kafka AbstractFetcherThread 源码
kafka AbstractFetcherThread 代码
文件路径：/core/src/main/scala/kafka/server/AbstractFetcherThread.scala
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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 kafka.server
import kafka.common.ClientIdAndBroker
import kafka.log.LogAppendInfo
import kafka.metrics.KafkaMetricsGroup
import kafka.server.AbstractFetcherThread.{ReplicaFetch, ResultWithPartitions}
import kafka.utils.CoreUtils.inLock
import kafka.utils.Implicits._
import kafka.utils.{DelayedItem, Pool, ShutdownableThread}
import org.apache.kafka.common.errors._
import org.apache.kafka.common.internals.PartitionStates
import org.apache.kafka.common.message.OffsetForLeaderEpochResponseData.EpochEndOffset
import org.apache.kafka.common.message.{FetchResponseData, OffsetForLeaderEpochRequestData}
import org.apache.kafka.common.protocol.Errors
import org.apache.kafka.common.record.{FileRecords, MemoryRecords, Records}
import org.apache.kafka.common.requests.OffsetsForLeaderEpochResponse.{UNDEFINED_EPOCH, UNDEFINED_EPOCH_OFFSET}
import org.apache.kafka.common.requests._
import org.apache.kafka.common.{InvalidRecordException, TopicPartition, Uuid}
import java.nio.ByteBuffer
import java.util
import java.util.Optional
import java.util.concurrent.TimeUnit
import java.util.concurrent.atomic.AtomicLong
import java.util.concurrent.locks.ReentrantLock
import scala.collection.{Map, Set, mutable}
import scala.compat.java8.OptionConverters._
import scala.jdk.CollectionConverters._
import scala.math._
/**
* Abstract class for fetching data from multiple partitions from the same broker.
*/
abstract class AbstractFetcherThread(name: String,
clientId: String,
val leader: LeaderEndPoint,
failedPartitions: FailedPartitions,
fetchBackOffMs: Int = 0,
isInterruptible: Boolean = true,
val brokerTopicStats: BrokerTopicStats) //BrokerTopicStats's lifecycle managed by ReplicaManager
extends ShutdownableThread(name, isInterruptible) {
type FetchData = FetchResponseData.PartitionData
type EpochData = OffsetForLeaderEpochRequestData.OffsetForLeaderPartition
private val partitionStates = new PartitionStates[PartitionFetchState]
protected val partitionMapLock = new ReentrantLock
private val partitionMapCond = partitionMapLock.newCondition()
private val metricId = ClientIdAndBroker(clientId, leader.brokerEndPoint().host, leader.brokerEndPoint().port)
val fetcherStats = new FetcherStats(metricId)
val fetcherLagStats = new FetcherLagStats(metricId)
/* callbacks to be defined in subclass */
// process fetched data
protected def processPartitionData(topicPartition: TopicPartition,
fetchOffset: Long,
partitionData: FetchData): Option[LogAppendInfo]
protected def truncate(topicPartition: TopicPartition, truncationState: OffsetTruncationState): Unit
protected def truncateFullyAndStartAt(topicPartition: TopicPartition, offset: Long): Unit
protected def latestEpoch(topicPartition: TopicPartition): Option[Int]
protected def logStartOffset(topicPartition: TopicPartition): Long
protected def logEndOffset(topicPartition: TopicPartition): Long
protected def endOffsetForEpoch(topicPartition: TopicPartition, epoch: Int): Option[OffsetAndEpoch]
protected val isOffsetForLeaderEpochSupported: Boolean
override def shutdown(): Unit = {
initiateShutdown()
inLock(partitionMapLock) {
partitionMapCond.signalAll()
}
awaitShutdown()
// we don't need the lock since the thread has finished shutdown and metric removal is safe
fetcherStats.unregister()
fetcherLagStats.unregister()
}
override def doWork(): Unit = {
maybeTruncate()
maybeFetch()
}
private def maybeFetch(): Unit = {
val fetchRequestOpt = inLock(partitionMapLock) {
val ResultWithPartitions(fetchRequestOpt, partitionsWithError) = leader.buildFetch(partitionStates.partitionStateMap.asScala)
handlePartitionsWithErrors(partitionsWithError, "maybeFetch")
if (fetchRequestOpt.isEmpty) {
trace(s"There are no active partitions. Back off for $fetchBackOffMs ms before sending a fetch request")
partitionMapCond.await(fetchBackOffMs, TimeUnit.MILLISECONDS)
}
fetchRequestOpt
}
fetchRequestOpt.foreach { case ReplicaFetch(sessionPartitions, fetchRequest) =>
processFetchRequest(sessionPartitions, fetchRequest)
}
}
// deal with partitions with errors, potentially due to leadership changes
private def handlePartitionsWithErrors(partitions: Iterable[TopicPartition], methodName: String): Unit = {
if (partitions.nonEmpty) {
debug(s"Handling errors in $methodName for partitions $partitions")
delayPartitions(partitions, fetchBackOffMs)
}
}
/**
* Builds offset for leader epoch requests for partitions that are in the truncating phase based
* on latest epochs of the future replicas (the one that is fetching)
*/
private def fetchTruncatingPartitions(): (Map[TopicPartition, EpochData], Set[TopicPartition]) = inLock(partitionMapLock) {
val partitionsWithEpochs = mutable.Map.empty[TopicPartition, EpochData]
val partitionsWithoutEpochs = mutable.Set.empty[TopicPartition]
partitionStates.partitionStateMap.forEach { (tp, state) =>
if (state.isTruncating) {
latestEpoch(tp) match {
case Some(epoch) if isOffsetForLeaderEpochSupported =>
partitionsWithEpochs += tp -> new EpochData()
.setPartition(tp.partition)
.setCurrentLeaderEpoch(state.currentLeaderEpoch)
.setLeaderEpoch(epoch)
case _ =>
partitionsWithoutEpochs += tp
}
}
}
(partitionsWithEpochs, partitionsWithoutEpochs)
}
private def maybeTruncate(): Unit = {
val (partitionsWithEpochs, partitionsWithoutEpochs) = fetchTruncatingPartitions()
if (partitionsWithEpochs.nonEmpty) {
truncateToEpochEndOffsets(partitionsWithEpochs)
}
if (partitionsWithoutEpochs.nonEmpty) {
truncateToHighWatermark(partitionsWithoutEpochs)
}
}
private def doTruncate(topicPartition: TopicPartition, truncationState: OffsetTruncationState): Boolean = {
try {
truncate(topicPartition, truncationState)
true
}
catch {
case e: KafkaStorageException =>
error(s"Failed to truncate $topicPartition at offset ${truncationState.offset}", e)
markPartitionFailed(topicPartition)
false
case t: Throwable =>
error(s"Unexpected error occurred during truncation for $topicPartition "
+ s"at offset ${truncationState.offset}", t)
markPartitionFailed(topicPartition)
false
}
}
/**
* - Build a leader epoch fetch based on partitions that are in the Truncating phase
* - Send OffsetsForLeaderEpochRequest, retrieving the latest offset for each partition's
* leader epoch. This is the offset the follower should truncate to ensure
* accurate log replication.
* - Finally truncate the logs for partitions in the truncating phase and mark the
* truncation complete. Do this within a lock to ensure no leadership changes can
* occur during truncation.
*/
private def truncateToEpochEndOffsets(latestEpochsForPartitions: Map[TopicPartition, EpochData]): Unit = {
val endOffsets = leader.fetchEpochEndOffsets(latestEpochsForPartitions)
//Ensure we hold a lock during truncation.
inLock(partitionMapLock) {
//Check no leadership and no leader epoch changes happened whilst we were unlocked, fetching epochs
val epochEndOffsets = endOffsets.filter { case (tp, _) =>
val curPartitionState = partitionStates.stateValue(tp)
val partitionEpochRequest = latestEpochsForPartitions.getOrElse(tp, {
throw new IllegalStateException(
s"Leader replied with partition $tp not requested in OffsetsForLeaderEpoch request")
})
val leaderEpochInRequest = partitionEpochRequest.currentLeaderEpoch
curPartitionState != null && leaderEpochInRequest == curPartitionState.currentLeaderEpoch
}
val ResultWithPartitions(fetchOffsets, partitionsWithError) = maybeTruncateToEpochEndOffsets(epochEndOffsets, latestEpochsForPartitions)
handlePartitionsWithErrors(partitionsWithError, "truncateToEpochEndOffsets")
updateFetchOffsetAndMaybeMarkTruncationComplete(fetchOffsets)
}
}
// Visibility for unit tests
protected[server] def truncateOnFetchResponse(epochEndOffsets: Map[TopicPartition, EpochEndOffset]): Unit = {
inLock(partitionMapLock) {
val ResultWithPartitions(fetchOffsets, partitionsWithError) = maybeTruncateToEpochEndOffsets(epochEndOffsets, Map.empty)
handlePartitionsWithErrors(partitionsWithError, "truncateOnFetchResponse")
updateFetchOffsetAndMaybeMarkTruncationComplete(fetchOffsets)
}
}
// Visible for testing
private[server] def truncateToHighWatermark(partitions: Set[TopicPartition]): Unit = inLock(partitionMapLock) {
val fetchOffsets = mutable.HashMap.empty[TopicPartition, OffsetTruncationState]
for (tp <- partitions) {
val partitionState = partitionStates.stateValue(tp)
if (partitionState != null) {
val highWatermark = partitionState.fetchOffset
val truncationState = OffsetTruncationState(highWatermark, truncationCompleted = true)
info(s"Truncating partition $tp with $truncationState due to local high watermark $highWatermark")
if (doTruncate(tp, truncationState))
fetchOffsets.put(tp, truncationState)
}
}
updateFetchOffsetAndMaybeMarkTruncationComplete(fetchOffsets)
}
private def maybeTruncateToEpochEndOffsets(fetchedEpochs: Map[TopicPartition, EpochEndOffset],
latestEpochsForPartitions: Map[TopicPartition, EpochData]): ResultWithPartitions[Map[TopicPartition, OffsetTruncationState]] = {
val fetchOffsets = mutable.HashMap.empty[TopicPartition, OffsetTruncationState]
val partitionsWithError = mutable.HashSet.empty[TopicPartition]
fetchedEpochs.forKeyValue { (tp, leaderEpochOffset) =>
if (partitionStates.contains(tp)) {
Errors.forCode(leaderEpochOffset.errorCode) match {
case Errors.NONE =>
val offsetTruncationState = getOffsetTruncationState(tp, leaderEpochOffset)
info(s"Truncating partition $tp with $offsetTruncationState due to leader epoch and offset $leaderEpochOffset")
if (doTruncate(tp, offsetTruncationState))
fetchOffsets.put(tp, offsetTruncationState)
case Errors.FENCED_LEADER_EPOCH =>
val currentLeaderEpoch = latestEpochsForPartitions.get(tp)
.map(epochEndOffset => Int.box(epochEndOffset.currentLeaderEpoch)).asJava
if (onPartitionFenced(tp, currentLeaderEpoch))
partitionsWithError += tp
case error =>
info(s"Retrying leaderEpoch request for partition $tp as the leader reported an error: $error")
partitionsWithError += tp
}
} else {
// Partitions may have been removed from the fetcher while the thread was waiting for fetch
// response. Removed partitions are filtered out while holding `partitionMapLock` to ensure that we
// don't update state for any partition that may have already been migrated to another thread.
trace(s"Ignoring epoch offsets for partition $tp since it has been removed from this fetcher thread.")
}
}
ResultWithPartitions(fetchOffsets, partitionsWithError)
}
/**
* remove the partition if the partition state is NOT updated. Otherwise, keep the partition active.
* @return true if the epoch in this thread is updated. otherwise, false
*/
private def onPartitionFenced(tp: TopicPartition, requestEpoch: Optional[Integer]): Boolean = inLock(partitionMapLock) {
Option(partitionStates.stateValue(tp)).exists { currentFetchState =>
val currentLeaderEpoch = currentFetchState.currentLeaderEpoch
if (requestEpoch.isPresent && requestEpoch.get == currentLeaderEpoch) {
info(s"Partition $tp has an older epoch ($currentLeaderEpoch) than the current leader. Will await " +
s"the new LeaderAndIsr state before resuming fetching.")
markPartitionFailed(tp)
false
} else {
info(s"Partition $tp has a newer epoch ($currentLeaderEpoch) than the current leader. Retry the partition later.")
true
}
}
}
private def processFetchRequest(sessionPartitions: util.Map[TopicPartition, FetchRequest.PartitionData],
fetchRequest: FetchRequest.Builder): Unit = {
val partitionsWithError = mutable.Set[TopicPartition]()
val divergingEndOffsets = mutable.Map.empty[TopicPartition, EpochEndOffset]
var responseData: Map[TopicPartition, FetchData] = Map.empty
try {
trace(s"Sending fetch request $fetchRequest")
responseData = leader.fetch(fetchRequest)
} catch {
case t: Throwable =>
if (isRunning) {
warn(s"Error in response for fetch request $fetchRequest", t)
inLock(partitionMapLock) {
partitionsWithError ++= partitionStates.partitionSet.asScala
}
}
}
fetcherStats.requestRate.mark()
if (responseData.nonEmpty) {
// process fetched data
inLock(partitionMapLock) {
responseData.forKeyValue { (topicPartition, partitionData) =>
Option(partitionStates.stateValue(topicPartition)).foreach { currentFetchState =>
// It's possible that a partition is removed and re-added or truncated when there is a pending fetch request.
// In this case, we only want to process the fetch response if the partition state is ready for fetch and
// the current offset is the same as the offset requested.
val fetchPartitionData = sessionPartitions.get(topicPartition)
if (fetchPartitionData != null && fetchPartitionData.fetchOffset == currentFetchState.fetchOffset && currentFetchState.isReadyForFetch) {
Errors.forCode(partitionData.errorCode) match {
case Errors.NONE =>
try {
// Once we hand off the partition data to the subclass, we can't mess with it any more in this thread
val logAppendInfoOpt = processPartitionData(topicPartition, currentFetchState.fetchOffset,
partitionData)
logAppendInfoOpt.foreach { logAppendInfo =>
val validBytes = logAppendInfo.validBytes
val nextOffset = if (validBytes > 0) logAppendInfo.lastOffset + 1 else currentFetchState.fetchOffset
val lag = Math.max(0L, partitionData.highWatermark - nextOffset)
fetcherLagStats.getAndMaybePut(topicPartition).lag = lag
// ReplicaDirAlterThread may have removed topicPartition from the partitionStates after processing the partition data
if (validBytes > 0 && partitionStates.contains(topicPartition)) {
// Update partitionStates only if there is no exception during processPartitionData
val newFetchState = PartitionFetchState(currentFetchState.topicId, nextOffset, Some(lag),
currentFetchState.currentLeaderEpoch, state = Fetching,
logAppendInfo.lastLeaderEpoch)
partitionStates.updateAndMoveToEnd(topicPartition, newFetchState)
fetcherStats.byteRate.mark(validBytes)
}
}
if (leader.isTruncationOnFetchSupported) {
FetchResponse.divergingEpoch(partitionData).ifPresent { divergingEpoch =>
divergingEndOffsets += topicPartition -> new EpochEndOffset()
.setPartition(topicPartition.partition)
.setErrorCode(Errors.NONE.code)
.setLeaderEpoch(divergingEpoch.epoch)
.setEndOffset(divergingEpoch.endOffset)
}
}
} catch {
case ime@(_: CorruptRecordException | _: InvalidRecordException) =>
// we log the error and continue. This ensures two things
// 1. If there is a corrupt message in a topic partition, it does not bring the fetcher thread
// down and cause other topic partition to also lag
// 2. If the message is corrupt due to a transient state in the log (truncation, partial writes
// can cause this), we simply continue and should get fixed in the subsequent fetches
error(s"Found invalid messages during fetch for partition $topicPartition " +
s"offset ${currentFetchState.fetchOffset}", ime)
partitionsWithError += topicPartition
case e: KafkaStorageException =>
error(s"Error while processing data for partition $topicPartition " +
s"at offset ${currentFetchState.fetchOffset}", e)
markPartitionFailed(topicPartition)
case t: Throwable =>
// stop monitoring this partition and add it to the set of failed partitions
error(s"Unexpected error occurred while processing data for partition $topicPartition " +
s"at offset ${currentFetchState.fetchOffset}", t)
markPartitionFailed(topicPartition)
}
case Errors.OFFSET_OUT_OF_RANGE =>
if (handleOutOfRangeError(topicPartition, currentFetchState, fetchPartitionData.currentLeaderEpoch))
partitionsWithError += topicPartition
case Errors.UNKNOWN_LEADER_EPOCH =>
debug(s"Remote broker has a smaller leader epoch for partition $topicPartition than " +
s"this replica's current leader epoch of ${currentFetchState.currentLeaderEpoch}.")
partitionsWithError += topicPartition
case Errors.FENCED_LEADER_EPOCH =>
if (onPartitionFenced(topicPartition, fetchPartitionData.currentLeaderEpoch))
partitionsWithError += topicPartition
case Errors.NOT_LEADER_OR_FOLLOWER =>
debug(s"Remote broker is not the leader for partition $topicPartition, which could indicate " +
"that the partition is being moved")
partitionsWithError += topicPartition
case Errors.UNKNOWN_TOPIC_OR_PARTITION =>
warn(s"Received ${Errors.UNKNOWN_TOPIC_OR_PARTITION} from the leader for partition $topicPartition. " +
"This error may be returned transiently when the partition is being created or deleted, but it is not " +
"expected to persist.")
partitionsWithError += topicPartition
case Errors.UNKNOWN_TOPIC_ID =>
warn(s"Received ${Errors.UNKNOWN_TOPIC_ID} from the leader for partition $topicPartition. " +
"This error may be returned transiently when the partition is being created or deleted, but it is not " +
"expected to persist.")
partitionsWithError += topicPartition
case Errors.INCONSISTENT_TOPIC_ID =>
warn(s"Received ${Errors.INCONSISTENT_TOPIC_ID} from the leader for partition $topicPartition. " +
"This error may be returned transiently when the partition is being created or deleted, but it is not " +
"expected to persist.")
partitionsWithError += topicPartition
case partitionError =>
error(s"Error for partition $topicPartition at offset ${currentFetchState.fetchOffset}", partitionError.exception)
partitionsWithError += topicPartition
}
}
}
}
}
}
if (divergingEndOffsets.nonEmpty)
truncateOnFetchResponse(divergingEndOffsets)
if (partitionsWithError.nonEmpty) {
handlePartitionsWithErrors(partitionsWithError, "processFetchRequest")
}
}
/**
* This is used to mark partitions for truncation in ReplicaAlterLogDirsThread after leader
* offsets are known.
*/
def markPartitionsForTruncation(topicPartition: TopicPartition, truncationOffset: Long): Unit = {
partitionMapLock.lockInterruptibly()
try {
Option(partitionStates.stateValue(topicPartition)).foreach { state =>
val newState = PartitionFetchState(state.topicId, math.min(truncationOffset, state.fetchOffset),
state.lag, state.currentLeaderEpoch, state.delay, state = Truncating,
lastFetchedEpoch = None)
partitionStates.updateAndMoveToEnd(topicPartition, newState)
partitionMapCond.signalAll()
}
} finally partitionMapLock.unlock()
}
private def markPartitionFailed(topicPartition: TopicPartition): Unit = {
partitionMapLock.lock()
try {
failedPartitions.add(topicPartition)
removePartitions(Set(topicPartition))
} finally partitionMapLock.unlock()
warn(s"Partition $topicPartition marked as failed")
}
/**
* Returns initial partition fetch state based on current state and the provided `initialFetchState`.
* From IBP 2.7 onwards, we can rely on truncation based on diverging data returned in fetch responses.
* For older versions, we can skip the truncation step iff the leader epoch matches the existing epoch.
*/
private def partitionFetchState(tp: TopicPartition, initialFetchState: InitialFetchState, currentState: PartitionFetchState): PartitionFetchState = {
if (currentState != null && currentState.currentLeaderEpoch == initialFetchState.currentLeaderEpoch) {
currentState
} else if (initialFetchState.initOffset < 0) {
fetchOffsetAndTruncate(tp, initialFetchState.topicId, initialFetchState.currentLeaderEpoch)
} else if (leader.isTruncationOnFetchSupported) {
// With old message format, `latestEpoch` will be empty and we use Truncating state
// to truncate to high watermark.
val lastFetchedEpoch = latestEpoch(tp)
val state = if (lastFetchedEpoch.nonEmpty) Fetching else Truncating
PartitionFetchState(initialFetchState.topicId, initialFetchState.initOffset, None, initialFetchState.currentLeaderEpoch,
state, lastFetchedEpoch)
} else {
PartitionFetchState(initialFetchState.topicId, initialFetchState.initOffset, None, initialFetchState.currentLeaderEpoch,
state = Truncating, lastFetchedEpoch = None)
}
}
def addPartitions(initialFetchStates: Map[TopicPartition, InitialFetchState]): Set[TopicPartition] = {
partitionMapLock.lockInterruptibly()
try {
failedPartitions.removeAll(initialFetchStates.keySet)
initialFetchStates.forKeyValue { (tp, initialFetchState) =>
val currentState = partitionStates.stateValue(tp)
val updatedState = partitionFetchState(tp, initialFetchState, currentState)
partitionStates.updateAndMoveToEnd(tp, updatedState)
}
partitionMapCond.signalAll()
initialFetchStates.keySet
} finally partitionMapLock.unlock()
}
def maybeUpdateTopicIds(partitions: Set[TopicPartition], topicIds: String => Option[Uuid]): Unit = {
partitionMapLock.lockInterruptibly()
try {
partitions.foreach { tp =>
val currentState = partitionStates.stateValue(tp)
if (currentState != null) {
val updatedState = currentState.updateTopicId(topicIds(tp.topic))
partitionStates.update(tp, updatedState)
}
}
partitionMapCond.signalAll()
} finally partitionMapLock.unlock()
}
/**
* Loop through all partitions, updating their fetch offset and maybe marking them as
* truncation completed if their offsetTruncationState indicates truncation completed
*
* @param fetchOffsets the partitions to update fetch offset and maybe mark truncation complete
*/
private def updateFetchOffsetAndMaybeMarkTruncationComplete(fetchOffsets: Map[TopicPartition, OffsetTruncationState]): Unit = {
val newStates: Map[TopicPartition, PartitionFetchState] = partitionStates.partitionStateMap.asScala
.map { case (topicPartition, currentFetchState) =>
val maybeTruncationComplete = fetchOffsets.get(topicPartition) match {
case Some(offsetTruncationState) =>
val lastFetchedEpoch = latestEpoch(topicPartition)
val state = if (leader.isTruncationOnFetchSupported || offsetTruncationState.truncationCompleted)
Fetching
else
Truncating
PartitionFetchState(currentFetchState.topicId, offsetTruncationState.offset, currentFetchState.lag,
currentFetchState.currentLeaderEpoch, currentFetchState.delay, state, lastFetchedEpoch)
case None => currentFetchState
}
(topicPartition, maybeTruncationComplete)
}
partitionStates.set(newStates.asJava)
}
/**
* Called from ReplicaFetcherThread and ReplicaAlterLogDirsThread maybeTruncate for each topic
* partition. Returns truncation offset and whether this is the final offset to truncate to
*
* For each topic partition, the offset to truncate to is calculated based on leader's returned
* epoch and offset:
* -- If the leader replied with undefined epoch offset, we must use the high watermark. This can
* happen if 1) the leader is still using message format older than IBP_0_11_0; 2) the follower
* requested leader epoch < the first leader epoch known to the leader.
* -- If the leader replied with the valid offset but undefined leader epoch, we truncate to
* leader's offset if it is lower than follower's Log End Offset. This may happen if the
* leader is on the inter-broker protocol version < IBP_2_0_IV0
* -- If the leader replied with leader epoch not known to the follower, we truncate to the
* end offset of the largest epoch that is smaller than the epoch the leader replied with, and
* send OffsetsForLeaderEpochRequest with that leader epoch. In a more rare case, where the
* follower was not tracking epochs smaller than the epoch the leader replied with, we
* truncate the leader's offset (and do not send any more leader epoch requests).
* -- Otherwise, truncate to min(leader's offset, end offset on the follower for epoch that
* leader replied with, follower's Log End Offset).
*
* @param tp Topic partition
* @param leaderEpochOffset Epoch end offset received from the leader for this topic partition
*/
private def getOffsetTruncationState(tp: TopicPartition,
leaderEpochOffset: EpochEndOffset): OffsetTruncationState = inLock(partitionMapLock) {
if (leaderEpochOffset.endOffset == UNDEFINED_EPOCH_OFFSET) {
// truncate to initial offset which is the high watermark for follower replica. For
// future replica, it is either high watermark of the future replica or current
// replica's truncation offset (when the current replica truncates, it forces future
// replica's partition state to 'truncating' and sets initial offset to its truncation offset)
warn(s"Based on replica's leader epoch, leader replied with an unknown offset in $tp. " +
s"The initial fetch offset ${partitionStates.stateValue(tp).fetchOffset} will be used for truncation.")
OffsetTruncationState(partitionStates.stateValue(tp).fetchOffset, truncationCompleted = true)
} else if (leaderEpochOffset.leaderEpoch == UNDEFINED_EPOCH) {
// either leader or follower or both use inter-broker protocol version < IBP_2_0_IV0
// (version 0 of OffsetForLeaderEpoch request/response)
warn(s"Leader or replica is on protocol version where leader epoch is not considered in the OffsetsForLeaderEpoch response. " +
s"The leader's offset ${leaderEpochOffset.endOffset} will be used for truncation in $tp.")
OffsetTruncationState(min(leaderEpochOffset.endOffset, logEndOffset(tp)), truncationCompleted = true)
} else {
val replicaEndOffset = logEndOffset(tp)
// get (leader epoch, end offset) pair that corresponds to the largest leader epoch
// less than or equal to the requested epoch.
endOffsetForEpoch(tp, leaderEpochOffset.leaderEpoch) match {
case Some(OffsetAndEpoch(followerEndOffset, followerEpoch)) =>
if (followerEpoch != leaderEpochOffset.leaderEpoch) {
// the follower does not know about the epoch that leader replied with
// we truncate to the end offset of the largest epoch that is smaller than the
// epoch the leader replied with, and send another offset for leader epoch request
val intermediateOffsetToTruncateTo = min(followerEndOffset, replicaEndOffset)
info(s"Based on replica's leader epoch, leader replied with epoch ${leaderEpochOffset.leaderEpoch} " +
s"unknown to the replica for $tp. " +
s"Will truncate to $intermediateOffsetToTruncateTo and send another leader epoch request to the leader.")
OffsetTruncationState(intermediateOffsetToTruncateTo, truncationCompleted = false)
} else {
val offsetToTruncateTo = min(followerEndOffset, leaderEpochOffset.endOffset)
OffsetTruncationState(min(offsetToTruncateTo, replicaEndOffset), truncationCompleted = true)
}
case None =>
// This can happen if the follower was not tracking leader epochs at that point (before the
// upgrade, or if this broker is new). Since the leader replied with epoch <
// requested epoch from follower, so should be safe to truncate to leader's
// offset (this is the same behavior as post-KIP-101 and pre-KIP-279)
warn(s"Based on replica's leader epoch, leader replied with epoch ${leaderEpochOffset.leaderEpoch} " +
s"below any replica's tracked epochs for $tp. " +
s"The leader's offset only ${leaderEpochOffset.endOffset} will be used for truncation.")
OffsetTruncationState(min(leaderEpochOffset.endOffset, replicaEndOffset), truncationCompleted = true)
}
}
}
/**
* Handle the out of range error. Return false if
* 1) the request succeeded or
* 2) was fenced and this thread haven't received new epoch,
* which means we need not backoff and retry. True if there was a retriable error.
*/
private def handleOutOfRangeError(topicPartition: TopicPartition,
fetchState: PartitionFetchState,
requestEpoch: Optional[Integer]): Boolean = {
try {
val newFetchState = fetchOffsetAndTruncate(topicPartition, fetchState.topicId, fetchState.currentLeaderEpoch)
partitionStates.updateAndMoveToEnd(topicPartition, newFetchState)
info(s"Current offset ${fetchState.fetchOffset} for partition $topicPartition is " +
s"out of range, which typically implies a leader change. Reset fetch offset to ${newFetchState.fetchOffset}")
false
} catch {
case _: FencedLeaderEpochException =>
onPartitionFenced(topicPartition, requestEpoch)
case e @ (_ : UnknownTopicOrPartitionException |
_ : UnknownLeaderEpochException |
_ : NotLeaderOrFollowerException) =>
info(s"Could not fetch offset for $topicPartition due to error: ${e.getMessage}")
true
case e: Throwable =>
error(s"Error getting offset for partition $topicPartition", e)
true
}
}
/**
* Handle a partition whose offset is out of range and return a new fetch offset.
*/
protected def fetchOffsetAndTruncate(topicPartition: TopicPartition, topicId: Option[Uuid], currentLeaderEpoch: Int): PartitionFetchState = {
val replicaEndOffset = logEndOffset(topicPartition)
/**
* Unclean leader election: A follower goes down, in the meanwhile the leader keeps appending messages. The follower comes back up
* and before it has completely caught up with the leader's logs, all replicas in the ISR go down. The follower is now uncleanly
* elected as the new leader, and it starts appending messages from the client. The old leader comes back up, becomes a follower
* and it may discover that the current leader's end offset is behind its own end offset.
*
* In such a case, truncate the current follower's log to the current leader's end offset and continue fetching.
*
* There is a potential for a mismatch between the logs of the two replicas here. We don't fix this mismatch as of now.
*/
val leaderEndOffset = leader.fetchLatestOffset(topicPartition, currentLeaderEpoch)
if (leaderEndOffset < replicaEndOffset) {
warn(s"Reset fetch offset for partition $topicPartition from $replicaEndOffset to current " +
s"leader's latest offset $leaderEndOffset")
truncate(topicPartition, OffsetTruncationState(leaderEndOffset, truncationCompleted = true))
fetcherLagStats.getAndMaybePut(topicPartition).lag = 0
PartitionFetchState(topicId, leaderEndOffset, Some(0), currentLeaderEpoch,
state = Fetching, lastFetchedEpoch = latestEpoch(topicPartition))
} else {
/**
* If the leader's log end offset is greater than the follower's log end offset, there are two possibilities:
* 1. The follower could have been down for a long time and when it starts up, its end offset could be smaller than the leader's
* start offset because the leader has deleted old logs (log.logEndOffset < leaderStartOffset).
* 2. When unclean leader election occurs, it is possible that the old leader's high watermark is greater than
* the new leader's log end offset. So when the old leader truncates its offset to its high watermark and starts
* to fetch from the new leader, an OffsetOutOfRangeException will be thrown. After that some more messages are
* produced to the new leader. While the old leader is trying to handle the OffsetOutOfRangeException and query
* the log end offset of the new leader, the new leader's log end offset becomes higher than the follower's log end offset.
*
* In the first case, the follower's current log end offset is smaller than the leader's log start offset. So the
* follower should truncate all its logs, roll out a new segment and start to fetch from the current leader's log
* start offset.
* In the second case, the follower should just keep the current log segments and retry the fetch. In the second
* case, there will be some inconsistency of data between old and new leader. We are not solving it here.
* If users want to have strong consistency guarantees, appropriate configurations needs to be set for both
* brokers and producers.
*
* Putting the two cases together, the follower should fetch from the higher one of its replica log end offset
* and the current leader's log start offset.
*/
val leaderStartOffset = leader.fetchEarliestOffset(topicPartition, currentLeaderEpoch)
warn(s"Reset fetch offset for partition $topicPartition from $replicaEndOffset to current " +
s"leader's start offset $leaderStartOffset")
val offsetToFetch = Math.max(leaderStartOffset, replicaEndOffset)
// Only truncate log when current leader's log start offset is greater than follower's log end offset.
if (leaderStartOffset > replicaEndOffset)
truncateFullyAndStartAt(topicPartition, leaderStartOffset)
val initialLag = leaderEndOffset - offsetToFetch
fetcherLagStats.getAndMaybePut(topicPartition).lag = initialLag
PartitionFetchState(topicId, offsetToFetch, Some(initialLag), currentLeaderEpoch,
state = Fetching, lastFetchedEpoch = latestEpoch(topicPartition))
}
}
def delayPartitions(partitions: Iterable[TopicPartition], delay: Long): Unit = {
partitionMapLock.lockInterruptibly()
try {
for (partition <- partitions) {
Option(partitionStates.stateValue(partition)).foreach { currentFetchState =>
if (!currentFetchState.isDelayed) {
partitionStates.updateAndMoveToEnd(partition, PartitionFetchState(currentFetchState.topicId, currentFetchState.fetchOffset,
currentFetchState.lag, currentFetchState.currentLeaderEpoch, Some(new DelayedItem(delay)),
currentFetchState.state, currentFetchState.lastFetchedEpoch))
}
}
}
partitionMapCond.signalAll()
} finally partitionMapLock.unlock()
}
def removePartitions(topicPartitions: Set[TopicPartition]): Map[TopicPartition, PartitionFetchState] = {
partitionMapLock.lockInterruptibly()
try {
topicPartitions.map { topicPartition =>
val state = partitionStates.stateValue(topicPartition)
partitionStates.remove(topicPartition)
fetcherLagStats.unregister(topicPartition)
topicPartition -> state
}.filter(_._2 != null).toMap
} finally partitionMapLock.unlock()
}
def removeAllPartitions(): Map[TopicPartition, PartitionFetchState] = {
partitionMapLock.lockInterruptibly()
try {
val allPartitionState = partitionStates.partitionStateMap.asScala.toMap
allPartitionState.keys.foreach { tp =>
partitionStates.remove(tp)
fetcherLagStats.unregister(tp)
}
allPartitionState
} finally partitionMapLock.unlock()
}
def partitionCount: Int = {
partitionMapLock.lockInterruptibly()
try partitionStates.size
finally partitionMapLock.unlock()
}
def partitions: Set[TopicPartition] = {
partitionMapLock.lockInterruptibly()
try partitionStates.partitionSet.asScala.toSet
finally partitionMapLock.unlock()
}
// Visible for testing
private[server] def fetchState(topicPartition: TopicPartition): Option[PartitionFetchState] = inLock(partitionMapLock) {
Option(partitionStates.stateValue(topicPartition))
}
protected def toMemoryRecords(records: Records): MemoryRecords = {
(records: @unchecked) match {
case r: MemoryRecords => r
case r: FileRecords =>
val buffer = ByteBuffer.allocate(r.sizeInBytes)
r.readInto(buffer, 0)
MemoryRecords.readableRecords(buffer)
}
}
}
object AbstractFetcherThread {
case class ReplicaFetch(partitionData: util.Map[TopicPartition, FetchRequest.PartitionData], fetchRequest: FetchRequest.Builder)
case class ResultWithPartitions[R](result: R, partitionsWithError: Set[TopicPartition])
}
object FetcherMetrics {
val ConsumerLag = "ConsumerLag"
val RequestsPerSec = "RequestsPerSec"
val BytesPerSec = "BytesPerSec"
}
class FetcherLagMetrics(metricId: ClientIdTopicPartition) extends KafkaMetricsGroup {
private[this] val lagVal = new AtomicLong(-1L)
private[this] val tags = Map(
"clientId" -> metricId.clientId,
"topic" -> metricId.topicPartition.topic,
"partition" -> metricId.topicPartition.partition.toString)
newGauge(FetcherMetrics.ConsumerLag, () => lagVal.get, tags)
def lag_=(newLag: Long): Unit = {
lagVal.set(newLag)
}
def lag = lagVal.get
def unregister(): Unit = {
removeMetric(FetcherMetrics.ConsumerLag, tags)
}
}
class FetcherLagStats(metricId: ClientIdAndBroker) {
private val valueFactory = (k: TopicPartition) => new FetcherLagMetrics(ClientIdTopicPartition(metricId.clientId, k))
val stats = new Pool[TopicPartition, FetcherLagMetrics](Some(valueFactory))
def getAndMaybePut(topicPartition: TopicPartition): FetcherLagMetrics = {
stats.getAndMaybePut(topicPartition)
}
def unregister(topicPartition: TopicPartition): Unit = {
val lagMetrics = stats.remove(topicPartition)
if (lagMetrics != null) lagMetrics.unregister()
}
def unregister(): Unit = {
stats.keys.toBuffer.foreach { key: TopicPartition =>
unregister(key)
}
}
}
class FetcherStats(metricId: ClientIdAndBroker) extends KafkaMetricsGroup {
val tags = Map("clientId" -> metricId.clientId,
"brokerHost" -> metricId.brokerHost,
"brokerPort" -> metricId.brokerPort.toString)
val requestRate = newMeter(FetcherMetrics.RequestsPerSec, "requests", TimeUnit.SECONDS, tags)
val byteRate = newMeter(FetcherMetrics.BytesPerSec, "bytes", TimeUnit.SECONDS, tags)
def unregister(): Unit = {
removeMetric(FetcherMetrics.RequestsPerSec, tags)
removeMetric(FetcherMetrics.BytesPerSec, tags)
}
}
case class ClientIdTopicPartition(clientId: String, topicPartition: TopicPartition) {
override def toString: String = s"$clientId-$topicPartition"
}
sealed trait ReplicaState
case object Truncating extends ReplicaState
case object Fetching extends ReplicaState
object PartitionFetchState {
def apply(topicId: Option[Uuid], offset: Long, lag: Option[Long], currentLeaderEpoch: Int, state: ReplicaState,
lastFetchedEpoch: Option[Int]): PartitionFetchState = {
PartitionFetchState(topicId, offset, lag, currentLeaderEpoch, None, state, lastFetchedEpoch)
}
}
/**
* case class to keep partition offset and its state(truncatingLog, delayed)
* This represents a partition as being either:
* (1) Truncating its log, for example having recently become a follower
* (2) Delayed, for example due to an error, where we subsequently back off a bit
* (3) ReadyForFetch, the is the active state where the thread is actively fetching data.
*/
case class PartitionFetchState(topicId: Option[Uuid],
fetchOffset: Long,
lag: Option[Long],
currentLeaderEpoch: Int,
delay: Option[DelayedItem],
state: ReplicaState,
lastFetchedEpoch: Option[Int]) {
def isReadyForFetch: Boolean = state == Fetching && !isDelayed
def isReplicaInSync: Boolean = lag.isDefined && lag.get <= 0
def isTruncating: Boolean = state == Truncating && !isDelayed
def isDelayed: Boolean = delay.exists(_.getDelay(TimeUnit.MILLISECONDS) > 0)
override def toString: String = {
s"FetchState(topicId=$topicId" +
s", fetchOffset=$fetchOffset" +
s", currentLeaderEpoch=$currentLeaderEpoch" +
s", lastFetchedEpoch=$lastFetchedEpoch" +
s", state=$state" +
s", lag=$lag" +
s", delay=${delay.map(_.delayMs).getOrElse(0)}ms" +
s")"
}
def updateTopicId(topicId: Option[Uuid]): PartitionFetchState = {
this.copy(topicId = topicId)
}
}
case class OffsetTruncationState(offset: Long, truncationCompleted: Boolean) {
def this(offset: Long) = this(offset, true)
override def toString: String = s"TruncationState(offset=$offset, completed=$truncationCompleted)"
}
case class OffsetAndEpoch(offset: Long, leaderEpoch: Int) {
override def toString: String = {
s"(offset=$offset, leaderEpoch=$leaderEpoch)"
}
}
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kafka AbstractFetcherManager 源码
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