KAFKA-19259: Async consumer fetch intermittent delays on console consumer (#19980)

There’s a difference in the two consumers’ `pollForFetches()` methods in
this case: `ClassicKafkaConsumer` doesn't block waiting for data in the
fetch buffer, but `AsyncKafkaConsumer` does.

In `ClassicKafkaConsumer.pollForFetches()`, after enqueuing the `FETCH`
request, the consumer makes a call to `ConsumerNetworkClient.poll()`. In
most cases `poll()` returns almost immediately because it successfully
sent the `FETCH` request. So even when the `pollTimeout` value is, e.g.
3000, the call to `ConsumerNetworkClient.poll()` doesn't block that long
waiting for a response.

After sending out a `FETCH` request, `AsyncKafkaConsumer` then calls
`FetchBuffer.awaitNotEmpty()` and proceeds to block there for the full
length of the timeout. In some cases, the response to the `FETCH` comes
back with no results, which doesn't unblock
`FetchBuffer.awaitNotEmpty()`. So because the application thread is
still waiting for data in the buffer, it remains blocked, preventing any
more `FETCH` requests from being sent, causing the long pauses in the
console consumer.

Reviewers: Lianet Magrans <lmagrans@confluent.io>, Andrew Schofield
 <aschofield@confluent.io>
This commit is contained in:
Kirk True 2025-09-05 07:50:47 -07:00 committed by GitHub
parent b92d47d487
commit f922ff6d1f
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5 changed files with 96 additions and 20 deletions

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@ -63,6 +63,7 @@ import java.util.Set;
import java.util.UUID;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicReference;
@ -109,6 +110,7 @@ import static org.junit.jupiter.api.Assertions.assertNotNull;
import static org.junit.jupiter.api.Assertions.assertNull;
import static org.junit.jupiter.api.Assertions.assertThrows;
import static org.junit.jupiter.api.Assertions.assertTrue;
import static org.junit.jupiter.api.Assertions.fail;
@ClusterTestDefaults(
types = {Type.KRAFT},
@ -1593,6 +1595,75 @@ public class PlaintextConsumerTest {
}
}
@ClusterTest
public void testClassicConsumerStallBetweenPoll() throws Exception {
testStallBetweenPoll(GroupProtocol.CLASSIC);
}
@ClusterTest
public void testAsyncConsumerStallBetweenPoll() throws Exception {
testStallBetweenPoll(GroupProtocol.CONSUMER);
}
/**
* This test is to prove that the intermittent stalling that has been experienced when using the asynchronous
* consumer, as filed under KAFKA-19259, have been fixed.
*
* <p/>
*
* The basic idea is to have one thread that produces a record every 500 ms. and the main thread that consumes
* records without pausing between polls for much more than the produce delay. In the test case filed in
* KAFKA-19259, the consumer sometimes pauses for up to 5-10 seconds despite records being produced every second.
*/
private void testStallBetweenPoll(GroupProtocol groupProtocol) throws Exception {
var testTopic = "stall-test-topic";
var numPartitions = 6;
cluster.createTopic(testTopic, numPartitions, (short) BROKER_COUNT);
// The producer must produce slowly to tickle the scenario.
var produceDelay = 500;
var executor = Executors.newScheduledThreadPool(1);
try (var producer = cluster.producer()) {
// Start a thread running that produces records at a relative trickle.
executor.scheduleWithFixedDelay(
() -> producer.send(new ProducerRecord<>(testTopic, TestUtils.randomBytes(64))),
0,
produceDelay,
TimeUnit.MILLISECONDS
);
Map<String, Object> consumerConfig = Map.of(GROUP_PROTOCOL_CONFIG, groupProtocol.name().toLowerCase(Locale.ROOT));
// Assign a tolerance for how much time is allowed to pass between Consumer.poll() calls given that there
// should be *at least* one record to read every second.
var pollDelayTolerance = 2000;
try (Consumer<byte[], byte[]> consumer = cluster.consumer(consumerConfig)) {
consumer.subscribe(List.of(testTopic));
// This is here to allow the consumer time to settle the group membership/assignment.
awaitNonEmptyRecords(consumer, new TopicPartition(testTopic, 0));
// Keep track of the last time the poll is invoked to ensure the deltas between invocations don't
// exceed the delay threshold defined above.
var beforePoll = System.currentTimeMillis();
consumer.poll(Duration.ofSeconds(5));
consumer.poll(Duration.ofSeconds(5));
var afterPoll = System.currentTimeMillis();
var pollDelay = afterPoll - beforePoll;
if (pollDelay > pollDelayTolerance)
fail("Detected a stall of " + pollDelay + " ms between Consumer.poll() invocations despite a Producer producing records every " + produceDelay + " ms");
} finally {
executor.shutdownNow();
// Wait for any active tasks to terminate to ensure consumer is not closed while being used from another thread
assertTrue(executor.awaitTermination(5, TimeUnit.SECONDS), "Executor did not terminate");
}
}
}
private ConsumerRecords<byte[], byte[]> awaitNonEmptyRecords(
Consumer<byte[], byte[]> consumer,
TopicPartition tp

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@ -147,6 +147,7 @@ public abstract class AbstractFetch implements Closeable {
* @param data {@link FetchSessionHandler.FetchRequestData} that represents the session data
* @param resp {@link ClientResponse} from which the {@link FetchResponse} will be retrieved
*/
@SuppressWarnings("NPathComplexity")
protected void handleFetchSuccess(final Node fetchTarget,
final FetchSessionHandler.FetchRequestData data,
final ClientResponse resp) {
@ -174,6 +175,8 @@ public abstract class AbstractFetch implements Closeable {
final Set<TopicPartition> partitions = new HashSet<>(responseData.keySet());
final FetchMetricsAggregator metricAggregator = new FetchMetricsAggregator(metricsManager, partitions);
boolean needsWakeup = true;
Map<TopicPartition, Metadata.LeaderIdAndEpoch> partitionsWithUpdatedLeaderInfo = new HashMap<>();
for (Map.Entry<TopicPartition, FetchResponseData.PartitionData> entry : responseData.entrySet()) {
TopicPartition partition = entry.getKey();
@ -220,8 +223,14 @@ public abstract class AbstractFetch implements Closeable {
metricAggregator,
fetchOffset);
fetchBuffer.add(completedFetch);
needsWakeup = false;
}
// "Wake" the fetch buffer on any response, even if it's empty, to allow the consumer to not block
// indefinitely waiting on the fetch buffer to get data.
if (needsWakeup)
fetchBuffer.wakeup();
if (!partitionsWithUpdatedLeaderInfo.isEmpty()) {
List<Node> leaderNodes = new ArrayList<>();

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@ -1811,7 +1811,7 @@ public class AsyncKafkaConsumer<K, V> implements ConsumerDelegate<K, V> {
// use of a shorter, dedicated "pollTimer" here which updates "timer" so that calling method (poll) will
// correctly handle the overall timeout.
try {
fetchBuffer.awaitNotEmpty(pollTimer);
fetchBuffer.awaitWakeup(pollTimer);
} catch (InterruptException e) {
log.trace("Interrupt during fetch", e);
throw e;

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@ -27,6 +27,7 @@ import org.slf4j.Logger;
import java.util.Collection;
import java.util.Collections;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import java.util.concurrent.ConcurrentLinkedQueue;
import java.util.concurrent.TimeUnit;
@ -51,7 +52,7 @@ public class FetchBuffer implements AutoCloseable {
private final Logger log;
private final ConcurrentLinkedQueue<CompletedFetch> completedFetches;
private final Lock lock;
private final Condition notEmptyCondition;
private final Condition blockingCondition;
private final IdempotentCloser idempotentCloser = new IdempotentCloser();
private final AtomicBoolean wokenup = new AtomicBoolean(false);
@ -62,7 +63,7 @@ public class FetchBuffer implements AutoCloseable {
this.log = logContext.logger(FetchBuffer.class);
this.completedFetches = new ConcurrentLinkedQueue<>();
this.lock = new ReentrantLock();
this.notEmptyCondition = lock.newCondition();
this.blockingCondition = lock.newCondition();
}
/**
@ -95,13 +96,7 @@ public class FetchBuffer implements AutoCloseable {
}
void add(CompletedFetch completedFetch) {
try {
lock.lock();
completedFetches.add(completedFetch);
notEmptyCondition.signalAll();
} finally {
lock.unlock();
}
addAll(List.of(completedFetch));
}
void addAll(Collection<CompletedFetch> completedFetches) {
@ -111,7 +106,8 @@ public class FetchBuffer implements AutoCloseable {
try {
lock.lock();
this.completedFetches.addAll(completedFetches);
notEmptyCondition.signalAll();
wokenup.set(true);
blockingCondition.signalAll();
} finally {
lock.unlock();
}
@ -154,23 +150,23 @@ public class FetchBuffer implements AutoCloseable {
}
/**
* Allows the caller to await presence of data in the buffer. The method will block, returning only
* Allows the caller to await a response from the broker for requested data. The method will block, returning only
* under one of the following conditions:
*
* <ol>
* <li>The buffer was already non-empty on entry</li>
* <li>The buffer was populated during the wait</li>
* <li>The buffer was already woken</li>
* <li>The buffer was woken during the wait</li>
* <li>The remaining time on the {@link Timer timer} elapsed</li>
* <li>The thread was interrupted</li>
* </ol>
*
* @param timer Timer that provides time to wait
*/
void awaitNotEmpty(Timer timer) {
void awaitWakeup(Timer timer) {
try {
lock.lock();
while (isEmpty() && !wokenup.compareAndSet(true, false)) {
while (!wokenup.compareAndSet(true, false)) {
// Update the timer before we head into the loop in case it took a while to get the lock.
timer.update();
@ -185,7 +181,7 @@ public class FetchBuffer implements AutoCloseable {
break;
}
if (!notEmptyCondition.await(timer.remainingMs(), TimeUnit.MILLISECONDS)) {
if (!blockingCondition.await(timer.remainingMs(), TimeUnit.MILLISECONDS)) {
break;
}
}
@ -198,10 +194,10 @@ public class FetchBuffer implements AutoCloseable {
}
void wakeup() {
wokenup.set(true);
try {
lock.lock();
notEmptyCondition.signalAll();
wokenup.set(true);
blockingCondition.signalAll();
} finally {
lock.unlock();
}

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@ -177,7 +177,7 @@ public class FetchBufferTest {
try (FetchBuffer fetchBuffer = new FetchBuffer(logContext)) {
final Thread waitingThread = new Thread(() -> {
final Timer timer = time.timer(Duration.ofMinutes(1));
fetchBuffer.awaitNotEmpty(timer);
fetchBuffer.awaitWakeup(timer);
});
waitingThread.start();
fetchBuffer.wakeup();