How [JVM] manages memory

JVM memory management model

The following is a detailed diagram of JVM memory management:

+------------------------------------------------------+
|                        Java 运行时数据区                             |
+------------------------------------------------------+
|                                                       |
|                       程序计数器                                    |
|                                                       |
+------------------------------------------------------+
|                                                       |
|                         虚拟机栈                                       |
|                                                       |
+------------------------------------------------------+
|                                                       |
|                         本地方法栈                                     |
|                                                       |
+------------------------------------------------------+
|                                                       |
|                            堆                                             |
|                                                       |
+------------------------------------------------------+
|                                                       |
|                         方法区                                         |
|                                                       |
+-------------------+---------------------+--------------+
|                   |                     |              |
|    运行时常量池      |     静态变量域       |   类结构信息  |
|                   |                     |              |
+-------------------+---------------------+--------------+
|                                                       |
|                      直接内存                                      |
|                                                       |
+------------------------------------------------------+

• Program Counter: Each thread has a program counter that indicates the address of the currently executed bytecode instruction or the address of the next instruction to be executed.

• Virtual Machine Stack: Each thread is allocated a virtual machine stack when it is created, which is used to store data such as local variables, operand stacks, and return values ​​during method calls. As methods are called and returned, stack frames are pushed and popped dynamically.

• Native Method Stack: Similar to the virtual machine stack, but it serves native methods.

• Heap: It is the largest memory area of ​​a Java program and is used to store object instances and arrays. The heap is divided into the young generation and the old generation to support the garbage collection mechanism.

  • New generation: includes one Eden space and two Survivor spaces. Newly created objects are first allocated to the Eden space. When the Eden space is full, some surviving objects will be transferred to the Survivor space. Objects that are still alive after multiple garbage collections will be promoted to the old generation.

  • Old generation: used to store long-lived objects. When objects survive multiple garbage collections and cannot be allocated space in the young generation, they are promoted to the old generation.

• Method Area: Stores class structure information, static variables, constant pool and other data. The method area also contains the runtime constant pool, which is the in-memory representation of the constant table in the Class file.

• Direct Memory: It is not part of the JVM runtime data area, but is used by the NIO library to allocate memory when performing I/O operations. Direct memory is managed through the ByteBuffer class.

These memory areas together form the runtime data area of ​​the JVM. By properly configuring and optimizing memory parameters, we can improve the performance and scalability of the application. .

The JVM uses an automatic garbage collector to reclaim and organize memory for objects in the heap. The garbage collector marks and clears objects that are no longer referenced, and moves or organizes surviving objects to optimize memory space utilization. In this way, developers do not need to manually release memory that is no longer used, thereby improving development efficiency and application robustness.

By properly configuring and optimizing the memory parameters of the JVM, such as heap size, ratio of new generation to old generation, garbage collection algorithm, etc., the performance and scalability of the application can be improved.

JVM memory management example analysis

Below is a sample code showing how the JVM manages memory:

public class MemoryManagementExample {
    
    
    public static void main(String[] args) {
    
    
        // 创建一个对象
        MyClass myObj = new MyClass();
        
        // 访问对象的实例变量
        myObj.setValue(42);
        System.out.println(myObj.getValue());
        
        // 引用置为null，释放对象
        myObj = null;
    }
}

class MyClass {
    
    
    private int value;

    public void setValue(int value) {
    
    
        this.value = value;
    }

    public int getValue() {
    
    
        return value;
    }
}

In this example, we create an MyClassobject of class myObj. The object has an instance variable valueand corresponding access method.

When executing new MyClass(), the JVM allocates a space in the heap memory to store MyClassthe object's instance variables. This object is called a heap object.

When a method myObjis called on an object setValue(42), the JVM will store the value 42 in myObjthe instance variable of the referenced heap object value.

Through getValue()the method, we can access the value of myObjthe object's instance variable valueand print it out.

Finally, the myObjreference is set to null, which means the object is no longer referenced. When there are no other references pointing to the object, the JVM's garbage collector will recognize that the object has become garbage, then automatically reclaim it and release the occupied heap memory space.

This example shows how the JVM manages memory through automatic garbage collection. Developers do not need to manually release the object, but by letting the object lose its reference, and then the garbage collector is responsible for reclaiming and releasing the memory. This approach reduces the burden on developers and ensures efficient memory utilization.

Common optimization methods for jvm

When optimizing JVM memory management, there are many aspects to consider. The following is a detailed explanation of some JVM memory management optimization techniques:

1. Heap sizing : Heap size has a significant impact on application performance and garbage collection behavior. If the heap is too small, garbage collection will occur frequently, resulting in longer application pause times; if the heap is too large, precious memory resources will be wasted. By adjusting -Xmsthe (initial heap size) and -Xmx(maximum heap size) parameters, you can optimize the heap size to suit your application's needs.

2. Adjustment of the ratio between the new generation and the old generation : The new generation mainly stores newly created objects, while the old generation stores long-lived objects. Properly allocating the space ratio between the new generation and the old generation can reduce the number of garbage collections and improve performance. Use -XX:NewRatioparameters to specify the ratio of the new generation to the old generation. The default value is 2, which means the new generation accounts for 1/3 of the entire heap.

3. Garbage collection algorithm selection : JVM provides different garbage collection algorithms to choose from. Common algorithms include mark-clear, copy, mark-organize, etc. Various algorithms perform differently in different scenarios, so choosing the appropriate garbage collector and algorithm based on the characteristics of the application can significantly improve performance. For example, using the CMS (Concurrent Mark Sweep) garbage collector can reduce pause times and is suitable for applications with high low latency requirements; while the G1 (Garbage First) garbage collector is suitable for large heaps, multi-core processors and low pause times. application.

4. Garbage collector parameter tuning : The JVM provides a series of parameters to adjust the behavior of the garbage collector. By adjusting these parameters, you can control aspects such as garbage collection pause time, throughput, and memory usage. For example, -XX:MaxGCPauseMillisyou can control the maximum pause time of garbage collection by adjusting parameters, and -XX:ParallelGCThreadsspecify the number of threads for parallel garbage collection by adjusting parameters.

5. Object life cycle management : Properly designing and using objects, and promptly releasing references to objects that are no longer used, are the keys to avoiding memory leaks and reducing garbage collection overhead. It is important to note that holding a reference to an object for a long time can cause a memory leak, so the object's life cycle should be carefully managed and references manually released when no longer needed.

6. Parallelism and Concurrent Processing : Leverage multi-threading and parallel processing to speed up the garbage collection process. The JVM's garbage collector can usually improve the efficiency of garbage collection through parallel processing. By adjusting related parameters, for example -XX:ParallelGCThreads, you can specify the number of threads for parallel garbage collection.

7. Memory allocation optimization : Short-lived objects that are frequently created and destroyed will increase the overhead of memory allocation and garbage collection. In order to reduce this overhead, you can use object pools or reuse objects to avoid frequent creation and destruction of objects.

8. Disable unnecessary features : Disabling unnecessary JVM features and debugging options can reduce additional overhead and memory usage. For example, disable assertions, turn off debugging information output, etc.

The above are some common JVM memory management optimization techniques. Depending on the specific application requirements and environment characteristics, it may be necessary to perform tuning and testing based on actual conditions to achieve optimal performance and resource utilization.