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/*
* 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.clients.producer.internals;
import org.apache.kafka.clients.ApiVersions;
import org.apache.kafka.clients.ClientRequest;
import org.apache.kafka.clients.ClientResponse;
import org.apache.kafka.clients.KafkaClient;
import org.apache.kafka.clients.Metadata;
import org.apache.kafka.clients.NetworkClientUtils;
import org.apache.kafka.clients.RequestCompletionHandler;
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.InvalidRecordException;
import org.apache.kafka.common.KafkaException;
import org.apache.kafka.common.MetricName;
import org.apache.kafka.common.Node;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.errors.AuthenticationException;
import org.apache.kafka.common.errors.ClusterAuthorizationException;
import org.apache.kafka.common.errors.InvalidMetadataException;
import org.apache.kafka.common.errors.RetriableException;
import org.apache.kafka.common.errors.TimeoutException;
import org.apache.kafka.common.errors.TopicAuthorizationException;
import org.apache.kafka.common.errors.TransactionAbortedException;
import org.apache.kafka.common.errors.UnknownTopicOrPartitionException;
import org.apache.kafka.common.message.ProduceRequestData;
import org.apache.kafka.common.metrics.Sensor;
import org.apache.kafka.common.metrics.stats.Avg;
import org.apache.kafka.common.metrics.stats.Max;
import org.apache.kafka.common.metrics.stats.Meter;
import org.apache.kafka.common.protocol.Errors;
import org.apache.kafka.common.record.MemoryRecords;
import org.apache.kafka.common.record.RecordBatch;
import org.apache.kafka.common.requests.AbstractRequest;
import org.apache.kafka.common.requests.FindCoordinatorRequest;
import org.apache.kafka.common.requests.ProduceRequest;
import org.apache.kafka.common.requests.ProduceResponse;
import org.apache.kafka.common.requests.RequestHeader;
import org.apache.kafka.common.utils.LogContext;
import org.apache.kafka.common.utils.Time;
import org.slf4j.Logger;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.function.Function;
import java.util.stream.Collectors;
/**
* The background thread that handles the sending of produce requests to the Kafka cluster. This thread makes metadata
* requests to renew its view of the cluster and then sends produce requests to the appropriate nodes.
*/
public class Sender implements Runnable {
private final Logger log;
/* the state of each nodes connection */
private final KafkaClient client;
/* the record accumulator that batches records */
private final RecordAccumulator accumulator;
/* the metadata for the client */
private final ProducerMetadata metadata;
/* the flag indicating whether the producer should guarantee the message order on the broker or not. */
private final boolean guaranteeMessageOrder;
/* the maximum request size to attempt to send to the server */
private final int maxRequestSize;
/* the number of acknowledgements to request from the server */
private final short acks;
/* the number of times to retry a failed request before giving up */
private final int retries;
/* the clock instance used for getting the time */
private final Time time;
/* true while the sender thread is still running */
private volatile boolean running;
/* true when the caller wants to ignore all unsent/inflight messages and force close. */
private volatile boolean forceClose;
/* metrics */
private final SenderMetrics sensors;
/* the max time to wait for the server to respond to the request*/
private final int requestTimeoutMs;
/* The max time to wait before retrying a request which has failed */
private final long retryBackoffMs;
/* current request API versions supported by the known brokers */
private final ApiVersions apiVersions;
/* all the state related to transactions, in particular the producer id, producer epoch, and sequence numbers */
private final TransactionManager transactionManager;
// A per-partition queue of batches ordered by creation time for tracking the in-flight batches
private final Map> inFlightBatches;
public Sender(LogContext logContext,
KafkaClient client,
ProducerMetadata metadata,
RecordAccumulator accumulator,
boolean guaranteeMessageOrder,
int maxRequestSize,
short acks,
int retries,
SenderMetricsRegistry metricsRegistry,
Time time,
int requestTimeoutMs,
long retryBackoffMs,
TransactionManager transactionManager,
ApiVersions apiVersions) {
this.log = logContext.logger(Sender.class);
this.client = client;
this.accumulator = accumulator;
this.metadata = metadata;
this.guaranteeMessageOrder = guaranteeMessageOrder;
this.maxRequestSize = maxRequestSize;
this.running = true;
this.acks = acks;
this.retries = retries;
this.time = time;
this.sensors = new SenderMetrics(metricsRegistry, metadata, client, time);
this.requestTimeoutMs = requestTimeoutMs;
this.retryBackoffMs = retryBackoffMs;
this.apiVersions = apiVersions;
this.transactionManager = transactionManager;
this.inFlightBatches = new HashMap<>();
}
public List inFlightBatches(TopicPartition tp) {
return inFlightBatches.containsKey(tp) ? inFlightBatches.get(tp) : new ArrayList<>();
}
private void maybeRemoveFromInflightBatches(ProducerBatch batch) {
List batches = inFlightBatches.get(batch.topicPartition);
if (batches != null) {
batches.remove(batch);
if (batches.isEmpty()) {
inFlightBatches.remove(batch.topicPartition);
}
}
}
private void maybeRemoveAndDeallocateBatch(ProducerBatch batch) {
maybeRemoveFromInflightBatches(batch);
this.accumulator.deallocate(batch);
}
/**
* Get the in-flight batches that has reached delivery timeout.
*/
private List getExpiredInflightBatches(long now) {
List expiredBatches = new ArrayList<>();
for (Iterator>> batchIt = inFlightBatches.entrySet().iterator(); batchIt.hasNext();) {
Map.Entry> entry = batchIt.next();
List partitionInFlightBatches = entry.getValue();
if (partitionInFlightBatches != null) {
Iterator iter = partitionInFlightBatches.iterator();
while (iter.hasNext()) {
ProducerBatch batch = iter.next();
if (batch.hasReachedDeliveryTimeout(accumulator.getDeliveryTimeoutMs(), now)) {
iter.remove();
// expireBatches is called in Sender.sendProducerData, before client.poll.
// The !batch.isDone() invariant should always hold. An IllegalStateException
// exception will be thrown if the invariant is violated.
if (!batch.isDone()) {
expiredBatches.add(batch);
} else {
throw new IllegalStateException(batch.topicPartition + " batch created at " +
batch.createdMs + " gets unexpected final state " + batch.finalState());
}
} else {
accumulator.maybeUpdateNextBatchExpiryTime(batch);
break;
}
}
if (partitionInFlightBatches.isEmpty()) {
batchIt.remove();
}
}
}
return expiredBatches;
}
private void addToInflightBatches(List batches) {
for (ProducerBatch batch : batches) {
List inflightBatchList = inFlightBatches.get(batch.topicPartition);
if (inflightBatchList == null) {
inflightBatchList = new ArrayList<>();
inFlightBatches.put(batch.topicPartition, inflightBatchList);
}
inflightBatchList.add(batch);
}
}
public void addToInflightBatches(Map> batches) {
for (List batchList : batches.values()) {
addToInflightBatches(batchList);
}
}
private boolean hasPendingTransactionalRequests() {
return transactionManager != null && transactionManager.hasPendingRequests() && transactionManager.hasOngoingTransaction();
}
/**
* The main run loop for the sender thread
*/
@Override
public void run() {
log.debug("Starting Kafka producer I/O thread.");
// main loop, runs until close is called
while (running) {
try {
runOnce();
} catch (Exception e) {
log.error("Uncaught error in kafka producer I/O thread: ", e);
}
}
log.debug("Beginning shutdown of Kafka producer I/O thread, sending remaining records.");
// okay we stopped accepting requests but there may still be
// requests in the transaction manager, accumulator or waiting for acknowledgment,
// wait until these are completed.
while (!forceClose && ((this.accumulator.hasUndrained() || this.client.inFlightRequestCount() > 0) || hasPendingTransactionalRequests())) {
try {
runOnce();
} catch (Exception e) {
log.error("Uncaught error in kafka producer I/O thread: ", e);
}
}
// Abort the transaction if any commit or abort didn't go through the transaction manager's queue
while (!forceClose && transactionManager != null && transactionManager.hasOngoingTransaction()) {
if (!transactionManager.isCompleting()) {
log.info("Aborting incomplete transaction due to shutdown");
transactionManager.beginAbort();
}
try {
runOnce();
} catch (Exception e) {
log.error("Uncaught error in kafka producer I/O thread: ", e);
}
}
if (forceClose) {
// We need to fail all the incomplete transactional requests and batches and wake up the threads waiting on
// the futures.
if (transactionManager != null) {
log.debug("Aborting incomplete transactional requests due to forced shutdown");
transactionManager.close();
}
log.debug("Aborting incomplete batches due to forced shutdown");
this.accumulator.abortIncompleteBatches();
}
try {
this.client.close();
} catch (Exception e) {
log.error("Failed to close network client", e);
}
log.debug("Shutdown of Kafka producer I/O thread has completed.");
}
/**
* Run a single iteration of sending
*
*/
void runOnce() {
if (transactionManager != null) {
try {
transactionManager.maybeResolveSequences();
// do not continue sending if the transaction manager is in a failed state
if (transactionManager.hasFatalError()) {
RuntimeException lastError = transactionManager.lastError();
if (lastError != null)
maybeAbortBatches(lastError);
client.poll(retryBackoffMs, time.milliseconds());
return;
}
// Check whether we need a new producerId. If so, we will enqueue an InitProducerId
// request which will be sent below
transactionManager.bumpIdempotentEpochAndResetIdIfNeeded();
if (maybeSendAndPollTransactionalRequest()) {
return;
}
} catch (AuthenticationException e) {
// This is already logged as error, but propagated here to perform any clean ups.
log.trace("Authentication exception while processing transactional request", e);
transactionManager.authenticationFailed(e);
}
}
long currentTimeMs = time.milliseconds();
long pollTimeout = sendProducerData(currentTimeMs);
client.poll(pollTimeout, currentTimeMs);
}
private long sendProducerData(long now) {
Cluster cluster = metadata.fetch();
// get the list of partitions with data ready to send
RecordAccumulator.ReadyCheckResult result = this.accumulator.ready(cluster, now);
// if there are any partitions whose leaders are not known yet, force metadata update
if (!result.unknownLeaderTopics.isEmpty()) {
// The set of topics with unknown leader contains topics with leader election pending as well as
// topics which may have expired. Add the topic again to metadata to ensure it is included
// and request metadata update, since there are messages to send to the topic.
for (String topic : result.unknownLeaderTopics)
this.metadata.add(topic, now);
log.debug("Requesting metadata update due to unknown leader topics from the batched records: {}",
result.unknownLeaderTopics);
this.metadata.requestUpdate();
}
// remove any nodes we aren't ready to send to
Iterator iter = result.readyNodes.iterator();
long notReadyTimeout = Long.MAX_VALUE;
while (iter.hasNext()) {
Node node = iter.next();
if (!this.client.ready(node, now)) {
// Update just the readyTimeMs of the latency stats, so that it moves forward
// every time the batch is ready (then the difference between readyTimeMs and
// drainTimeMs would represent how long data is waiting for the node).
this.accumulator.updateNodeLatencyStats(node.id(), now, false);
iter.remove();
notReadyTimeout = Math.min(notReadyTimeout, this.client.pollDelayMs(node, now));
} else {
// Update both readyTimeMs and drainTimeMs, this would "reset" the node
// latency.
this.accumulator.updateNodeLatencyStats(node.id(), now, true);
}
}
// create produce requests
Map> batches = this.accumulator.drain(cluster, result.readyNodes, this.maxRequestSize, now);
addToInflightBatches(batches);
if (guaranteeMessageOrder) {
// Mute all the partitions drained
for (List batchList : batches.values()) {
for (ProducerBatch batch : batchList)
this.accumulator.mutePartition(batch.topicPartition);
}
}
accumulator.resetNextBatchExpiryTime();
List expiredInflightBatches = getExpiredInflightBatches(now);
List expiredBatches = this.accumulator.expiredBatches(now);
expiredBatches.addAll(expiredInflightBatches);
// Reset the producer id if an expired batch has previously been sent to the broker. Also update the metrics
// for expired batches. see the documentation of @TransactionState.resetIdempotentProducerId to understand why
// we need to reset the producer id here.
if (!expiredBatches.isEmpty())
log.trace("Expired {} batches in accumulator", expiredBatches.size());
for (ProducerBatch expiredBatch : expiredBatches) {
String errorMessage = "Expiring " + expiredBatch.recordCount + " record(s) for " + expiredBatch.topicPartition
+ ":" + (now - expiredBatch.createdMs) + " ms has passed since batch creation";
failBatch(expiredBatch, new TimeoutException(errorMessage), false);
if (transactionManager != null && expiredBatch.inRetry()) {
// This ensures that no new batches are drained until the current in flight batches are fully resolved.
transactionManager.markSequenceUnresolved(expiredBatch);
}
}
sensors.updateProduceRequestMetrics(batches);
// If we have any nodes that are ready to send + have sendable data, poll with 0 timeout so this can immediately
// loop and try sending more data. Otherwise, the timeout will be the smaller value between next batch expiry
// time, and the delay time for checking data availability. Note that the nodes may have data that isn't yet
// sendable due to lingering, backing off, etc. This specifically does not include nodes with sendable data
// that aren't ready to send since they would cause busy looping.
long pollTimeout = Math.min(result.nextReadyCheckDelayMs, notReadyTimeout);
pollTimeout = Math.min(pollTimeout, this.accumulator.nextExpiryTimeMs() - now);
pollTimeout = Math.max(pollTimeout, 0);
if (!result.readyNodes.isEmpty()) {
log.trace("Nodes with data ready to send: {}", result.readyNodes);
// if some partitions are already ready to be sent, the select time would be 0;
// otherwise if some partition already has some data accumulated but not ready yet,
// the select time will be the time difference between now and its linger expiry time;
// otherwise the select time will be the time difference between now and the metadata expiry time;
pollTimeout = 0;
}
sendProduceRequests(batches, now);
return pollTimeout;
}
/**
* Returns true if a transactional request is sent or polled, or if a FindCoordinator request is enqueued
*/
private boolean maybeSendAndPollTransactionalRequest() {
if (transactionManager.hasInFlightRequest()) {
// as long as there are outstanding transactional requests, we simply wait for them to return
client.poll(retryBackoffMs, time.milliseconds());
return true;
}
if (transactionManager.hasAbortableError() || transactionManager.isAborting()) {
if (accumulator.hasIncomplete()) {
// Attempt to get the last error that caused this abort.
RuntimeException exception = transactionManager.lastError();
// If there was no error, but we are still aborting,
// then this is most likely a case where there was no fatal error.
if (exception == null) {
exception = new TransactionAbortedException();
}
accumulator.abortUndrainedBatches(exception);
}
}
TransactionManager.TxnRequestHandler nextRequestHandler = transactionManager.nextRequest(accumulator.hasIncomplete());
if (nextRequestHandler == null)
return false;
AbstractRequest.Builder requestBuilder = nextRequestHandler.requestBuilder();
Node targetNode = null;
try {
FindCoordinatorRequest.CoordinatorType coordinatorType = nextRequestHandler.coordinatorType();
targetNode = coordinatorType != null ?
transactionManager.coordinator(coordinatorType) :
client.leastLoadedNode(time.milliseconds());
if (targetNode != null) {
if (!awaitNodeReady(targetNode, coordinatorType)) {
log.trace("Target node {} not ready within request timeout, will retry when node is ready.", targetNode);
maybeFindCoordinatorAndRetry(nextRequestHandler);
return true;
}
} else if (coordinatorType != null) {
log.trace("Coordinator not known for {}, will retry {} after finding coordinator.", coordinatorType, requestBuilder.apiKey());
maybeFindCoordinatorAndRetry(nextRequestHandler);
return true;
} else {
log.trace("No nodes available to send requests, will poll and retry when until a node is ready.");
transactionManager.retry(nextRequestHandler);
client.poll(retryBackoffMs, time.milliseconds());
return true;
}
if (nextRequestHandler.isRetry())
time.sleep(nextRequestHandler.retryBackoffMs());
long currentTimeMs = time.milliseconds();
ClientRequest clientRequest = client.newClientRequest(targetNode.idString(), requestBuilder, currentTimeMs,
true, requestTimeoutMs, nextRequestHandler);
log.debug("Sending transactional request {} to node {} with correlation ID {}", requestBuilder, targetNode, clientRequest.correlationId());
client.send(clientRequest, currentTimeMs);
transactionManager.setInFlightCorrelationId(clientRequest.correlationId());
client.poll(retryBackoffMs, time.milliseconds());
return true;
} catch (IOException e) {
log.debug("Disconnect from {} while trying to send request {}. Going " +
"to back off and retry.", targetNode, requestBuilder, e);
// We break here so that we pick up the FindCoordinator request immediately.
maybeFindCoordinatorAndRetry(nextRequestHandler);
return true;
}
}
private void maybeFindCoordinatorAndRetry(TransactionManager.TxnRequestHandler nextRequestHandler) {
if (nextRequestHandler.needsCoordinator()) {
transactionManager.lookupCoordinator(nextRequestHandler);
} else {
// For non-coordinator requests, sleep here to prevent a tight loop when no node is available
time.sleep(retryBackoffMs);
metadata.requestUpdate();
}
transactionManager.retry(nextRequestHandler);
}
private void maybeAbortBatches(RuntimeException exception) {
if (accumulator.hasIncomplete()) {
log.error("Aborting producer batches due to fatal error", exception);
accumulator.abortBatches(exception);
}
}
/**
* Start closing the sender (won't actually complete until all data is sent out)
*/
public void initiateClose() {
// Ensure accumulator is closed first to guarantee that no more appends are accepted after
// breaking from the sender loop. Otherwise, we may miss some callbacks when shutting down.
this.accumulator.close();
this.running = false;
this.wakeup();
}
/**
* Closes the sender without sending out any pending messages.
*/
public void forceClose() {
this.forceClose = true;
initiateClose();
}
public boolean isRunning() {
return running;
}
private boolean awaitNodeReady(Node node, FindCoordinatorRequest.CoordinatorType coordinatorType) throws IOException {
if (NetworkClientUtils.awaitReady(client, node, time, requestTimeoutMs)) {
if (coordinatorType == FindCoordinatorRequest.CoordinatorType.TRANSACTION) {
// Indicate to the transaction manager that the coordinator is ready, allowing it to check ApiVersions
// This allows us to bump transactional epochs even if the coordinator is temporarily unavailable at
// the time when the abortable error is handled
transactionManager.handleCoordinatorReady();
}
return true;
}
return false;
}
/**
* Handle a produce response
*/
private void handleProduceResponse(ClientResponse response, Map batches, long now) {
RequestHeader requestHeader = response.requestHeader();
int correlationId = requestHeader.correlationId();
if (response.wasDisconnected()) {
log.trace("Cancelled request with header {} due to node {} being disconnected",
requestHeader, response.destination());
for (ProducerBatch batch : batches.values())
completeBatch(batch, new ProduceResponse.PartitionResponse(Errors.NETWORK_EXCEPTION, String.format("Disconnected from node %s", response.destination())),
correlationId, now);
} else if (response.versionMismatch() != null) {
log.warn("Cancelled request {} due to a version mismatch with node {}",
response, response.destination(), response.versionMismatch());
for (ProducerBatch batch : batches.values())
completeBatch(batch, new ProduceResponse.PartitionResponse(Errors.UNSUPPORTED_VERSION), correlationId, now);
} else {
log.trace("Received produce response from node {} with correlation id {}", response.destination(), correlationId);
// if we have a response, parse it
if (response.hasResponse()) {
// Sender should exercise PartitionProduceResponse rather than ProduceResponse.PartitionResponse
// https://issues.apache.org/jira/browse/KAFKA-10696
ProduceResponse produceResponse = (ProduceResponse) response.responseBody();
produceResponse.data().responses().forEach(r -> r.partitionResponses().forEach(p -> {
TopicPartition tp = new TopicPartition(r.name(), p.index());
ProduceResponse.PartitionResponse partResp = new ProduceResponse.PartitionResponse(
Errors.forCode(p.errorCode()),
p.baseOffset(),
p.logAppendTimeMs(),
p.logStartOffset(),
p.recordErrors()
.stream()
.map(e -> new ProduceResponse.RecordError(e.batchIndex(), e.batchIndexErrorMessage()))
.collect(Collectors.toList()),
p.errorMessage());
ProducerBatch batch = batches.get(tp);
completeBatch(batch, partResp, correlationId, now);
}));
this.sensors.recordLatency(response.destination(), response.requestLatencyMs());
} else {
// this is the acks = 0 case, just complete all requests
for (ProducerBatch batch : batches.values()) {
completeBatch(batch, new ProduceResponse.PartitionResponse(Errors.NONE), correlationId, now);
}
}
}
}
/**
* Complete or retry the given batch of records.
*
* @param batch The record batch
* @param response The produce response
* @param correlationId The correlation id for the request
* @param now The current POSIX timestamp in milliseconds
*/
private void completeBatch(ProducerBatch batch, ProduceResponse.PartitionResponse response, long correlationId,
long now) {
Errors error = response.error;
if (error == Errors.MESSAGE_TOO_LARGE && batch.recordCount > 1 && !batch.isDone() &&
(batch.magic() >= RecordBatch.MAGIC_VALUE_V2 || batch.isCompressed())) {
// If the batch is too large, we split the batch and send the split batches again. We do not decrement
// the retry attempts in this case.
log.warn(
"Got error produce response in correlation id {} on topic-partition {}, splitting and retrying ({} attempts left). Error: {}",
correlationId,
batch.topicPartition,
this.retries - batch.attempts(),
formatErrMsg(response));
if (transactionManager != null)
transactionManager.removeInFlightBatch(batch);
this.accumulator.splitAndReenqueue(batch);
maybeRemoveAndDeallocateBatch(batch);
this.sensors.recordBatchSplit();
} else if (error != Errors.NONE) {
if (canRetry(batch, response, now)) {
log.warn(
"Got error produce response with correlation id {} on topic-partition {}, retrying ({} attempts left). Error: {}",
correlationId,
batch.topicPartition,
this.retries - batch.attempts() - 1,
formatErrMsg(response));
reenqueueBatch(batch, now);
} else if (error == Errors.DUPLICATE_SEQUENCE_NUMBER) {
// If we have received a duplicate sequence error, it means that the sequence number has advanced beyond
// the sequence of the current batch, and we haven't retained batch metadata on the broker to return
// the correct offset and timestamp.
//
// The only thing we can do is to return success to the user and not return a valid offset and timestamp.
completeBatch(batch, response);
} else {
// tell the user the result of their request. We only adjust sequence numbers if the batch didn't exhaust
// its retries -- if it did, we don't know whether the sequence number was accepted or not, and
// thus it is not safe to reassign the sequence.
failBatch(batch, response, batch.attempts() < this.retries);
}
if (error.exception() instanceof InvalidMetadataException) {
if (error.exception() instanceof UnknownTopicOrPartitionException) {
log.warn("Received unknown topic or partition error in produce request on partition {}. The " +
"topic-partition may not exist or the user may not have Describe access to it",
batch.topicPartition);
} else {
log.warn("Received invalid metadata error in produce request on partition {} due to {}. Going " +
"to request metadata update now", batch.topicPartition,
error.exception(response.errorMessage).toString());
}
metadata.requestUpdate();
}
} else {
completeBatch(batch, response);
}
// Unmute the completed partition.
if (guaranteeMessageOrder)
this.accumulator.unmutePartition(batch.topicPartition);
}
/**
* Format the error from a {@link ProduceResponse.PartitionResponse} in a user-friendly string
* e.g "NETWORK_EXCEPTION. Error Message: Disconnected from node 0"
*/
private String formatErrMsg(ProduceResponse.PartitionResponse response) {
String errorMessageSuffix = (response.errorMessage == null || response.errorMessage.isEmpty()) ?
"" : String.format(". Error Message: %s", response.errorMessage);
return String.format("%s%s", response.error, errorMessageSuffix);
}
private void reenqueueBatch(ProducerBatch batch, long currentTimeMs) {
this.accumulator.reenqueue(batch, currentTimeMs);
maybeRemoveFromInflightBatches(batch);
this.sensors.recordRetries(batch.topicPartition.topic(), batch.recordCount);
}
private void completeBatch(ProducerBatch batch, ProduceResponse.PartitionResponse response) {
if (transactionManager != null) {
transactionManager.handleCompletedBatch(batch, response);
}
if (batch.complete(response.baseOffset, response.logAppendTime)) {
maybeRemoveAndDeallocateBatch(batch);
}
}
private void failBatch(ProducerBatch batch,
ProduceResponse.PartitionResponse response,
boolean adjustSequenceNumbers) {
final RuntimeException topLevelException;
if (response.error == Errors.TOPIC_AUTHORIZATION_FAILED)
topLevelException = new TopicAuthorizationException(Collections.singleton(batch.topicPartition.topic()));
else if (response.error == Errors.CLUSTER_AUTHORIZATION_FAILED)
topLevelException = new ClusterAuthorizationException("The producer is not authorized to do idempotent sends");
else
topLevelException = response.error.exception(response.errorMessage);
if (response.recordErrors == null || response.recordErrors.isEmpty()) {
failBatch(batch, topLevelException, adjustSequenceNumbers);
} else {
Map recordErrorMap = new HashMap<>(response.recordErrors.size());
for (ProduceResponse.RecordError recordError : response.recordErrors) {
// The API leaves us with some awkwardness interpreting the errors in the response.
// We cannot differentiate between different error cases (such as INVALID_TIMESTAMP)
// from the single error code at the partition level, so instead we use INVALID_RECORD
// for all failed records and rely on the message to distinguish the cases.
final String errorMessage;
if (recordError.message != null) {
errorMessage = recordError.message;
} else if (response.errorMessage != null) {
errorMessage = response.errorMessage;
} else {
errorMessage = response.error.message();
}
// If the batch contained only a single record error, then we can unambiguously
// use the exception type corresponding to the partition-level error code.
if (response.recordErrors.size() == 1) {
recordErrorMap.put(recordError.batchIndex, response.error.exception(errorMessage));
} else {
recordErrorMap.put(recordError.batchIndex, new InvalidRecordException(errorMessage));
}
}
Function recordExceptions = batchIndex -> {
RuntimeException exception = recordErrorMap.get(batchIndex);
if (exception != null) {
return exception;
} else {
// If the response contains record errors, then the records which failed validation
// will be present in the response. To avoid confusion for the remaining records, we
// return a generic exception.
return new KafkaException("Failed to append record because it was part of a batch " +
"which had one more more invalid records");
}
};
failBatch(batch, topLevelException, recordExceptions, adjustSequenceNumbers);
}
}
private void failBatch(
ProducerBatch batch,
RuntimeException topLevelException,
boolean adjustSequenceNumbers
) {
failBatch(batch, topLevelException, batchIndex -> topLevelException, adjustSequenceNumbers);
}
private void failBatch(
ProducerBatch batch,
RuntimeException topLevelException,
Function recordExceptions,
boolean adjustSequenceNumbers
) {
if (transactionManager != null) {
transactionManager.handleFailedBatch(batch, topLevelException, adjustSequenceNumbers);
}
this.sensors.recordErrors(batch.topicPartition.topic(), batch.recordCount);
if (batch.completeExceptionally(topLevelException, recordExceptions)) {
maybeRemoveAndDeallocateBatch(batch);
}
}
/**
* We can retry a send if the error is transient and the number of attempts taken is fewer than the maximum allowed.
* We can also retry OutOfOrderSequence exceptions for future batches, since if the first batch has failed, the
* future batches are certain to fail with an OutOfOrderSequence exception.
*/
private boolean canRetry(ProducerBatch batch, ProduceResponse.PartitionResponse response, long now) {
return !batch.hasReachedDeliveryTimeout(accumulator.getDeliveryTimeoutMs(), now) &&
batch.attempts() < this.retries &&
!batch.isDone() &&
(transactionManager == null ?
response.error.exception() instanceof RetriableException :
transactionManager.canRetry(response, batch));
}
/**
* Transfer the record batches into a list of produce requests on a per-node basis
*/
private void sendProduceRequests(Map> collated, long now) {
for (Map.Entry> entry : collated.entrySet())
sendProduceRequest(now, entry.getKey(), acks, requestTimeoutMs, entry.getValue());
}
/**
* Create a produce request from the given record batches
*/
private void sendProduceRequest(long now, int destination, short acks, int timeout, List batches) {
if (batches.isEmpty())
return;
final Map recordsByPartition = new HashMap<>(batches.size());
// find the minimum magic version used when creating the record sets
byte minUsedMagic = apiVersions.maxUsableProduceMagic();
for (ProducerBatch batch : batches) {
if (batch.magic() < minUsedMagic)
minUsedMagic = batch.magic();
}
ProduceRequestData.TopicProduceDataCollection tpd = new ProduceRequestData.TopicProduceDataCollection();
for (ProducerBatch batch : batches) {
TopicPartition tp = batch.topicPartition;
MemoryRecords records = batch.records();
// down convert if necessary to the minimum magic used. In general, there can be a delay between the time
// that the producer starts building the batch and the time that we send the request, and we may have
// chosen the message format based on out-dated metadata. In the worst case, we optimistically chose to use
// the new message format, but found that the broker didn't support it, so we need to down-convert on the
// client before sending. This is intended to handle edge cases around cluster upgrades where brokers may
// not all support the same message format version. For example, if a partition migrates from a broker
// which is supporting the new magic version to one which doesn't, then we will need to convert.
if (!records.hasMatchingMagic(minUsedMagic))
records = batch.records().downConvert(minUsedMagic, 0, time).records();
ProduceRequestData.TopicProduceData tpData = tpd.find(tp.topic());
if (tpData == null) {
tpData = new ProduceRequestData.TopicProduceData().setName(tp.topic());
tpd.add(tpData);
}
tpData.partitionData().add(new ProduceRequestData.PartitionProduceData()
.setIndex(tp.partition())
.setRecords(records));
recordsByPartition.put(tp, batch);
}
String transactionalId = null;
if (transactionManager != null && transactionManager.isTransactional()) {
transactionalId = transactionManager.transactionalId();
}
ProduceRequest.Builder requestBuilder = ProduceRequest.forMagic(minUsedMagic,
new ProduceRequestData()
.setAcks(acks)
.setTimeoutMs(timeout)
.setTransactionalId(transactionalId)
.setTopicData(tpd));
RequestCompletionHandler callback = response -> handleProduceResponse(response, recordsByPartition, time.milliseconds());
String nodeId = Integer.toString(destination);
ClientRequest clientRequest = client.newClientRequest(nodeId, requestBuilder, now, acks != 0,
requestTimeoutMs, callback);
client.send(clientRequest, now);
log.trace("Sent produce request to {}: {}", nodeId, requestBuilder);
}
/**
* Wake up the selector associated with this send thread
*/
public void wakeup() {
this.client.wakeup();
}
public static Sensor throttleTimeSensor(SenderMetricsRegistry metrics) {
Sensor produceThrottleTimeSensor = metrics.sensor("produce-throttle-time");
produceThrottleTimeSensor.add(metrics.produceThrottleTimeAvg, new Avg());
produceThrottleTimeSensor.add(metrics.produceThrottleTimeMax, new Max());
return produceThrottleTimeSensor;
}
/**
* A collection of sensors for the sender
*/
private static class SenderMetrics {
public final Sensor retrySensor;
public final Sensor errorSensor;
public final Sensor queueTimeSensor;
public final Sensor requestTimeSensor;
public final Sensor recordsPerRequestSensor;
public final Sensor batchSizeSensor;
public final Sensor compressionRateSensor;
public final Sensor maxRecordSizeSensor;
public final Sensor batchSplitSensor;
private final SenderMetricsRegistry metrics;
private final Time time;
public SenderMetrics(SenderMetricsRegistry metrics, Metadata metadata, KafkaClient client, Time time) {
this.metrics = metrics;
this.time = time;
this.batchSizeSensor = metrics.sensor("batch-size");
this.batchSizeSensor.add(metrics.batchSizeAvg, new Avg());
this.batchSizeSensor.add(metrics.batchSizeMax, new Max());
this.compressionRateSensor = metrics.sensor("compression-rate");
this.compressionRateSensor.add(metrics.compressionRateAvg, new Avg());
this.queueTimeSensor = metrics.sensor("queue-time");
this.queueTimeSensor.add(metrics.recordQueueTimeAvg, new Avg());
this.queueTimeSensor.add(metrics.recordQueueTimeMax, new Max());
this.requestTimeSensor = metrics.sensor("request-time");
this.requestTimeSensor.add(metrics.requestLatencyAvg, new Avg());
this.requestTimeSensor.add(metrics.requestLatencyMax, new Max());
this.recordsPerRequestSensor = metrics.sensor("records-per-request");
this.recordsPerRequestSensor.add(new Meter(metrics.recordSendRate, metrics.recordSendTotal));
this.recordsPerRequestSensor.add(metrics.recordsPerRequestAvg, new Avg());
this.retrySensor = metrics.sensor("record-retries");
this.retrySensor.add(new Meter(metrics.recordRetryRate, metrics.recordRetryTotal));
this.errorSensor = metrics.sensor("errors");
this.errorSensor.add(new Meter(metrics.recordErrorRate, metrics.recordErrorTotal));
this.maxRecordSizeSensor = metrics.sensor("record-size");
this.maxRecordSizeSensor.add(metrics.recordSizeMax, new Max());
this.maxRecordSizeSensor.add(metrics.recordSizeAvg, new Avg());
this.metrics.addMetric(metrics.requestsInFlight, (config, now) -> client.inFlightRequestCount());
this.metrics.addMetric(metrics.metadataAge,
(config, now) -> (now - metadata.lastSuccessfulUpdate()) / 1000.0);
this.batchSplitSensor = metrics.sensor("batch-split-rate");
this.batchSplitSensor.add(new Meter(metrics.batchSplitRate, metrics.batchSplitTotal));
}
private void maybeRegisterTopicMetrics(String topic) {
// if one sensor of the metrics has been registered for the topic,
// then all other sensors should have been registered; and vice versa
String topicRecordsCountName = "topic." + topic + ".records-per-batch";
Sensor topicRecordCount = this.metrics.getSensor(topicRecordsCountName);
if (topicRecordCount == null) {
Map metricTags = Collections.singletonMap("topic", topic);
topicRecordCount = this.metrics.sensor(topicRecordsCountName);
MetricName rateMetricName = this.metrics.topicRecordSendRate(metricTags);
MetricName totalMetricName = this.metrics.topicRecordSendTotal(metricTags);
topicRecordCount.add(new Meter(rateMetricName, totalMetricName));
String topicByteRateName = "topic." + topic + ".bytes";
Sensor topicByteRate = this.metrics.sensor(topicByteRateName);
rateMetricName = this.metrics.topicByteRate(metricTags);
totalMetricName = this.metrics.topicByteTotal(metricTags);
topicByteRate.add(new Meter(rateMetricName, totalMetricName));
String topicCompressionRateName = "topic." + topic + ".compression-rate";
Sensor topicCompressionRate = this.metrics.sensor(topicCompressionRateName);
MetricName m = this.metrics.topicCompressionRate(metricTags);
topicCompressionRate.add(m, new Avg());
String topicRetryName = "topic." + topic + ".record-retries";
Sensor topicRetrySensor = this.metrics.sensor(topicRetryName);
rateMetricName = this.metrics.topicRecordRetryRate(metricTags);
totalMetricName = this.metrics.topicRecordRetryTotal(metricTags);
topicRetrySensor.add(new Meter(rateMetricName, totalMetricName));
String topicErrorName = "topic." + topic + ".record-errors";
Sensor topicErrorSensor = this.metrics.sensor(topicErrorName);
rateMetricName = this.metrics.topicRecordErrorRate(metricTags);
totalMetricName = this.metrics.topicRecordErrorTotal(metricTags);
topicErrorSensor.add(new Meter(rateMetricName, totalMetricName));
}
}
public void updateProduceRequestMetrics(Map> batches) {
long now = time.milliseconds();
for (List nodeBatch : batches.values()) {
int records = 0;
for (ProducerBatch batch : nodeBatch) {
// register all per-topic metrics at once
String topic = batch.topicPartition.topic();
maybeRegisterTopicMetrics(topic);
// per-topic record send rate
String topicRecordsCountName = "topic." + topic + ".records-per-batch";
Sensor topicRecordCount = Objects.requireNonNull(this.metrics.getSensor(topicRecordsCountName));
topicRecordCount.record(batch.recordCount);
// per-topic bytes send rate
String topicByteRateName = "topic." + topic + ".bytes";
Sensor topicByteRate = Objects.requireNonNull(this.metrics.getSensor(topicByteRateName));
topicByteRate.record(batch.estimatedSizeInBytes());
// per-topic compression rate
String topicCompressionRateName = "topic." + topic + ".compression-rate";
Sensor topicCompressionRate = Objects.requireNonNull(this.metrics.getSensor(topicCompressionRateName));
topicCompressionRate.record(batch.compressionRatio());
// global metrics
this.batchSizeSensor.record(batch.estimatedSizeInBytes(), now);
this.queueTimeSensor.record(batch.queueTimeMs(), now);
this.compressionRateSensor.record(batch.compressionRatio());
this.maxRecordSizeSensor.record(batch.maxRecordSize, now);
records += batch.recordCount;
}
this.recordsPerRequestSensor.record(records, now);
}
}
public void recordRetries(String topic, int count) {
long now = time.milliseconds();
this.retrySensor.record(count, now);
String topicRetryName = "topic." + topic + ".record-retries";
Sensor topicRetrySensor = this.metrics.getSensor(topicRetryName);
if (topicRetrySensor != null)
topicRetrySensor.record(count, now);
}
public void recordErrors(String topic, int count) {
long now = time.milliseconds();
this.errorSensor.record(count, now);
String topicErrorName = "topic." + topic + ".record-errors";
Sensor topicErrorSensor = this.metrics.getSensor(topicErrorName);
if (topicErrorSensor != null)
topicErrorSensor.record(count, now);
}
public void recordLatency(String node, long latency) {
long now = time.milliseconds();
this.requestTimeSensor.record(latency, now);
if (!node.isEmpty()) {
String nodeTimeName = "node-" + node + ".latency";
Sensor nodeRequestTime = this.metrics.getSensor(nodeTimeName);
if (nodeRequestTime != null)
nodeRequestTime.record(latency, now);
}
}
void recordBatchSplit() {
this.batchSplitSensor.record();
}
}
}
