Java Flight Recorder: Advanced Profiling & Diagnostics Techniques

Java Flight Recorder (JFR) is a high-performance data collection framework that allows developers to monitor and diagnose Java applications with minimal overhead. It is an indispensable tool for developers looking to gather insights into the inner workings of their applications and optimize them for peak performance. This article explores advanced profiling and diagnostics techniques using Java Flight Recorder and offers practical tips for experienced developers.

1. Understanding Java Flight Recorder (JFR)

Java Flight Recorder, a feature in the JDK since version 11, is a powerful tool for collecting runtime information from a Java application. It is designed to have a low impact on application performance, making it ideal for use in production environments. JFR works by collecting data in circular buffers and writing it to disk when the buffers are full or when the recording is stopped.

2. Enabling Java Flight Recorder

To enable JFR, you must first ensure that you are using a JDK version that supports it (JDK 11 or later). Then, start your application with the following JVM arguments:

-XX:StartFlightRecording=<options>
-XX:+UnlockDiagnosticVMOptions
-XX:+DebugNonSafepointsCode language: Java (java)

Replace <options> with your desired JFR options, such as filename, duration, and settings. For example, the following command starts a recording that will last 60 minutes and save the data to a file called my_recording.jfr:

-XX:StartFlightRecording=filename=my_recording.jfr,duration=60mCode language: Java (java)

3. Advanced Profiling Techniques

3.1. Custom JFR Events

While JFR provides a rich set of built-in events for monitoring JVM performance, you can also create custom events to track application-specific data. To create a custom event, extend the jdk.jfr.Event class and add fields to represent the data you want to record. Then, instantiate the event, set its fields, and call the commit() method to record the event.

import jdk.jfr.Event;
import jdk.jfr.Label;

@Label("My Custom Event")
public class MyCustomEvent extends Event {
    @Label("Custom Value")
    private int customValue;

    public void setCustomValue(int value) {
        this.customValue = value;
    }
}Code language: Java (java)

3.2. Thread Profiling

JFR can help you identify performance bottlenecks by profiling the threads in your application. The jdk.ThreadCPULoad event provides information about CPU usage per thread. Use the jdk.ThreadPark and jdk.ThreadSleep events to analyze thread wait times and identify contention points.

3.3. Garbage Collection Analysis

JFR provides in-depth information about garbage collection (GC) activity in your application. Use the jdk.GarbageCollection event to analyze GC duration and frequency, and the jdk.ObjectCount event to track object allocation rates.

4. Advanced Diagnostics Techniques

4.1. Identifying Memory Leaks

Use JFR’s heap profiling events, such as jdk.ObjectCount and jdk.ObjectAllocationInNewTLAB, to track object allocation and identify potential memory leaks. By analyzing heap data, you can pinpoint the objects causing memory leaks and devise strategies to address them.

4.2. Analyzing JIT Compilation

JFR’s JIT compilation events, such as jdk.Compilation, can help you identify code hotspots and understand how the Just-In-Time (JIT) compiler is optimizing your application. This information can be useful for making informed decisions about code optimizations and tuning JIT compilation settings.

4.3. Monitoring File I/O and Socket Operations

JFR offers events to monitor file I/O and socket operations, such as jdk.FileRead, jdk.FileWrite, jdk.SocketRead, and jdk.SocketWrite. Analyzing these events can help you identify bottlenecks related to disk access or network communication, and optimize your application’s I/O performance.

4.4. Tracking Class Loading and Unloading

By examining the jdk.ClassLoad and jdk.ClassUnload events, you can gain insights into class loading and unloading behavior in your application. This information can help you identify class loading issues, optimize class loader performance, and detect class loader leaks.

5. Analyzing JFR Data

After collecting JFR data, you can use various tools to analyze the results. These include:

5.1. JDK Mission Control (JMC)

JDK Mission Control is the official tool for analyzing JFR data. It offers a powerful and intuitive user interface for exploring JFR recordings and provides advanced visualizations and analysis features. With JMC, you can easily identify performance bottlenecks, memory leaks, and other issues in your application.

5.2. Command-Line Interface (jfr)

The jfr command-line tool, available in JDK 12 and later, allows you to analyze JFR data from the command line. This can be useful for automated analysis or integration with continuous integration pipelines. Use the jfr tool to print summaries, filter events, or extract specific information from JFR recordings.

5.3. Third-Party Tools and Libraries

Several third-party tools and libraries support JFR data analysis, such as VisualVM and the JFR Streaming API. These tools can help you analyze JFR data in different ways or integrate JFR analysis into custom applications.

Exercise: Analyzing an Application with Java Flight Recorder

Objective: In this exercise, you will create a sample Java application that simulates an e-commerce checkout process, and then use Java Flight Recorder to analyze its performance.

Step 1: Create the sample Java application

1.1. Define the Product class to represent an e-commerce product:

public class Product {
    private String name;
    private double price;

    public Product(String name, double price) {
        this.name = name;
        this.price = price;
    }

    public String getName() {
        return name;
    }

    public double getPrice() {
        return price;
    }
}Code language: Java (java)

1.2. Define the CheckoutEvent class, a custom JFR event that records the details of a checkout:

import jdk.jfr.Event;
import jdk.jfr.Label;

@Label("Checkout Event")
public class CheckoutEvent extends Event {
    @Label("Total Amount")
    private double totalAmount;

    public void setTotalAmount(double totalAmount) {
        this.totalAmount = totalAmount;
    }
}Code language: Java (java)

1.3. Create the ECommerceApp class, which simulates the e-commerce checkout process:

import java.util.List;
import java.util.Random;

public class ECommerceApp {

    private static final List<Product> PRODUCTS = List.of(
            new Product("Product A", 20.0),
            new Product("Product B", 30.0),
            new Product("Product C", 40.0),
            new Product("Product D", 50.0)
    );

    public static void main(String[] args) throws InterruptedException {
        while (true) {
            simulateCheckout();
            Thread.sleep(1000);
        }
    }

    private static void simulateCheckout() {
        Random random = new Random();
        int numberOfItems = random.nextInt(5) + 1;

        double totalAmount = 0;
        for (int i = 0; i < numberOfItems; i++) {
            Product product = PRODUCTS.get(random.nextInt(PRODUCTS.size()));
            totalAmount += product.getPrice();
        }

        CheckoutEvent checkoutEvent = new CheckoutEvent();
        checkoutEvent.setTotalAmount(totalAmount);
        checkoutEvent.commit();
    }
}Code language: Java (java)

Step 2: Run the application with Java Flight Recorder enabled

2.1. Compile and run the application with JFR enabled:

javac Product.java CheckoutEvent.java ECommerceApp.java
java -XX:StartFlightRecording=filename=ecommerce.jfr,duration=60s -cp . ECommerceAppCode language: Java (java)

This command starts a 60-second JFR recording, saving the data to a file named ecommerce.jfr.

Step 3: Analyze the JFR data

3.1. Use JDK Mission Control to open the ecommerce.jfr file and analyze the custom Checkout Event.

3.2. Examine the Total Amount field of the custom events to understand the distribution of checkout amounts.

3.3. Analyze other JFR events, such as jdk.ThreadCPULoad, jdk.GarbageCollection, and jdk.ObjectCount, to gain insights into the application’s performance, garbage collection, and memory usage.

In this exercise, you created a sample Java application that simulates an e-commerce checkout process and used Java Flight Recorder to analyze its performance. By implementing custom JFR events and analyzing built-in events, you can gain valuable insights into your application’s performance and behavior, helping you optimize the application and deliver a better experience for end-users.