap. Purpose: Store class-related metadata, method definitions, and interned strings.

6. Identifying Issues and Resolutions

Memory Leak

Symptom: Continuous increase in heap usage over time, eventually leading to an OutOfMemoryError.

Detection:

1. Leak Suspects Report: Use Eclipse MAT's Leak Suspects report to identify potential memory leaks. This report highlights objects with unexpectedly high retained heap sizes.
2. Histogram Analysis: Check for classes with an unusually high number of instances or excessive memory consumption. Look for objects that should have been garbage collected but are still retained.
3. Dominator Tree: Identify large objects or groups of objects that are preventing memory from being reclaimed.

Resolution:

1. Identify Root Cause: Find the root cause of the memory leak by examining references to the leaked objects. Common causes include unintentional static references, collections that grow indefinitely, or improper handling of listeners and caches.
2. Fix Code: Modify the code to remove unnecessary references, ensuring objects are eligible for garbage collection. For instance, clear collections, remove listeners, or use weak references where appropriate.

Large Object Retention

Symptom: Large objects or arrays occupy significant heap space, potentially leading to inefficient memory usage.

Detection:

1. Histogram and Dominator Tree: Use the Histogram to find classes with large objects. The Dominator Tree can help identify objects with large retained heaps, highlighting which objects, if removed, would free the most memory.
2. Top Consumers: Identify objects that are consuming the most memory and investigate why they are so large.

Resolution:

1. Optimize Data Structures: Consider using more memory-efficient data structures or algorithms. For example, replace large arrays with more compact representations or use collections with better memory characteristics.
2. Reduce Object Size: Minimize the memory footprint of objects by eliminating unnecessary fields, using primitive types instead of their wrapper classes, or employing more efficient serialization techniques.

Large Object Retention

Symptom: Large objects or arrays occupy significant heap space, potentially leading to inefficient memory usage.

Detection:

1. Histogram and Dominator Tree: Use the Histogram to find classes with large objects. The Dominator Tree can help identify objects with large retained heaps, highlighting which objects, if removed, would free the most memory.
2. Top Consumers: Identify objects that are consuming the most memory and investigate why they are so large.

Resolution:

1. Optimize Data Structures: Consider using more memory-efficient data structures or algorithms. For example, replace large arrays with more compact representations or use collections with better memory characteristics.
2. Reduce Object Size: Minimize the memory footprint of objects by eliminating unnecessary fields, using primitive types instead of their wrapper classes, or employing more efficient serialization techniques.

Unnecessary Object Retention

Symptom: Objects that should have been garbage collected are still present in the heap, indicating they are being retained unnecessarily.

Detection:

1. Reference Analysis: Use MAT to analyze references to objects that are unexpectedly retained. Determine why these objects are still reachable from the garbage collection roots.
2. Paths to GC Roots: Examine the paths from objects to GC roots to understand the chain of references keeping them alive.

Resolution:

1. Fix Code: Ensure proper dereferencing of objects when they are no longer needed. For example, set object references to null, clear collections, or remove event listeners.
2. Use Weak References: In cases where objects should not prevent garbage collection but still need to be referenced (e.g., caching), use weak references. This allows the garbage collector to reclaim these objects when memory is needed.

7. Heap Content

The heap typically contains:

• Java Objects: Instances of classes created by the application.
• Class Objects: Representations of loaded classes.
• Array Objects: Arrays created in the application.
• Garbage Collection Roots: References from JVM internals, local variables, etc.

8. System Settings for Large Heap Files

To analyze large heap files, you may need to adjust the JVM settings for MAT:

• Increase MAT's Memory Allocation: Edit?MemoryAnalyzer.ini?(or similar) to increase the maximum heap size allocated to MAT.

-vmargs
-Xmx4g
-XX:+UseG1GC        

• Use a 64-bit JVM: Ensure that MAT is running on a 64-bit JVM to handle larger heap sizes.

Example of Heap Dump Analysis:

After generating a heap dump, load it into MAT:

1. Open the Dump: Open the .hprof file in MAT.
2. Run Leak Suspects Report: Start by running the Leak Suspects report to get an overview of potential issues.
3. Analyze Histogram: Check the histogram for classes with a large number of instances or large memory consumption.
4. Examine Dominator Tree: Look for objects with large retained heaps to find memory hogs.
5. Inspect Paths to GC Roots: Analyze paths from objects to GC roots to understand why they are retained.

Conclusion

Heap dump analysis is a powerful technique for diagnosing memory issues in Java applications. By using tools like MAT and understanding key concepts such as shallow and retained heap, developers can effectively identify and resolve memory-related problems. Properly generating and analyzing heap dumps helps ensure efficient memory usage and application stability.