kafka RecordCollectorImpl 源码
kafka RecordCollectorImpl 代码
文件路径：/streams/src/main/java/org/apache/kafka/streams/processor/internals/RecordCollectorImpl.java
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.kafka.streams.processor.internals;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.common.KafkaException;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.errors.AuthenticationException;
import org.apache.kafka.common.errors.AuthorizationException;
import org.apache.kafka.common.errors.InvalidProducerEpochException;
import org.apache.kafka.common.errors.InvalidTopicException;
import org.apache.kafka.common.errors.OffsetMetadataTooLarge;
import org.apache.kafka.common.errors.OutOfOrderSequenceException;
import org.apache.kafka.common.errors.ProducerFencedException;
import org.apache.kafka.common.errors.RetriableException;
import org.apache.kafka.common.errors.SecurityDisabledException;
import org.apache.kafka.common.errors.SerializationException;
import org.apache.kafka.common.errors.TimeoutException;
import org.apache.kafka.common.errors.UnknownServerException;
import org.apache.kafka.common.header.Headers;
import org.apache.kafka.common.metrics.Sensor;
import org.apache.kafka.common.serialization.Serializer;
import org.apache.kafka.common.utils.LogContext;
import org.apache.kafka.streams.errors.ProductionExceptionHandler;
import org.apache.kafka.streams.errors.ProductionExceptionHandler.ProductionExceptionHandlerResponse;
import org.apache.kafka.streams.errors.StreamsException;
import org.apache.kafka.streams.errors.TaskCorruptedException;
import org.apache.kafka.streams.errors.TaskMigratedException;
import org.apache.kafka.streams.processor.StreamPartitioner;
import org.apache.kafka.streams.processor.TaskId;
import org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl;
import org.apache.kafka.streams.processor.internals.metrics.TaskMetrics;
import org.apache.kafka.streams.processor.internals.metrics.TopicMetrics;
import org.slf4j.Logger;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.atomic.AtomicReference;
import static org.apache.kafka.streams.processor.internals.ClientUtils.producerRecordSizeInBytes;
public class RecordCollectorImpl implements RecordCollector {
private final static String SEND_EXCEPTION_MESSAGE = "Error encountered sending record to topic %s for task %s due to:%n%s";
private final Logger log;
private final TaskId taskId;
private final StreamsProducer streamsProducer;
private final ProductionExceptionHandler productionExceptionHandler;
private final boolean eosEnabled;
private final Map<TopicPartition, Long> offsets;
private final StreamsMetricsImpl streamsMetrics;
private final Sensor droppedRecordsSensor;
private final Map<String, Map<String, Sensor>> sinkNodeToProducedSensorByTopic = new HashMap<>();
private final AtomicReference<KafkaException> sendException = new AtomicReference<>(null);
/**
* @throws StreamsException fatal error that should cause the thread to die (from producer.initTxn)
*/
public RecordCollectorImpl(final LogContext logContext,
final TaskId taskId,
final StreamsProducer streamsProducer,
final ProductionExceptionHandler productionExceptionHandler,
final StreamsMetricsImpl streamsMetrics,
final ProcessorTopology topology) {
this.log = logContext.logger(getClass());
this.taskId = taskId;
this.streamsProducer = streamsProducer;
this.productionExceptionHandler = productionExceptionHandler;
this.eosEnabled = streamsProducer.eosEnabled();
this.streamsMetrics = streamsMetrics;
final String threadId = Thread.currentThread().getName();
this.droppedRecordsSensor = TaskMetrics.droppedRecordsSensor(threadId, taskId.toString(), streamsMetrics);
for (final String topic : topology.sinkTopics()) {
final String processorNodeId = topology.sink(topic).name();
sinkNodeToProducedSensorByTopic.computeIfAbsent(processorNodeId, t -> new HashMap<>()).put(
topic,
TopicMetrics.producedSensor(
threadId,
taskId.toString(),
processorNodeId,
topic,
streamsMetrics
));
}
this.offsets = new HashMap<>();
}
@Override
public void initialize() {
if (eosEnabled) {
streamsProducer.initTransaction();
}
}
/**
* @throws StreamsException fatal error that should cause the thread to die
* @throws TaskMigratedException recoverable error that would cause the task to be removed
*/
@Override
public <K, V> void send(final String topic,
final K key,
final V value,
final Headers headers,
final Long timestamp,
final Serializer<K> keySerializer,
final Serializer<V> valueSerializer,
final String processorNodeId,
final InternalProcessorContext<Void, Void> context,
final StreamPartitioner<? super K, ? super V> partitioner) {
final Integer partition;
if (partitioner != null) {
final List<PartitionInfo> partitions;
try {
partitions = streamsProducer.partitionsFor(topic);
} catch (final TimeoutException timeoutException) {
log.warn("Could not get partitions for topic {}, will retry", topic);
// re-throw to trigger `task.timeout.ms`
throw timeoutException;
} catch (final KafkaException fatal) {
// here we cannot drop the message on the floor even if it is a transient timeout exception,
// so we treat everything the same as a fatal exception
throw new StreamsException("Could not determine the number of partitions for topic '" + topic +
"' for task " + taskId + " due to " + fatal,
fatal
);
}
if (partitions.size() > 0) {
partition = partitioner.partition(topic, key, value, partitions.size());
} else {
throw new StreamsException("Could not get partition information for topic " + topic + " for task " + taskId +
". This can happen if the topic does not exist.");
}
} else {
partition = null;
}
send(topic, key, value, headers, partition, timestamp, keySerializer, valueSerializer, processorNodeId, context);
}
@Override
public <K, V> void send(final String topic,
final K key,
final V value,
final Headers headers,
final Integer partition,
final Long timestamp,
final Serializer<K> keySerializer,
final Serializer<V> valueSerializer,
final String processorNodeId,
final InternalProcessorContext<Void, Void> context) {
checkForException();
final byte[] keyBytes;
final byte[] valBytes;
try {
keyBytes = keySerializer.serialize(topic, headers, key);
valBytes = valueSerializer.serialize(topic, headers, value);
} catch (final ClassCastException exception) {
final String keyClass = key == null ? "unknown because key is null" : key.getClass().getName();
final String valueClass = value == null ? "unknown because value is null" : value.getClass().getName();
throw new StreamsException(
String.format(
"ClassCastException while producing data to topic %s. " +
"A serializer (key: %s / value: %s) is not compatible to the actual key or value type " +
"(key type: %s / value type: %s). " +
"Change the default Serdes in StreamConfig or provide correct Serdes via method parameters " +
"(for example if using the DSL, `#to(String topic, Produced<K, V> produced)` with " +
"`Produced.keySerde(WindowedSerdes.timeWindowedSerdeFrom(String.class))`).",
topic,
keySerializer.getClass().getName(),
valueSerializer.getClass().getName(),
keyClass,
valueClass),
exception);
} catch (final RuntimeException exception) {
final String errorMessage = String.format(SEND_EXCEPTION_MESSAGE, topic, taskId, exception);
throw new StreamsException(errorMessage, exception);
}
final ProducerRecord<byte[], byte[]> serializedRecord = new ProducerRecord<>(topic, partition, timestamp, keyBytes, valBytes, headers);
streamsProducer.send(serializedRecord, (metadata, exception) -> {
// if there's already an exception record, skip logging offsets or new exceptions
if (sendException.get() != null) {
return;
}
if (exception == null) {
final TopicPartition tp = new TopicPartition(metadata.topic(), metadata.partition());
if (metadata.offset() >= 0L) {
offsets.put(tp, metadata.offset());
} else {
log.warn("Received offset={} in produce response for {}", metadata.offset(), tp);
}
if (!topic.endsWith("-changelog")) {
final Map<String, Sensor> producedSensorByTopic = sinkNodeToProducedSensorByTopic.get(processorNodeId);
if (producedSensorByTopic == null) {
log.error("Unable to records bytes produced to topic {} by sink node {} as the node is not recognized.\n"
+ "Known sink nodes are {}.", topic, processorNodeId, sinkNodeToProducedSensorByTopic.keySet());
} else {
// we may not have created a sensor during initialization if the node uses dynamic topic routing,
// as all topics are not known up front, so create the sensor for that topic if absent
final Sensor topicProducedSensor = producedSensorByTopic.computeIfAbsent(
topic,
t -> TopicMetrics.producedSensor(
Thread.currentThread().getName(),
taskId.toString(),
processorNodeId,
topic,
context.metrics()
)
);
final long bytesProduced = producerRecordSizeInBytes(serializedRecord);
topicProducedSensor.record(bytesProduced, context.currentSystemTimeMs());
}
}
} else {
recordSendError(topic, exception, serializedRecord);
// KAFKA-7510 only put message key and value in TRACE level log so we don't leak data by default
log.trace("Failed record: (key {} value {} timestamp {}) topic=[{}] partition=[{}]", key, value, timestamp, topic, partition);
}
});
}
private void recordSendError(final String topic, final Exception exception, final ProducerRecord<byte[], byte[]> serializedRecord) {
String errorMessage = String.format(SEND_EXCEPTION_MESSAGE, topic, taskId, exception.toString());
if (isFatalException(exception)) {
errorMessage += "\nWritten offsets would not be recorded and no more records would be sent since this is a fatal error.";
sendException.set(new StreamsException(errorMessage, exception));
} else if (exception instanceof ProducerFencedException ||
exception instanceof InvalidProducerEpochException ||
exception instanceof OutOfOrderSequenceException) {
errorMessage += "\nWritten offsets would not be recorded and no more records would be sent since the producer is fenced, " +
"indicating the task may be migrated out";
sendException.set(new TaskMigratedException(errorMessage, exception));
} else {
if (exception instanceof RetriableException) {
errorMessage += "\nThe broker is either slow or in bad state (like not having enough replicas) in responding the request, " +
"or the connection to broker was interrupted sending the request or receiving the response. " +
"\nConsider overwriting `max.block.ms` and /or " +
"`delivery.timeout.ms` to a larger value to wait longer for such scenarios and avoid timeout errors";
sendException.set(new TaskCorruptedException(Collections.singleton(taskId)));
} else {
if (productionExceptionHandler.handle(serializedRecord, exception) == ProductionExceptionHandlerResponse.FAIL) {
errorMessage += "\nException handler choose to FAIL the processing, no more records would be sent.";
sendException.set(new StreamsException(errorMessage, exception));
} else {
errorMessage += "\nException handler choose to CONTINUE processing in spite of this error but written offsets would not be recorded.";
droppedRecordsSensor.record();
}
}
}
log.error(errorMessage, exception);
}
private boolean isFatalException(final Exception exception) {
final boolean securityException = exception instanceof AuthenticationException ||
exception instanceof AuthorizationException ||
exception instanceof SecurityDisabledException;
final boolean communicationException = exception instanceof InvalidTopicException ||
exception instanceof UnknownServerException ||
exception instanceof SerializationException ||
exception instanceof OffsetMetadataTooLarge ||
exception instanceof IllegalStateException;
return securityException || communicationException;
}
/**
* @throws StreamsException fatal error that should cause the thread to die
* @throws TaskMigratedException recoverable error that would cause the task to be removed
*/
@Override
public void flush() {
log.debug("Flushing record collector");
streamsProducer.flush();
checkForException();
}
/**
* @throws StreamsException fatal error that should cause the thread to die
* @throws TaskMigratedException recoverable error that would cause the task to be removed
*/
@Override
public void closeClean() {
log.info("Closing record collector clean");
removeAllProducedSensors();
// No need to abort transaction during a clean close: either we have successfully committed the ongoing
// transaction during handleRevocation and thus there is no transaction in flight, or else none of the revoked
// tasks had any data in the current transaction and therefore there is no need to commit or abort it.
checkForException();
}
/**
* @throws StreamsException fatal error that should cause the thread to die
* @throws TaskMigratedException recoverable error that would cause the task to be removed
*/
@Override
public void closeDirty() {
log.info("Closing record collector dirty");
if (eosEnabled) {
// We may be closing dirty because the commit failed, so we must abort the transaction to be safe
streamsProducer.abortTransaction();
}
checkForException();
}
private void removeAllProducedSensors() {
for (final Map<String, Sensor> nodeMap : sinkNodeToProducedSensorByTopic.values()) {
for (final Sensor sensor : nodeMap.values()) {
streamsMetrics.removeSensor(sensor);
}
}
}
@Override
public Map<TopicPartition, Long> offsets() {
return Collections.unmodifiableMap(new HashMap<>(offsets));
}
private void checkForException() {
final KafkaException exception = sendException.get();
if (exception != null) {
sendException.set(null);
throw exception;
}
}
// for testing only
Producer<byte[], byte[]> producer() {
return streamsProducer.kafkaProducer();
}
}
相关信息
相关文章
kafka AbstractProcessorContext 源码
kafka AbstractReadOnlyDecorator 源码
kafka AbstractReadWriteDecorator 源码
0
赞
热门推荐
-
2、 - 优质文章
-
3、 gate.io
-
7、 golang
-
9、 openharmony
-
10、 Vue中input框自动聚焦