Garbage collection (GC), as its name implies, is a means of freeing space occupied by waste materials, or garbage, and avoid memory leaks. Through performing the GC mechanism, available memory can be effectively used. Moreover, through this process, objects that are dead or unused for a long time in the memory heap will be deleted and the memory space used by these objects will be reclaimed.
GC on the Java virtual machine (JVM) follows the Stop-The-World mechanism. Stop-The-World means that the execution of the program is suspended for GC till all objects in the heap are processed.
In Java, GC roots can be four types of objects:
After determining the garbage to be collected, the garbage collector starts its work. However, this involves a question: How can we efficiently perform GC? JVM specifications do not clearly define how to implement the garbage collector. Therefore, VMs from different manufacturers can implement the garbage collector in different ways.
For more detailed information, please go to How Does Garbage Collection Work in Java?.
In this article, we will look at the system implemented by Alibaba's Xianyu team, which can process tens of millions of data records every second in real time.
To gain a better grasp of the system and how it works, it's important to clarify first what exactly are the system inputs and outputs.
First, the system's inputs include the following: First there's request logs, including the traceID, timestamp, client IP address, server IP address, consumed time, return code, service name, and method name. Then, there's also the environment monitoring data, which includes the indicator name, IP address, timestamp, and indicator value, which may be (for example, the CPU, number of Java Virtual Machine (JVM) garbage-collections (GCs), JVM consumed time (GC), and database indicators).
Now, let's discuss the system outputs: Outputs include the root causes of service errors within a time period. A directed acyclic graph (DAG) is used to display the error analysis result of each service error. The root node is the analyzed error node, while the left nodes are the error root cause nodes. A leaf node may be an externally dependent service error or a Java Virtual Machine (JVM) exception.
The Alibaba Cloud messaging team devoted to Apache RocketMQ™ performance optimization has reached new heights in recent times with the latest TPS for medium-sized and small messages in Apache RocketMQ™ by reaching 470,000. The TPS peak, once, detected on F43 model hit 570,000. How you ask? This article will review some of the techniques we used.
Before we get down to performance optimization at the kernel level, we first need to perform the Java-level optimization. First you must ensure that no other interferences, as well as a complete utilization of the features of JVM preheat (JIT) exist. Our recommendation would be the Benchmark tool JMH developed by OpenJDK.
The biggest hurdle impairing the Java application performance is the JVM pause. We are also familiar with the STW (Stop the World) at the GC stage STW, and in addition to GC, there are many other reasons that affect the Java application.
Response time errors are likely caused by the long response time of downstream applications, uneven traffic, an excessive number of full garbage collection (GC) activities, or an excessive load.
Locating and troubleshooting response time errors is a long and complex process. Application Real-Time Monitoring Service (ARMS) provides the active diagnosis feature to help you quickly and accurately locate response time errors. Active diagnosis of ARMS shortens the response time of applications.
The application monitoring function of Application Real-Time Monitoring Service (ARMS) provides the Java Virtual Machine (JVM) monitoring function. It monitors heap metrics, non-heap metrics, direct buffer metrics, memory-mapped buffer metrics, garbage collection (GC) details, and the number of JVM threads. This topic describes the JVM monitoring feature and how to monitor JVM metrics.
Application Real-Time Monitoring Service (ARMS) is an end-to-end Alibaba Cloud monitoring service for Application Performance Management (APM). You can quickly develop real-time business monitoring capabilities using the frontend monitoring, application monitoring, and custom monitoring features provided by ARMS.
Log Service is a complete real-time data logging service that has been developed by Alibaba Group. Log Service supports collection, consumption, shipping, search, and analysis of logs, and improves the capacity of processing and analyzing large amounts of logs.
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