Monthly Archives: October 2025

Making JFR Quack: Importing JFR files into DuckDB

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In my previous post, I showed you how tricky it is to compare objects from the JFR Java API. You probably wondered why I wrote about this topic. Here is the reason: In this blog post, I’ll cover how to load JFR files into a DuckDB database to allow querying profiling data with simple SQL queries, all JFR views included.

This blog post will start a small series on making JFR quack.

TL;DR

You can now use a query tool (via GitHub) to transform JFR files into similarly sized DuckDB files:

> java -jar target/query.jar duckdb import jfr_files/recording.jfr duckdb.db
> duckdb duckdb.db "SELECT * FROM Events";
┌───────────────────────────────┬───────┐
│             name              │ count │
│            varchar            │ int32 │
├───────────────────────────────┼───────┤
│ GCPhaseParallel               │ 69426 │
│ ObjectAllocationSample        │  6273 │

Or run the queries directly, with the database file being cached (if you don’t pass --no-cache), directly supporting all built-in JFR views:

> java -jar target/query.jar query jfr_files/metal.jfr "hot-methods" 
Method                                                                                                   Samples Percent
-------------------------------------------------------------------------------------------------------- ------- -------
java.util.concurrent.ForkJoinPool.deactivate(ForkJoinPool.WorkQueue, int)                                   1066   8.09%
scala.collection.immutable.RedBlackTree$.lookup(RedBlackTree.Tree, Object, Ordering)                         695   5.27%
akka.actor.dungeon.Children.initChild(ActorRef)                                                              678   5.14%

This view is implemented as:

CREATE VIEW "hot-methods" AS
SELECT
  (c.javaName || '.' || m.name || m.descriptor) AS "Method",
  COUNT(*) AS "Samples",
  format_percentage(COUNT(*) / (SELECT COUNT(*) FROM ExecutionSample)) AS "Percent"
FROM ExecutionSample es
JOIN Method m ON es.stackTrace$topMethod = m._id
JOIN Class c ON m.type = c._id
GROUP BY es.stackTrace$topApplicationMethod, c.javaName, m.name, m.descriptor
ORDER BY COUNT(*) DESC
LIMIT 25
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JFR and Equality: A tale of many objects

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In the last blog post, I showed you how to silence JFR’s startup messages. This week’s blog post is also related to JFR, and no, it’s not about the JFR Events website, which got a simple search bar. It’s a short blog post on comparing objects from JFR recordings in Java and why this is slightly trickier than you might have expected.

Example

Getting a JFR recording is simple; just use the RecordingStream API. We do this in the following to record an execution trace of a tight loop using JFR and store it in a list:

List<RecordedEvent> events = new ArrayList<>();
// Know when to stop the loop
AtomicBoolean running = new AtomicBoolean(true);
// We obtain one hundred execution samples 
// that have all the same stack trace
final long currentThreadId = Thread.currentThread().threadId();
try (RecordingStream rs = new RecordingStream()) {
    rs.enable("jdk.ExecutionSample").with("period", "1ms");
    rs.onEvent("jdk.ExecutionSample", event -> {
        if (event.getThread("sampledThread")
                 .getJavaThreadId() != currentThreadId) {
            return; // don't record other threads
        }
        events.add(event);
        if (events.size() >= 100) {
            // we can signal to stop
            running.set(false);
        }
    });
    rs.startAsync();
    int i = 0;
    while (running.get()) { // some busy loop to produce sample
        for (int j = 0; j < 100000; j++) {
            i += j;
        }
    }
    rs.stop();
}
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