Common JVM interview questions

1. What is JVM?

JVM (Java Virtual Machine) is the abbreviation of Java Virtual Machine, which is the core and key of Java language. JVM is a virtual computer capable of executing Java bytecode. It simulates a complete computer system on an actual computer, including processors, memory, registers, etc. When a Java program is running, the Java compiler compiles the Java code into bytecodes, and the JVM interprets and executes these bytecodes or compiles them, and is responsible for managing the memory, threads, and garbage collection of the program.

Since the JVM provides cross-platform capabilities, programs written in the Java language can run on different operating systems without modifying any code. At the same time, the existence of the JVM also makes the Java language have good portability and security, and it is widely used in enterprise-level applications, Internet applications, mobile phone applications and other fields.

2. What are the components of the JVM?

JVM (Java Virtual Machine) mainly consists of the following parts:

1. Class Loader (ClassLoader): Responsible for loading Java class files from the file system or network, converting them into Class objects and storing them in the JVM.

2. Runtime Data Area: The memory space of the JVM, which is used to store data and information when the program is running. Including method area, heap, virtual machine stack, local method stack and other parts.

3. Execution Engine: Responsible for executing bytecode instructions, translating bytecode into machine code and executing it at runtime.

4. Garbage Collector: The JVM is responsible for automatically managing memory, scanning the reference relationship of objects through the garbage collector, finding objects that are no longer used and releasing their memory space.

5. Native Interface: Allows Java code to interact with libraries written in native languages.

6. Class Library: It is the implementation of the Java standard library, which provides a large number of commonly used classes and methods, and provides convenience for developers.

These components together constitute the JVM, which makes the Java program have cross-platform capabilities, and can automatically manage memory to ensure the stability and security of the program.

3. What is the memory structure of the JVM?

The memory structure of JVM (Java Virtual Machine) mainly consists of the following parts:

1. Program Counter Register: Each thread has a program counter, which is used to record the address of the bytecode instruction executed by the current thread. When a thread switches, the program counter is saved in thread-private memory.

2. Virtual Machine Stacks (Java Virtual Machine Stacks): Each method will create a stack frame (Stack Frame) when it is executed, which is used to store information such as local variables, operand stacks, dynamic links, and method exits. Each thread has its own virtual machine stack, which is created when the thread starts and destroyed when the thread ends.

3. Native Method Stack: Similar to the virtual machine stack, but used to execute native methods. It is also thread-private.

4. Heap: All objects are stored in the heap. The heap is the largest memory area in the JVM, shared by all threads. The size of the heap can be set via command line parameters.

5. Method Area: Used to store metadata of a class, such as class name, access modifier, field descriptor, method descriptor, constant pool, etc. The method area is also shared by all threads.

In addition to the above five parts, there are also parts such as direct memory (Direct Memory) and permanent generation (Perm Gen, which has been removed in JDK8). The specific implementation of the JVM memory structure may vary depending on the JVM vendor, virtual machine version, command line arguments, etc., but the basic principles are the same.

4. What is the running process of a Java program?

The running process of the Java program is as follows:

1. Writing Java code: Developers write programs in the Java language and save them as .java files.

2. Compile Java code: Use the javac tool in the JDK to compile Java code into bytecode files (.class files).

3. Class loading: The class loader of the JVM is responsible for loading bytecode files from the file system or network, converting them into Class objects and storing them in the method area.

4. Bytecode Verification: The JVM verifies the loaded bytecode to ensure it complies with the Java Virtual Machine Specification.

5. Interpretation and compilation: JVM interprets bytecode into machine code for execution, and also compiles hotspot code that has been detected by hotspots into local machine code for execution to improve performance.

6. Executing the program: When the JVM executes the program, it will execute the program one by one according to the bytecode instructions. The program counter records the address of the instruction executed by the current thread, and modifies the value of the program counter according to instructions such as jumps and loops.

7. Garbage collection: The JVM automatically recycles objects that are no longer referenced through the garbage collector to release memory space.

8. End of program: When the program is executed or an exception occurs, the JVM will output an error message and exit.

It should be noted that the running process of a Java program is managed and executed by the JVM, so the performance and stability of the program largely depends on the implementation of the JVM. Mechanisms such as JVM optimization and garbage collection also have an important impact on program performance.

5. What is the role of the class loader?

The class loader (ClassLoader) is an important part of the JVM. Its main function is to load Java class files from the file system, JAR package or network, convert them into Class objects and store them in the JVM. Class loaders are responsible for dynamically loading classes at runtime, providing a flexible mechanism to extend the Java platform.

The main functions of the class loader are as follows:

1. Loading class: When a program needs to use a certain class, the class loader will try to find and load the bytecode file of the class.

2. Isolated namespace: The classes loaded by different class loaders are independent of each other, and multiple classes with the same name but independent of each other can be created.

3. Security management: By customizing the class loader, the security control of the loaded class can be realized to prevent the execution of malicious code.

4. Dynamic proxy: Dynamic proxy technology requires the use of class loaders to dynamically generate proxy classes at runtime.

5. Modularity: Java 9 introduced a modular system where class loaders play an important role.

In short, as a basic component of the JVM, the class loader has an important impact on the stability and security of the Java runtime environment. In Java application development, the class loader is also one of the important design patterns, which can have a positive impact on the scalability and flexibility of the application.

6. What are the types of class loaders? What is the difference between each?

There are three main types of class loaders in Java:

1. Start class loader (Bootstrap ClassLoader): responsible for loading Java's core class library, such as rt.jar and so on. It is part of the implementation of the JVM and is not a normal Java class, so it cannot be referenced or accessed directly by Java code.

2. Extension ClassLoader: Responsible for loading JAR packages and class files in the JVM extension directory. By default, the extension directory is located under the $JAVA_HOME/lib/ext directory.

3. Application ClassLoader (Application ClassLoader): Also known as the system class loader, it is responsible for loading the class files under the class path specified in the application classpath. When you set the classpath with the -classpath or -cp parameter, you are actually specifying the classpath that the application classloader needs to load.

In addition to the above three types, there is also a custom class loader, that is, create your own class loader by inheriting the java.lang.ClassLoader class. Custom class loaders can flexibly adapt to various scenarios according to actual needs, such as hot deployment, dynamic proxy, etc.

These class loaders have different class loading orders and priorities, and each class loader has a namespace for the classes it loads, which are isolated from each other. When a class needs to be loaded, the JVM will try to use these class loaders in a specific order until it finds the required class.

In short, the class loader is an important part of the Java platform, responsible for loading classes and isolating namespaces, helping programs achieve better flexibility and scalability.

7. What is the principle of the garbage collection mechanism?

The principle of the garbage collection mechanism is to release memory resources and improve system performance by automatically detecting and recycling unused memory objects. Its basic principles include the following aspects:

1. Reference Counting (Reference Counting): This is a simple garbage collection technology. Each object maintains a reference counter that records the number of references pointing to the object. When the reference count is zero, that is, when there is no reference to the object, the object is judged as a garbage object and can be recycled.

2. Reachability Analysis: This is a more advanced garbage collection technique that determines whether an object is recyclable based on "reachability". Starting from the root object (such as global variables, active function call stacks, etc.), by traversing the reference relationship between objects, mark all reachable objects, and unmarked objects are considered garbage objects.

3. Garbage collection algorithm: According to the garbage objects obtained by the reachability analysis, the garbage collector executes a specific recovery algorithm to clean up the memory. Common algorithms include Mark and Sweep, Copying, Mark and Compact, etc. The goal of these algorithms is to efficiently reclaim garbage objects and organize the memory space to improve memory utilization.

4. Concurrency and pauses: Garbage collection can introduce system pauses, where program execution is suspended during garbage collection operations. In order to reduce the impact of this pause time on application performance, some garbage collectors use concurrent (Concurrent) or incremental (Incremental) methods for collection, allowing garbage collection and application execution at the same time.

Generally speaking, the principle of the garbage collection mechanism is to automatically manage memory resources, avoid memory leaks and improve system performance by detecting the reachability of objects and recycling them according to specific algorithms. Different languages ​​and garbage collectors have different implementations and strategies, but the core goal is the same.

8. What are the common garbage collection algorithms? What are their respective characteristics?

Common garbage collection algorithms are as follows:

1. Mark-Sweep algorithm (Mark-Sweep): Mark-Sweep algorithm is one of the earliest and most commonly used algorithms for garbage collection. It performs garbage collection by marking all live objects and then clearing all unmarked objects. The algorithm is simple to implement, but prone to memory fragmentation.

2. Copying algorithm (Copying): The copying algorithm divides the memory into two areas, and only uses one of the areas at a time. When the space in one area is used up, the surviving objects are copied to another area, and then the area is emptied. This avoids the problem of memory fragmentation, but requires additional memory space to hold unreclaimed objects.

3. Mark-compact algorithm (Mark-Compact): After marking all reachable objects, the mark-compact algorithm moves all surviving objects to one end, and then releases the memory space at the other end. This algorithm can avoid the problem of memory fragmentation, but it needs to move objects, which may affect performance.

4. Generational Collection Algorithm (Generational Collection): The generational collection algorithm divides different generations according to the life cycle of objects. Generally, the new generation and the old generation are processed separately, the new generation uses the copy algorithm, and the old generation uses the mark-sort algorithm or the mark-clear algorithm. This algorithm can more accurately recycle according to the life cycle of objects and improve the efficiency of garbage collection.

5. Concurrent Mark-Sweep: A concurrent mark-sweep algorithm is an algorithm that performs garbage collection while the application is running. The algorithm uses one thread for marking operations and another thread for cleaning operations while the application is running. This algorithm can reduce the pause time of the application program, but it consumes a lot of CPU resources.

In short, different garbage collection algorithms have their own advantages and disadvantages, and are suitable for different application scenarios. In actual application development, it is necessary to select an appropriate garbage collection algorithm and implementation method according to specific scenarios to achieve the best performance and stability.

9. How to judge whether an object can be recycled?

The garbage collection mechanism in Java is based on a reachability analysis algorithm to determine which objects can be recycled. According to the reachability analysis algorithm, if an object is no longer referenced or indirectly referenced by any object, the object can be recycled.

Specifically, the Java garbage collector starts traversing from a group of root objects called "GC Roots". If an object is not referenced by GC Roots, the object is judged as an unreachable object, that is, a garbage object. Then these garbage objects will be collected, and the memory they occupy will be freed.

GC Roots objects in Java include the following:

1. Objects referenced in the virtual machine stack (local variable table in the stack frame).

2. The object referenced by the class static property in the method area.

3. The object referenced by the constant in the method area.

4. The object referenced by JNI (Java Native Interface) in the native method stack.

To sum up, as long as an object cannot be referenced by GC Roots, it can be judged as a garbage object and wait to be reclaimed by the garbage collector. Therefore, when writing a program, you need to pay attention to avoid creating too many useless objects, so as to reduce the burden of garbage collection and improve the performance of the program.

10. What is a JIT compiler? What does it do?

A JIT (Just-In-Time) compiler is a compiler that converts source code or intermediate code (such as bytecode) into machine code at runtime. Different from the traditional static compiler, the JIT compiler delays the compilation process and performs dynamic compilation according to the actual execution of the program.

The main functions of the JIT compiler include:

1. Improve execution efficiency: By compiling code into machine code, the JIT compiler can optimize for a specific hardware platform and generate more efficient instruction sequences. Compared with the interpreted execution method, the JIT compiler can significantly improve the execution speed of the program.

2. Dynamic optimization: The JIT compiler has the ability of dynamic optimization, which can make optimization decisions based on the behavior information of the program at runtime. For example, it can do inline unrolling based on the actual frequency of function calls, eliminate redundant calculations, loop unrolling, use more efficient data structures, etc.

3. Cross-platform support: The JIT compiler can select the appropriate target machine code generation according to the hardware architecture and operating system of the current environment, so as to achieve cross-platform support. This allows programs to be run on different systems without recompiling the source code.

4. Dynamic code generation: JIT compilers can dynamically generate new code fragments at runtime, compile them into machine code, and execute them immediately. This makes code generation and tuning in some specific scenarios more flexible and efficient.

JIT compilers are widely used in many fields, including virtual machines (such as Java virtual machines), dynamic language interpreters (such as Python, JavaScript), database systems, and instant games. It can provide the execution speed close to native code while maintaining the flexibility and cross-platform of high-level language, so as to obtain good performance and user experience.

11. What aspects of performance tuning of the JVM need to be considered?

Performance tuning of the JVM (Java Virtual Machine) involves many aspects, the following are some common aspects to consider:

1. Heap Memory Settings: Adjusting the JVM's heap memory size can affect application performance. If the heap memory is too small, it may lead to frequent garbage collection; if the heap memory is too large, it may cause long garbage collection pauses. Reasonably set the size of the heap memory, and tune it according to the needs of the application and the operating environment.

2. Garbage collector selection and tuning: JVM provides different types of garbage collectors, such as Serial, Parallel, CMS, G1, etc. According to the characteristics and needs of the application, select a suitable garbage collector and configure corresponding tuning parameters to minimize the overhead of garbage collection.

3. Thread Configuration: Set the number of threads reasonably, including application threads and garbage collection threads. Too many threads may lead to increased contention and context switching overhead, while too few threads may not fully utilize CPU resources.

4. JVM startup parameter tuning: By adjusting JVM startup parameters, such as -Xms (initial heap size), -Xmx (maximum heap size), -XX:NewRatio (the ratio of the new generation to the old generation), etc., the performance of the JVM can be adjusted Tuning.

5. Memory allocation and object lifecycle management: rationally use technologies such as object pools and caches to avoid frequent memory allocation and garbage collection. Pay attention to release unused objects in time to avoid memory leaks.

6. I/O operation optimization: Reasonable use of buffer, batch read and write, asynchronous IO and other technologies to reduce performance overhead caused by I/O operations.

7. Concurrency tuning: For applications involving concurrent operations, reasonably set the concurrency, such as the size of the thread pool, the granularity of locks, etc., to improve concurrency performance.

8. Use performance analysis tools: use performance analysis tools, such as Java VisualVM, JProfiler, etc., to monitor and analyze the application, find out where the bottleneck is, and make corresponding optimization adjustments.

9. Application design and algorithm optimization: optimize the design and algorithm of the application itself, reduce resource consumption and performance bottlenecks, such as avoiding unnecessary loops, optimizing algorithms with high complexity, etc.

It should be noted that performance tuning is a comprehensive process that needs to be adjusted in combination with specific application scenarios, hardware environments, and performance requirements. Additionally, tuning strategies may vary by JVM version, operating system, and hardware configuration. Therefore, when performing performance tuning, it is recommended to conduct evaluation and testing in combination with actual conditions, and pay close attention to the behavior and performance indicators of the application.

12. What is the difference between a memory leak and a memory overflow?

Memory leak (Memory Leak) and memory overflow (Memory Overflow) are two different memory management problems, they have the following differences:

1. Memory leak: A memory leak refers to the situation where the memory space that has been allocated in the program is not properly released when it is no longer needed. These unreleased memory will continue to occupy system resources, resulting in a gradual decrease in available memory. Memory leaks can be due to erroneous programming behavior, such as forgetting to free dynamically allocated memory, causing circular references that prevent objects from being garbage collected, etc. Memory leaks in long-running programs can cause system performance degradation or crashes.

2. Memory overflow: Memory overflow refers to a program that exceeds its available memory resource limit when applying for memory. Out of memory occurs when a program needs to allocate more memory space than the system can meet the demand. This is usually caused by program logic problems, algorithm errors, or unreasonable data structure design. Out of memory may cause the program to terminate abnormally, crash or trigger system-level errors.

In summary, a memory leak means that the allocated memory space is not released correctly, resulting in waste of resources and a reduction in available memory; and a memory overflow means that the program exceeds its available memory limit when applying for memory. Both can negatively affect program and system performance, but in different reasons and in different ways. Solving memory leaks and out-of-memory problems requires careful analysis of the code and ensuring that memory resources are managed and utilized correctly.

13. How to avoid memory leak and memory overflow?

To avoid memory leaks and memory overflow problems, you can consider the following considerations:

1. Accurate release of memory: For programming languages ​​that use dynamic memory allocation, such as C/C++, ensure that each allocated memory has a corresponding release operation. When a block of memory is no longer needed, call the release function (such as free() or delete) in time to release the memory resource.

2. Avoid circular references: In programming languages ​​that use garbage collection mechanisms, especially object-oriented languages, care should be taken to avoid object relationships that form circular references. Circular references can cause objects to not be correctly identified as recyclable objects by the garbage collector, resulting in memory leaks. It is necessary to carefully handle the reference relationship between objects and break the circular reference in due course.

3. Use automatic memory management tools: Some high-level programming languages ​​provide automatic memory management mechanisms, such as garbage collectors. Proper use of these tools can ease the burden of manual memory management and help avoid common memory leaks.

4. Use recursion and iteration carefully: When using recursive or iterative algorithms, be sure to ensure the correctness of the termination condition to prevent infinite recursion or iteration. Too deep recursive calls will consume a lot of stack space and may cause stack overflow.

5. Bounds checking and error handling: When performing memory operations, bounds checking is performed to ensure that problems such as out-of-bounds access to arrays or buffer overflows do not occur. At the same time, handle errors and exceptions in a timely manner to prevent memory leaks or overflows caused by erroneous memory operations.

6. Perform regular performance testing and memory analysis: Through regular performance testing and memory analysis, you can find potential memory leaks and overflow problems, and take timely measures to fix them. Using a professional memory analysis tool can help detect and diagnose memory problems.

7. Refer to programming conventions and best practices: Following good programming conventions and best practices can help prevent memory leaks and overflows. For example, reasonably manage the object life cycle, use smart pointers and other technologies.

In summary, by properly freeing memory, avoiding circular references, using automatic memory management tools, using recursion and iteration carefully, performing bounds checking and error handling, performing regular performance testing and memory analysis, and referring to programming specifications and best practices, Can effectively avoid memory leaks and memory overflow problems.

14. How to analyze the thread dump file of JVM?

To analyze the JVM thread dump file, you can follow the steps below:

1. Obtain thread dump files: When the JVM is running, you can use commands such as jstack and jcmd to generate thread dump files. For example, use the following command to get a thread dump file:

   jstack <pid> > thread_dump.txt
   

2. Open the thread dump file: Use a text editor to open the thread dump file and view the thread information in it.

3. Analyze thread status: Find threads with abnormal or abnormal status, such as BLOCKED, WAITING, TIMED_WAITING, etc. These threads may be critical threads causing performance problems or deadlocks.

4. View thread stack information: Locate a specific thread and view its complete stack information. By analyzing the stack information, you can understand the thread's execution path, calling relationship and code location.

5. Find the cause of the problem: pay attention to exceptions, deadlocks, long-term blocking, etc. Check whether there are resource contention, deadlock, infinite loop, long-term IO and other problems.

6. Analyze the synchronization situation: Check whether there are synchronization-related operations in the thread stack, such as locking, waiting, notification, etc. Check for race conditions or deadlock situations.

7. Use tools to assist analysis: In addition to manually analyzing thread dump files, you can also use some visual tools to assist analysis, such as VisualVM, MAT (Memory Analyzer Tool), etc. These tools can display thread information, stack data, and memory usage in a more intuitive and interactive manner.

8. Optimization based on the analysis results: optimize the code or configuration based on the analysis results of the thread dump file. It may be necessary to fix problems in the code, adjust the thread pool size, garbage collector parameters, etc., in order to achieve the purpose of performance optimization.

It should be noted that the thread dump file is only a snapshot, and the analysis needs to be combined with the actual application scenario and other monitoring data for comprehensive judgment. In addition, for complex thread dump file analysis, it may be necessary to have a deep understanding of JVM internal principles and threading model knowledge. Therefore, it is recommended to combine professional knowledge and experience and refer to relevant documents and materials when analyzing thread dump files to obtain accurate and comprehensive analysis results.

15. How to locate the performance problem of JVM?

To locate JVM performance problems, you can follow the steps below:

1. Collect performance data: Use performance monitoring tools to collect JVM performance data. These tools include Java Mission Control (JMC), VisualVM, Grafana, Prometheus, and more. The collected performance data can include CPU usage, memory usage, garbage collection statistics, thread status, method call time, etc.

2. Observe the system load: Check the utilization of system resources such as CPU, memory, disk IO, and network IO. If system resources are overused or bottlenecked, there may be an impact on JVM performance.

3. View Garbage Collection: Learn about the type and configuration of garbage collectors, as well as the frequency and duration of garbage collections. High frequency garbage collection and long pauses may be one of the reasons for performance problems.

4. Check the thread status: Check the status of the thread, especially the thread in the BLOCKED, WAITING, TIMED_WAITING state. These threads can be performance issues due to lock contention, deadlocks, infinite loops, etc.

5. Locating hot codes: By analyzing the time-consuming data of method calls, find out the hot codes that consume the most CPU. These methods may be the key points that need to be optimized. You can use tools such as Java Profiler, JMC's Flight Recorder, etc. to locate hot codes.

6. Check memory usage: Observe the usage of heap memory and non-heap memory to see if there are memory leaks or excessive memory usage.

7. Conduct stress testing: run performance test cases in a simulated high-load environment to observe system performance. By analyzing performance indicators and log information, understand the response time and throughput of the system under high load, and find performance bottlenecks.

8. Use debugging tools: If the above steps still fail to locate the problem, you can use debugging tools for in-depth analysis. For example, when a problem occurs, use jstack to obtain the thread dump file, and locate the problem point by analyzing the thread stack information.

9. Optimization based on analysis results: According to the results of the above analysis, corresponding optimization measures are carried out. It may be necessary to fix problems in the code, adjust JVM parameters, optimize algorithms or data structures, etc., to improve system performance.

It should be noted that locating performance problems is an iterative process, which may require collecting and analyzing performance data multiple times and trying different optimization strategies. At the same time, the actual requirements and constraints of the application should also be considered to find the most suitable performance optimization solution.