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How the Java Z Garbage Collector Revolutionized Memory Management

Popularity：185 ℃/2024-10-30 11:33:05

Hello, I'm V, today's content to talk about ZGC, Java Z Garbage Collector (ZGC) is a low-latency garbage collector designed to optimize memory management, mainly for large memory application scenarios. It has revolutionized traditional Java memory management through several key innovations:

V Brother summarized the following 5 points, welcome to discuss together.

1. Very low pause times

  • ZGC's pause time generally stays under 10 milliseconds and does not lengthen as the heap size increases, which is especially important for large applications that require real-time response.
  • This is achieved through concurrent tagging and concurrent redistribution techniques, without stopping the entire application to complete the garbage collection task.

2. Large memory support

  • ZGC was designed from the ground up for memory management of terabyte heaps. Compared to collectors such as G1 or CMS, it can handle larger amounts of memory without compromising performance.

3. Colored Pointers

  • ZGC uses the high bits of 64-bit pointers to mark the different states of an object, enabling object mobility and lifecycle management. This approach allows objects to move within the heap without updating references.
  • The combination of coloring pointers and loading barriers allows ZGC to efficiently track the state of objects and ensure consistent memory management and object movement.

4. Concurrent compression and de-fragmentation

  • ZGC can compress and defragment heap memory without stopping the application. This improves memory utilization and enables long running Java applications to run consistently and stably.

5. generational optimization

  • Although ZGC does not distinguish between young and old generations, its efficient memory management makes it advantageous for handling objects of all lifecycles, and is especially suitable for objects with unpredictable lifecycles.

Usage Scenarios

  • ZGC is suitable for services with huge memory requirements, such as real-time data analytics, high-performance servers, online trading systems, and other Java applications with high requirements for low latency and real-time response.

ZGC greatly improves Java's memory management capabilities, giving developers more options for dealing with large-scale in-memory applications and further optimizing application performance and responsiveness.

In scenarios such as real-time data analytics, high-performance servers, and online trading systems, where low latency, high concurrency, and stability are critical, ZGC's features can significantly optimize the performance of these applications. Let's take a look at how ZGC is used in each of these scenarios.

1. Real-time data analysis

  • specificities: Real-time data analysis usually requires processing large amounts of data with high memory requirements and high response time requirements. Especially in applications such as data stream analysis, event processing and big data statistics, GC stalls can directly affect the real-time data processing.
  • ZGC Optimization：
    • low latency: The pause time of ZGC is kept below 10 milliseconds and does not increase with the heap size. This means that even if the amount of data grows significantly, ZGC's GC pause time is still negligible, thus ensuring a smooth data analysis process.
    • Concurrent memory compression: ZGC is able to concurrently perform memory compression and de-fragmentation at GC time to avoid performance degradation caused by heap memory fragmentation in long-running applications. This is particularly important for real-time data analytics platforms, where applications typically run continuously for long periods of time and handle large numbers of dynamically generated objects.
    • Large memory support: Real-time data analytics systems often need to process terabytes of data, and ZGC can efficiently manage high-capacity memory, thus safeguarding the memory requirements of big data analytics applications.

2. High-performance servers

  • specificities: High-performance servers need to respond quickly to requests in highly concurrent environments, especially in services that deal with a large number of short-cycle requests, where GC stalls may cause user request blocking and slow system response.
  • ZGC Optimization：
    • Concurrent GC processing: ZGC operations such as labeling, compression, and object movement are almost fully concurrent and do not affect service response due to GC stalls, thus ensuring high concurrency performance of the server.
    • coloring pointer: ZGC uses 64-bit colored pointers to allow objects to migrate without updating all references. This not only simplifies memory management, but also reduces memory fragmentation, allowing services to allocate memory more consistently and efficiently in highly concurrent scenarios.
    • elasticity scaling: For high-performance servers, ZGC efficiently manages and allocates large memory pools when the number of requests skyrockets to meet peak resource demands.

3. Online trading system

  • specificities: Online trading systems (e.g., financial and e-commerce) have extremely high latency requirements, as any GC stalls can directly affect the user experience or even trigger trading errors. Trading systems also need to guarantee long-term stability to avoid memory leaks or performance degradation.
  • ZGC Optimization：
    • Extremely low GC downtime: ZGC's pause time is usually at the level of a few milliseconds, and this low-latency feature can significantly reduce transaction delays caused by GCs in the trading system, ensuring a smooth trading process.
    • Secure object movement: ZGC's coloring pointers and loading barriers enable concurrent object movement without pausing the application during GC. This object movement feature avoids transaction lags or delays caused by GC pauses in long-running online systems.
    • High throughput and reliability: ZGC's concurrency compression and memory fragmentation management avoids the performance degradation caused by fragmentation in the old era, so that the trading system can maintain stable memory allocation and management capability under high concurrency and long time operation environment.

wrap-up

  • Low latency, high concurrency, stability guarantee: ZGC is able to effectively address the challenges of real-time data analytics, high-performance servers, and online trading systems with features such as low-latency GC stalls, efficient large-memory management, and concurrent garbage collection.
  • Reduce the risk of memory fragmentation: ZGC's concurrent memory compression and de-fragmentation mechanisms ensure that applications remain stable and efficient over long periods of time.
  • Adaptation to complex and diverse scenariosZGC's advanced memory management provides significant performance improvements for both real-time systems requiring fast response times and online services seeking stability and low latency, freeing applications from the limitations of traditional GC.

How to use ZGC

To enable Z Garbage Collector (ZGC) in Java, we can configure the JVM parameters to turn on ZGC by following the steps below when starting a Java application.

1. Checking the JVM version

  • ZGC is available in JDK 11 and above (and is fully stable in JDK 15 and above).
  • Verify that your JVM version supports ZGC.

The version can be checked from the command line:

   java -version

2. priming parameter

  • utilization-XX:+UseZGCparameter to enable ZGC.
  • You can add this parameter to the command line to start an application. such as V Brother has an application:
     java -XX:+UseZGC -Xms<size> -Xmx<size> -jar
  • -Xms<size> cap (a poem)-Xmx<size> Set the minimum and maximum values for heap memory.ZGC is typically used in large heap memory environments, and the heap size can be set as required, for example-Xmx16g Indicates that the maximum heap memory is 16GB.

3. Optional parameters

ZGC also supports a number of optimization parameters that can be adjusted as required:

  • Limit the number of GC threads：-XX:ConcGCThreads=<n>The default number of threads is related to the number of CPU cores, but can be adjusted appropriately according to the application load.
  • log output: Turn on detailed GC logging to help monitor ZGC performance.
     java -XX:+UseZGC -Xlog:gc -Xlog:gc+phases -jar
  • Maximum pause time target: Although the ZGC pause time is extremely low, it is still possible to set a target pause time such as-XX:MaxGCPauseMillis=<time>The ZGC will try to stay under target, but it is not strictly guaranteed.

4. startup test

utilization-Xlog:gcCheck the GC logs to confirm that ZGC is enabled and to monitor GC performance. You can run the application and then check in the logs to see if it shows information similar to the following:

   Using ZGC
   [gc,start      ] GC(0) Start

Sample Full Command

Assuming that the application requires 16GB of heap space and wants to monitor GC logs, the full command is as follows:

java -XX:+UseZGC -Xms16g -Xmx16g -Xlog:gc -jar

caveat

  • Operating System Requirements: ZGC is only supported on 64-bit Linux, macOS, Windows, make sure your operating system is compatible.
  • hardware requirement: ZGC requires high hardware support for large memory and is usually suitable for heaps larger than 8GB.

OVER, with ZGC turned on and appropriate parameters configured, Java applications will run in a large-memory environment with low pause times, suitable for applications such as real-time data analytics and highly concurrent servers.

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