JMC 6 Automated Analysis Headless

This post will be a little bit wider than the title implies; it will be about using the JMC core JFR APIs in general. That said, one of the things we will be using it for, towards the end, will be to run the JMC 6 automated analysis headless.

This article will also cheat by talking about JMC 6.1, so that anyone reading this article will have relevant information for JMC 6.1 as well. Winking smile 

The JAR-files Needed

To run these examples you will need to have the following Jar-files from the JDK_HOME/lib/missioncontrol/plugins folder on your classpath:

Prefix

Version needed

Comment

com.oracle.jmc.common

>= 6.0.0

Classes common to JMC, such as stacktrace definitions, the content type system (quantities/ units of measurement) etc.
com.oracle.jmc.flightrecorder

>= 6.0.0

The Java Flight Recorder parser, classes for extracting information from a recording.
com.oracle.jmc.flightrecorder.rules

>= 6.0.0

The core definitions and classes for automated analysis of recordings.
com.oracle.jmc.flightrecorder.rules.jdk

>= 6.0.0

Contains the rules for the JDK (such as rules for synchronization trouble, long lasting VM operations and much more).
com.oracle.jmc.flightrecorder.ext.wls.parser

>= 6.0.0

(Optional, only relevant for users wanting WebLogic Server extensions)
com.oracle.jmc.flightrecorder.ext.wls.rules

>= 6.0.0

(Optional, only relevant for users wanting WebLogic Server extensions)

Loading a Recording

Loading a recording is done through a call to the JfrLoaderToolkit#loadEvents(). It takes a file argument, and returns an IItemCollection. The IItemCollection can be thought of as a collection of events.

The IItemCollection supports operations like filter(), and getAggregate(). Used correctly, you should rarely need to rely on external iteration.

Here is an example which loads a recording, and calculates the standard deviation for the java monitor enter events in a recording:

import java.io.File;

import com.oracle.jmc.common.IDisplayable;
import com.oracle.jmc.common.item.Aggregators;
import com.oracle.jmc.common.item.IItemCollection;
import com.oracle.jmc.common.item.ItemFilters;
import com.oracle.jmc.common.unit.IQuantity;
import com.oracle.jmc.flightrecorder.JfrAttributes;
import com.oracle.jmc.flightrecorder.JfrLoaderToolkit;
import com.oracle.jmc.flightrecorder.jdk.JdkTypeIDs;

/**
 * Finds out the standard deviation for the java monitor enter events.
 */
public class LoadRecording {
	public static void main(String[] args) throws Exception {
		DemoToolkit.verifyFirstFileArgument(RunRulesOnFile.class, args);
		
		IItemCollection events = JfrLoaderToolkit.loadEvents(new File(args[0]));
		IQuantity aggregate = events.apply(ItemFilters.type(JdkTypeIDs.MONITOR_ENTER))
				.getAggregate(Aggregators.stddev(JfrAttributes.DURATION));
		
		System.out.println("The standard deviation for the Java monitor enter events was "
				+ aggregate.displayUsing(IDisplayable.AUTO));
	}
}

Note the stream-like syntax. The JMC libraries work well together with streams, but are compiled on JDK 7, and can run on a JDK 7 compliant runtime. Also note that some class names start with Jfr whilst others class names start with Jdk. The difference being that some concepts, like DURATION, are intrinsic to JFR, whilst other are defined in terms of the Java JDK classes or runtime, like MONITOR_ENTER.

The JMC core libraries provide common statistical aggregators, and accessors for common attributes. Should you feel something is missing, it is easy to add to the built-in operations.

Also note the IQuantity returned by the aggregator. The built-in system for handling quantities and units of measurement makes it easy to calculate with, and display, quantities in different units of measurement.

Performing an Automated Analysis Headless

It is also easy to run the JMC rules headless using these core libraries. Simply evaluate the rules against the IItemCollection. Here is a simple example iterating through the rules and evaluating them one by one:

import java.io.File;
import java.util.concurrent.RunnableFuture;

import com.oracle.example.jmc6jfr.rules.util.DemoToolkit;
import com.oracle.jmc.common.item.IItemCollection;
import com.oracle.jmc.common.util.IPreferenceValueProvider;
import com.oracle.jmc.flightrecorder.JfrLoaderToolkit;
import com.oracle.jmc.flightrecorder.rules.IRule;
import com.oracle.jmc.flightrecorder.rules.Result;
import com.oracle.jmc.flightrecorder.rules.RuleRegistry;

public class RunRulesOnFileSimple {
	public static void main(String[] args) throws Exception {
		File recording = DemoToolkit.verifyRecordingArgument(RunRulesOnFileSimple.class, args);
		IItemCollection events = JfrLoaderToolkit.loadEvents(recording);
		
		for (IRule rule : RuleRegistry.getRules()) {
			RunnableFuture<Result> future = rule.evaluate(events, IPreferenceValueProvider.DEFAULT_VALUES);
			future.run();
			Result result = future.get();
			if (result.getScore() > 50) {
				System.out.println(String.format("[Score: %3.0f] Rule ID: %s, Rule name: %s, Short description: %s",
						result.getScore(), result.getRule().getId(), result.getRule().getName(),
						result.getShortDescription()));
			}
		}
	}
}

That said, if you are not constrained to have to run on JDK 7, you can always run the rules in parallel, for example by employing parallel streams:

import java.io.File;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Executor;
import java.util.concurrent.Executors;
import java.util.concurrent.RunnableFuture;
import java.util.stream.Collectors;
import java.util.stream.Stream;

import com.oracle.jmc.common.item.IItemCollection;
import com.oracle.jmc.common.util.IPreferenceValueProvider;
import com.oracle.jmc.flightrecorder.JfrLoaderToolkit;
import com.oracle.jmc.flightrecorder.rules.IRule;
import com.oracle.jmc.flightrecorder.rules.Result;
import com.oracle.jmc.flightrecorder.rules.RuleRegistry;

/**
 * Runs the rules on the events in the specified file in parallel, then prints
 * them in order of descending score.
 */
public class RunRulesOnFile {
	private final static Executor EXECUTOR = Executors
			.newFixedThreadPool(Runtime.getRuntime().availableProcessors() - 1);
	private static int limit;

	public static void main(String[] args) throws Exception {
		if (args.length == 0) {
			System.out.println(
					"Usage: RunRulesOnFile <recording file> [<limit>]\n\tThe recording file must be a flight recording from JDK 7 or above. The limit, if set, will only report rules triggered with a score higher or equal than the limit.");
			System.exit(2);
		}
		IItemCollection events = JfrLoaderToolkit.loadEvents(new File(args[0]));
		if (args.length > 1) {
			limit = Integer.parseInt(args[1]);
		}
		Stream<RunnableFuture<Result>> resultFutures = RuleRegistry.getRules().stream()
				.map((IRule r) -> evaluate(r, events));
		List<Result> results = resultFutures.parallel().map((RunnableFuture<Result> runnable) -> get(runnable))
				.collect(Collectors.toList());
		results.sort((Result r1, Result r2) -> Double.compare(r2.getScore(), r1.getScore()));
		results.stream().forEach(RunRulesOnFile::printResult);
	}

	public static RunnableFuture<Result> evaluate(IRule rule, IItemCollection events) {
		RunnableFuture<Result> evaluation = rule.evaluate(events, IPreferenceValueProvider.DEFAULT_VALUES);
		EXECUTOR.execute(evaluation);
		return evaluation;
	}

	public static Result get(RunnableFuture<Result> resultFuture) {
		try {
			return resultFuture.get();
		} catch (InterruptedException | ExecutionException e) {
			e.printStackTrace();
		}
		return null;
	}

	private static void printResult(Result result) {
		if (result.getScore() >= limit) {
			System.out.printf("(%.0f) [%s]: %s\nDetails:\n%s\n============<End of Result>============\n",
					result.getScore(), result.getRule().getId(), result.getShortDescription(),
					result.getLongDescription() == null ? "<no description>" : result.getLongDescription());
		}
	}
}

If you do not need that kind of control, there is a class available for performing automated analysis included with the JMC core library. To run an automatic analysis, simply run the class:

com.oracle.jmc.flightrecorder.rules.report.JfrRulesReport <files> –format <format> –min <severity>

…where files is one or more recordings, and <format> is and <min> is minimum severity to report [ok | info | warning]. In JMC 6.1.0 there is one additional class for generating the file, which produces an HTML in a format and style very similar to the looks of the JMC 6.0.0 Automated Analysis page:

com.oracle.jmc.flightrecorder.rules.report.html.JfrHtmlRulesReport <file> [<outputfile>]

…where <file> is the (single) recording to analyze, and where the optional <outputfile> is where the resulting HTML should be written. If no outputfile is specified, the result of the analysis will be written on stdout.

Adding Custom Rules

It’s easy to add you own heuristics. Do you find yourself with thousands of recordings, and would like to add a Bayesiean network to do some machine learning? The rules are all pure Java, so you can pretty much do whatever you want in a rule.

The easiest way to get started writing your own custom rules is to get yourself an Eclipse Oxygen or later, and install JMC and the experimental PDE plug-in into your Eclipse.

  1. Install Eclipse Oxygen or later.
  2. Got to the Mission Control homepage, and find the Eclipse Update site.
  3. Follow the instructions to install the Mission Control plug-ins.
    image
  4. Got to the Mission Control homepage, and find the Experimental Update site.
  5. Install the PDE plug-in.
    image

Here is a cheat sheet for the eclipse update sites for the JMC 6.0.0 release:

http://download.oracle.com/technology/products/missioncontrol/updatesites/base/6.0.0/eclipse/

http://download.oracle.com/technology/products/missioncontrol/updatesites/supported/6.0.0/eclipse/

http://download.oracle.com/technology/products/missioncontrol/updatesites/experimental/6.0.0/eclipse/

(JMC 6.1.0 will be released according to the same URL pattern.)

To start building your rule, press ctrl-n (or click the File | New | Other… menu) to bring up the New wizard.

image

Select Plug-in Project and hit Next. Name your rule project something exciting.

pic

Unclick that this plug-in will make contributions to the UI and hit Next.

pic2

Next select the Simple JFR Rule Wizard and click Finish (or Next, if you really wish to do some further customizations).

pic3

You will now have a new project in your workspace, containing an example rule. If you have compilation errors, you need to set JMC to be your target platform (see the next section). You can either just export your rule, put it on the class path with the other core libraries, or you can try out your rule by running JMC from within Eclipse with your new rule.

Starting JMC from within Eclipse with Workspace Plug-ins

Running JMC from within Eclipse with any plug-ins you are currently developing is a simple matter of setting the plug-in development target platform to your JMC installation, and launching that platform with your workspace plug-ins.

First set JMC to be your target platform.

  1. Go to Preferences in the main menu (Window | Preferences on Windows).
  2. Find Target Platform by typing Tar in the filter box:
    image
  3. Click Add… and type JMC 6 as name.
    image
  4. Press Add… and select Installation. Hit Next.
    image
  5. Browse to the JMC 6 installation directory (JDK_9_HOME/lib/missioncontrol), and hit Ok.
    SNAGHTML1538a63d
  6. Hit Finish, and Finish. You should now see your new platform.
    image
  7. Select the new JMC 6 platform, and hit Apply and Close to activate it.
    image

Everything should now compile cleanly. Next step is to run JMC with your new rule.

  1. Context click on your project and select Run as Eclipse Application
    SNAGHTML153e5cb4
  2. This should normally be it. If you for some reason run into trouble, go to Run Configurations, and make sure that your launcher is using the com.oracle.jmc.rcp.application.product.
    SNAGHTML1540e14b

You should now be able to see your rule in action. If you have not changed the rule code, try setting the environment variable in the launcher to various values between 0 and 100 and see what happens when you run the rule in JMC:

image

image

Exporting a Plug-in

You can export your rule by context-clicking on the project and selecting Export. In the Export wizard, select Deployable plug-ins and Fragments.

image 

Click Next, select a folder to export the plug-in to and Finish. The resulting jar can either be put on the class path to be included in the headless analysis, or put in the dropins folder of any Java Mission Control installation where you would want the rule to be available.

Summary

This blog described how to:

  • Get started using the JMC core libraries to read Java Flight Recordings (JDK 7, 8 and 9)
  • Get started doing headless analysis of Java Flight Recordings (JDK 7, 8 and 9)
  • Get started creating custom rules for analyzing Java Flight Recordings

Hope it helps someone!

Java Flight Recorder in JDK 9

As you probably already know, JFR is on the road to be open sourced. The plans are being drawn, and if everything goes well, this could happen as early as in JDK 10 (JDK 18.3). No promises, and please do not give anyone a hard time if this doesn’t work out. Know that we tried. Anyways, what we did recently do was to release JDK 9, and there are a LOT of exciting stuff happening for JFR already in JDK 9. Smile

Let’s dive into it…

Supported APIs

Yep. The JFR APIs in the JDK are supported. This means that unlike all my other posts on JFR related APIs, this post does not contain any disclaimer for using these APIs. They are supported! By Oracle! Woho!

On the sad side, this also means that the APIs have changed package, and signatures. On the plus side, they have been immensely enhanced for readability, performance and ease of use.

I will group the API as follows:

  • API for Custom Events
  • API for Controlling the Flight Recorder
  • API for Consuming Recordings

Now, there is an advanced API for consuming recordings included with JMC. That API sports internal iteration, aggregation in various forms, JDK 7, 8 and 9 JFR file compatibility, JDK 7 and later execution compatibility, POJO (no weird dependencies), rules evaluation, and more. This API will also be open sourced, and I will discuss it in a later post.

Creating Custom Events

The API for creating and recording your own events is very simple. All you need to do is to subclass jdk.jfr.Event.and annotate the fields you wish to record with jdk.jfr.Label.

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

public class Hello {
	@Label("Hello World")
	static class HelloWorldEvent extends Event {
		@Label("Message")
		String message;
	}
	public static void main(String... args) {
		HelloWorldEvent event = new HelloWorldEvent();
		event.message = "Hello World event message!";
		event.commit();
	}
}

It is good form to provide a description for your event class and for non-trivial attributes. Here is an example of an event from a JUnit plug-in for JUnit 5 (that I have not released for JDK 9 yet):

/**
 * Event for a test run and completed normally (without exception).
 * 
 * @author Marcus Hirt
 */
@Label("Test Run")
@Description("JUnit test executed and completed normally without exception")
@Category("JUnit")
public class TestEvent extends Event {
    @Label("Display Name")
    @Description("The JUnit display name for the test")
    private String displayName;

    public void setDisplayName(String displayName) {
        this.displayName = displayName;
    }

    public String getDisplayName() {
        return displayName;
    }
}

Other important annotations are, for example, the annotation for providing information about the content. These annotations are put on fields to explain to tools how to interpret the data. For example, Java Mission Control would be able to properly render timestamps and durations properly, if the appropriate @Timestamp and @Timespan annotations were used. I have provided a quick overview of some of the most commonly used ones below:

Annotation Comment
@Address The value is a memory address
@BooleanFlag The value is a boolean flag. Strictly speaking perhaps not the most useful one.
@Frequency The value is a frequency, in Hz
@MemoryAddress The value is a memory address.
@MemoryAmount The value is an amount of memory, in bytes.
@NetworkAddress The value is a network address. Value is a long below 2^32 or an unsigned integer and clients will likely display it in the usual octet format (e.g. 127.0.0.1).
@Percentage The event is a fraction, typically between 0 and 1, and is best represented as a percentage
@Timespan The event is a duration. Defaults to nanoseconds, but can be changed by setting value to one of the static fields defined in Timespan: MICROSECONDS, MILLISECONDS, NANOSECONDS, SECONDS, TICKS. It is always nice to explicitly set value (even for NANOSECONDS), so that it can be readily seen what was intended.
@Timestamp The event is a timestamp. Defaults to MILLISECONDS_TO_EPOCH, but can be changed by setting value to one of the static fields defined in Timestamp: MILLISECONDS_SINCE_EPOCH, TICKS. It is always nice to explicitly set value (even for MILLISECONDS_SINCE_EPOCH), so that it can be readily seen what was intended.

There are other annotations worth knowing about such as these:

Annotation Comment
@Enabled Determines if the event should be enabled by default. Remember the bad old days when you added an event, and then did not see it recorded, since the template did not include it? No more. Also, events are enabled by default, so be careful to explicitly set this to false if the event is expensive. Enable is true by default.
@Experimental The element is experimental, and may change in future versions without prior notice.
@Label The human readable label for the element. Use headline-style capitalization, capitalize first and last words, and all nouns, pronouns, verbs and adverbs. Do not include punctuation.
@Period The default period for a periodic event.
@Registered Events are automatically registered by default when they are first used. This annotation can override this behaviour. If you want to make sure that an event which is not likely to be encountered is registered, perhaps to make the metadata available to tools, you can use FlightRecorder.register(class) to register the event programatically.
@Threshold Defines the default threshold for the event. When an even have a duration lower than the threshold, it will not be recorded. The user can override this threshold in the template settings.
@Unsigned The field value should be treated as an unsigned value.


This is by no means an exhaustive list of all the annotations, and as soon as I find out where the javadocs will end up, I will add a link to them.

Note that the programming model is simpler, compared to previous releases. There is no Producer with which you need to register the events. The life cycle of an event simply follows the life cycle of the event class. Also, new event types are enabled by default. As a matter of fact, all the defaults for an event type can be configured using annotations. Also, compared to previous releases, you do not need to explicitly reuse event objects and keep event tokens around; care has been taken to ensure that events on the hot path should be easy to scalarize.

API for Controlling the FlightRecorder

In JDK 9 there are actually two, related, APIs for controlling the FlightRecorder. Just like before, there will be a JMX API. This API provides similar capabilities as the JDK 8 JMX API, but the API has been cleaned up and moved from the com.oracle.jrockit domain to the jdk.management.flightrecorder domain.

image

I will not spend much time on the JMX API. A good example on how to use the different versions of it will be provided in the JMC source, once it is open sourced.

Another addition is an easy to use local API for controlling the Flight Recorder. Here is an example which starts a recording, records the calculation of the first 50 Fibonacci numbers and writes the recording to disk:

import java.io.IOException;
import java.nio.file.Path;
import java.nio.file.Paths;

import com.oracle.example.jdk9jfr.fib.Fibonacci;
import com.oracle.example.jdk9jfr.fib.FibonacciEvent;

import jdk.jfr.Recording;

/**
 * Example program both controlling the recorder and parsing the resulting data.
 * 
 * The program will calculate the 50 first Fibonacci numbers, then print them
 * out.
 */
public class RecordOnly {
	public static void main(String[] args) throws IOException {
		if (args.length == 0) {
			System.out.println("Need to specify a location for the recording!");
			System.exit(2);
		}
		
		Path path = Paths.get(args[0]);

		try (Recording recording = new Recording()) {
			recording.setName("Fibonacci Recording");
			recording.start();
			recording.enable(FibonacciEvent.class);
			for (int n = 0; n &lt; 50; n++) {
				System.out.println("Calculating fib " + n);
				FibonacciEvent event = new FibonacciEvent();
				event.number = n;
				event.begin();
				event.value = Fibonacci.fibonacciIterative(n);
				event.commit();
			}
			recording.stop();
			recording.dump(path);
		}
	}
}

Consuming Recordings

There is a very easy to use API for consuming the recordings included in the JDK as well. It is only supported to use it to read recordings produced from the same JDK as the API reading it, and it is only supported to run the parser in the same JDK with which it is provided. So, in short, JFR recordings produced by JDK 9, and the parser running on JDK 9.

As I mentioned in the beginning, there is another parser included in JMC, with supported reading JDK 7, 8 and 9 recordings, and which supports internal iteration, aggregation in various forms, JDK 7 and later execution compatibility, and rules evaluation. It is still POJO, so it can be included into anything. Which parser to use depends on what you are trying to accomplish.

Here is an addition to the previous example which also reads the produced recording using the Parser built into the JDK, and which then writes out information from the captured events on stdout:

import java.io.IOException;
import java.nio.file.Path;
import java.nio.file.Paths;

import com.oracle.example.jdk9jfr.fib.Fibonacci;
import com.oracle.example.jdk9jfr.fib.FibonacciEvent;

import jdk.jfr.Recording;
import jdk.jfr.consumer.RecordedEvent;
import jdk.jfr.consumer.RecordingFile;

/**
 * Example program both controlling the recorder and parsing the resulting data.
 * 
 * The program will calculate the 50 first Fibonacci numbers, then print them
 * out.
 */
public class RecordAndConsume {
	public static void main(String[] args) throws IOException {
		if (args.length == 0) {
			System.out.println("Need to specify a location for the recording!");
			System.exit(2);
		}
		
		Path path = Paths.get(args[0]);

		try (Recording recording = new Recording()) {
			recording.setName("Fibonacci Recording");
			recording.start();
			recording.enable(FibonacciEvent.class);
			for (int n = 0; n &lt; 50; n++) {
				System.out.println("Calculating fib " + n);
				FibonacciEvent event = new FibonacciEvent();
				event.number = n;
				event.begin();
				event.value = Fibonacci.fibonacciIterative(n);
				event.commit();
			}
			recording.stop();
			recording.dump(path);
			for (RecordedEvent event : RecordingFile.readAllEvents(path)) {
				int number = event.getValue("number");
				long value = event.getValue("value");
				System.out.printf("fibonacci(%d) = %d (time: %dns)\n", number, value, event.getDuration().getNano());
			}
		}
	}
}

Other Improvements to JFR in JDK 9

Here is a list of some other improvements to JFR in JDK9:

  • Modularized APIs (if you do not need the JMX API, don’t include it).
  • Extensible APIs (can provide custom settings for event types, can provide custom metadata using annotations)
  • Performance improvements (more on this later)
  • Can emit data even in bad situations (Out of Memory for example)
  • New events
    • More detailed safe point information
    • More detailed code cache information
    • New PLAB (promotion) events
    • New compiler events for detailed inlining information
    • New H1 specific information for better visualization of region states
    • Module events (loaded modules, full transitive closure)
    • NativeLibrary (load, a periodic event, by default emitted each chunk)
    • …and more. Just make a test recording and include them all. Winking smile

Performance Enhancements

Here is a graphic (provided by my excellent friend Erik Gahlin at the Oracle JPG Serviceability Team), which shows some of the areas where JFR has improved in JDK 9:

image

Let’s take them in order:

  1. The time spent in safepoints due to chunk rotation to disk has been reduced from a bit over 7ms to almost nothing.
  2. If you have code with a disabled Java event, the overhead of having the event related code in your method will be zero (if that code is on the hot path). After optimization, any trace of the event related code will be optimized away.
  3. The overhead of writing an event (without capturing stack traces), has gone from 8ns to 6ns.
  4. The file size (and buffer memory usage) has roughly been cut by half, due to the introduction of compressed integers.
  5. The time required to capture a stack trace has been almost cut in half.
  6. Even the startup has been slightly improved.

So, not only have the APIs become easier to use, and more comprehensive. JFR has also become significantly faster. That is a bit of a feat, considering that it wasn’t very slow to begin with.

Summary

The new Java release, JDK 9, provides plenty of improvements to JFR:

  1. Supported API
  2. Simplified programming model
  3. Higher performance

This blog provided a quick introduction to JFR in JDK 9, with some simple examples.

Here is a link to the full source for the examples: source_jdk9_jfr_examples.zip