流程图
BlockManager原理剖析.png
Driver上，有BlockManagerMaster，它的功能，就是负责对各个节点上的BlockManager内部管理的数据的元数据进行维护，比如Block的增删改等操作，都会在这里维护元数据的变更
每个节点上，都有BlockManager，BlockManager上有几个关键组件
DiskStore，负责对磁盘上的数据进行读写
MemoryStore，负责对内存中的数据进行读写
ConnectionManager，负责建立BlockManager到远程其他节点的BlockManager的网络连接
BlockTransferService，负责远程其他节点的BlockManager的数据的读写
每个BlockManager创建之后，做的第一件事就是向BlockManagerMaster去进行注册，此时BlockManagerMaster会为其创建对应的BlockManagerInfo
使用BlockManager进行写操作时，比如说，RDD运行过程中的一些中间数据，或者手动指定了persist(),优先将数据写入内存中，内存大小不够用，会使用自己的算法，将内存中的部分数据写入磁盘
此外，如果persist()指定了要replica，那么，会使用BlockTransferService将数据replicate一份到其他节点的BlockManager上去
BlockTransferService会通过ConnectionManager连接其他BlockManager，BlockTransferService进行replicate操作
从BlockManager读数据时，比如Shuffle Read操作，如果能从本地读取数据，那么利用DiskStore或者MemoryStore从本地读取数据，
如果本地没有数据的话，会用ConnectionManager与有数据的BlockManager建立连接，然后用BlockTransferService从远程BlockManager读取数据
只要使用了BlockManager执行了数据增删改查的操作，那么必须将block的BlockStatus上报到BlockManagerMaster上去，在BlockManagerMaster上，会对指定BlockManager的BlockManagerInfo内部的BlockStatus，进行增删改操作，从而达到元数据的维护功能
源码剖析
BlockManager注册
首先看BlockManagerMasterActor，BlockManagerMasterActor就是负责维护各个executor的BlockManager的元数据，BlockManagerInfo，BlockStatus
首先看看BlockManagerMasterActor里面两个重要的map
// Mapping from block manager id to the block manager's information.
// 这个map，映射了block manager id 到 block manager的info
// BlockManagerMaster要负责维护每个BlockManager的BlockManagerInfo
private val blockManagerInfo = new mutable.HashMap[BlockManagerId, BlockManagerInfo]
// Mapping from executor ID to block manager ID.
// 映射了每个ExecutorId到BlockManagerId，也就是说，每个executor是与一个BlockManager相关联的
private val blockManagerIdByExecutor = new mutable.HashMap[String, BlockManagerId]
首先看看register()方法
/**
* 注册BlockManager
*/
private def register(id: BlockManagerId, maxMemSize: Long, slaveActor: ActorRef) {
val time = System.currentTimeMillis()
// 首先判断本地HashMap中没有指定的BlockManagerId，说明从来没有注册过，才会往下走，去注册这个BlockManager
if (!blockManagerInfo.contains(id)) {
// 根据BlockManager对应的executorId找到对应的BlockManagerInfo
// 这里其实是做一个安全判断，因为如果blockManagerInfo map里面没有BlockManagerId
// 那么同步的blockManagerIdByExecutor map里，也必须没有BlockManager对应的executor对应的BlockManagerId
// 所以这里要判断一下，如果blockManagerIdByExecutor map里有BlockManageId，那么做一下清理
blockManagerIdByExecutor.get(id.executorId) match {
case Some(oldId) =>
// A block manager of the same executor already exists, so remove it (assumed dead)
logError("Got two different block manager registrations on same executor - "
+ s" will replace old one $oldId with new one $id")
// 从内存中，移除该executorId相关的BlockManagerInfo
removeExecutor(id.executorId)
case None =>
}
logInfo("Registering block manager %s with %s RAM, %s".format(
id.hostPort, Utils.bytesToString(maxMemSize), id))
// 往blockManagerIdByExecutor map中保存一份executorId到BlockManagerId的映射
blockManagerIdByExecutor(id.executorId) = id
// 为BlockManagerId创建一根BlockManagerInfo，并往blockManagerInfo map中，保存一份BlockManagerId到BlockManagerInfo的映射
blockManagerInfo(id) = new BlockManagerInfo(
id, System.currentTimeMillis(), maxMemSize, slaveActor)
}
listenerBus.post(SparkListenerBlockManagerAdded(time, id, maxMemSize))
}
看看removeExecutor()方法
private def removeExecutor(execId: String) {
logInfo("Trying to remove executor " + execId + " from BlockManagerMaster.")
// 获取executorId对应的BlockManagerInfo，对其调用removeBlockManager方法
blockManagerIdByExecutor.get(execId).foreach(removeBlockManager)
}
看看removeBlockManager()方法
private def removeBlockManager(blockManagerId: BlockManagerId) {
// 尝试根据blockManagerId获取到它对应的BlockManagerInfo
val info = blockManagerInfo(blockManagerId)
// Remove the block manager from blockManagerIdByExecutor.
// 从blockManagerIdByExecutor map中移除executorId对应的BlockManagerInfo
blockManagerIdByExecutor -= blockManagerId.executorId
// Remove it from blockManagerInfo and remove all the blocks.
// 从blockManagerInfo也移除对应的BlockManagerInfo
blockManagerInfo.remove(blockManagerId)
// 遍历BlockManagerInfo内部所有的block的blockId
val iterator = info.blocks.keySet.iterator
while (iterator.hasNext) {
// 清空BlockManagerInfo内部的block的BlockStatus信息
val blockId = iterator.next
val locations = blockLocations.get(blockId)
locations -= blockManagerId
if (locations.size == 0) {
blockLocations.remove(blockId)
}
}
listenerBus.post(SparkListenerBlockManagerRemoved(System.currentTimeMillis(), blockManagerId))
logInfo(s"Removing block manager $blockManagerId")
}
更新BlockInfo
更新BlockInfo，也就是说，每个BlockManager上，如果block发生了变化，那么都要发送updateBlockInfo请求来BlockManagerMaster这里。来进行BlockInfo的更新
/**
* 更新BlockInfo，也就是说，每个BlockManager上，如果block发生了变化，那么都要发送updateBlockInfo请求来BlockManagerMaster这里。来进行BlockInfo的更新
*/
private def updateBlockInfo(
blockManagerId: BlockManagerId,
blockId: BlockId,
storageLevel: StorageLevel,
memSize: Long,
diskSize: Long,
tachyonSize: Long): Boolean = {
if (!blockManagerInfo.contains(blockManagerId)) {
if (blockManagerId.isDriver && !isLocal) {
// We intentionally do not register the master (except in local mode),
// so we should not indicate failure.
return true
} else {
return false
}
}
if (blockId == null) {
blockManagerInfo(blockManagerId).updateLastSeenMs()
return true
}
// 调用BlockManager的blockManagerInfo的updateBlockInfo()方法，更新block信息
blockManagerInfo(blockManagerId).updateBlockInfo(
blockId, storageLevel, memSize, diskSize, tachyonSize)
// 每一个block可能会在多个BlockManager上面，因为如果将StorageLevel设置成带着_2的这种，那么就需要将block replicate一份，放到其他
// BlockManager上，blockLocations map其实保存了blockId对应的BlockManagerId的set集合，所以，这里会更新blockLocations中的信息，
// 因为是用set存储BlockManagerId，因此自动就去重了
var locations: mutable.HashSet[BlockManagerId] = null
if (blockLocations.containsKey(blockId)) {
locations = blockLocations.get(blockId)
} else {
locations = new mutable.HashSet[BlockManagerId]
blockLocations.put(blockId, locations)
}
if (storageLevel.isValid) {
locations.add(blockManagerId)
} else {
locations.remove(blockManagerId)
}
// Remove the block from master tracking if it has been removed on all slaves.
if (locations.size == 0) {
blockLocations.remove(blockId)
}
true
}
BlockManager初始化
BlockManager运行在每个节点上，包括Driver和Executor，都会有一份，主要提供了在本地或者远程存取数据的功能，支持内存、磁盘、堆外存储(Tychyon)
先看一个map
// 每个BlockManager，都会自己维护一个map，这里维护的blockInfo map，可以代表一个block，blockInfo最大的作用，就是用于
// 多线程并发访问同一个block的同步监视器
private val blockInfo = new TimeStampedHashMap[BlockId, BlockInfo]
看initialize()方法
def initialize(appId: String): Unit = {
// 首先初始化，用于进行远程block数据传输的blockTransferService
blockTransferService.init(this)
shuffleClient.init(appId)
// 为当前这个BlockManager创建一个唯一的BlockManagerId
// 使用executorId(每个BlockManager都关联一个Executor)，blockTransferService的hostname，blockTransferService的port
// 所以，从BlockManagerId的初始化即可看出，一个BlockManager是通过一个节点上的Executor来唯一标识的
blockManagerId = BlockManagerId(
executorId, blockTransferService.hostName, blockTransferService.port)
shuffleServerId = if (externalShuffleServiceEnabled) {
BlockManagerId(executorId, blockTransferService.hostName, externalShuffleServicePort)
} else {
blockManagerId
}
// 使用BlockManagerMasterActor的引用，进行BlockManager的注册，发送消息到BlockManagerMasterActor
master.registerBlockManager(blockManagerId, maxMemory, slaveActor)
// Register Executors' configuration with the local shuffle service, if one should exist.
if (externalShuffleServiceEnabled && !blockManagerId.isDriver) {
registerWithExternalShuffleServer()
}
}
BlockManager写数据
看看doPut操作
private def doPut(
blockId: BlockId,
data: BlockValues,
level: StorageLevel,
tellMaster: Boolean = true,
effectiveStorageLevel: Option[StorageLevel] = None)
: Seq[(BlockId, BlockStatus)] = {
require(blockId != null, "BlockId is null")
require(level != null && level.isValid, "StorageLevel is null or invalid")
effectiveStorageLevel.foreach { level =>
require(level != null && level.isValid, "Effective StorageLevel is null or invalid")
}
// Return value
val updatedBlocks = new ArrayBuffer[(BlockId, BlockStatus)]
/* Remember the block's storage level so that we can correctly drop it to disk if it needs
* to be dropped right after it got put into memory. Note, however, that other threads will
* not be able to get() this block until we call markReady on its BlockInfo. */
// 为要写入的block，创建一个blockInfo，并将其放入blockinfo map中缓存起来
val putBlockInfo = {
val tinfo = new BlockInfo(level, tellMaster)
// Do atomically !
val oldBlockOpt = blockInfo.putIfAbsent(blockId, tinfo)
if (oldBlockOpt.isDefined) {
if (oldBlockOpt.get.waitForReady()) {
logWarning(s"Block $blockId already exists on this machine; not re-adding it")
return updatedBlocks
}
// TODO: So the block info exists - but previous attempt to load it (?) failed.
// What do we do now ? Retry on it ?
oldBlockOpt.get
} else {
tinfo
}
}
val startTimeMs = System.currentTimeMillis
/* If we're storing values and we need to replicate the data, we'll want access to the values,
* but because our put will read the whole iterator, there will be no values left. For the
* case where the put serializes data, we'll remember the bytes, above; but for the case where
* it doesn't, such as deserialized storage, let's rely on the put returning an Iterator. */
var valuesAfterPut: Iterator[Any] = null
// Ditto for the bytes after the put
var bytesAfterPut: ByteBuffer = null
// Size of the block in bytes
var size = 0L
// The level we actually use to put the block
val putLevel = effectiveStorageLevel.getOrElse(level)
// If we're storing bytes, then initiate the replication before storing them locally.
// This is faster as data is already serialized and ready to send.
val replicationFuture = data match {
case b: ByteBufferValues if putLevel.replication > 1 =>
// Duplicate doesn't copy the bytes, but just creates a wrapper
val bufferView = b.buffer.duplicate()
Future { replicate(blockId, bufferView, putLevel) }
case _ => null
}
// 尝试对BlockInfo加锁，进行多线程并发访问同步
putBlockInfo.synchronized {
logTrace("Put for block %s took %s to get into synchronized block"
.format(blockId, Utils.getUsedTimeMs(startTimeMs)))
var marked = false
try {
// returnValues - Whether to return the values put
// blockStore - The type of storage to put these values into
// 首先根据持久化级别，选择一种BlockStore
val (returnValues, blockStore: BlockStore) = {
if (putLevel.useMemory) {
// Put it in memory first, even if it also has useDisk set to true;
// We will drop it to disk later if the memory store can't hold it.
(true, memoryStore)
} else if (putLevel.useOffHeap) {
// Use tachyon for off-heap storage
(false, tachyonStore)
} else if (putLevel.useDisk) {
// Don't get back the bytes from put unless we replicate them
(putLevel.replication > 1, diskStore)
} else {
assert(putLevel == StorageLevel.NONE)
throw new BlockException(
blockId, s"Attempted to put block $blockId without specifying storage level!")
}
}
// Actually put the values
// 根据选择的BlockStore，然后根据数据的类型，将数据放入store中
val result = data match {
case IteratorValues(iterator) =>
blockStore.putIterator(blockId, iterator, putLevel, returnValues)
case ArrayValues(array) =>
blockStore.putArray(blockId, array, putLevel, returnValues)
case ByteBufferValues(bytes) =>
bytes.rewind()
blockStore.putBytes(blockId, bytes, putLevel)
}
size = result.size
result.data match {
case Left (newIterator) if putLevel.useMemory => valuesAfterPut = newIterator
case Right (newBytes) => bytesAfterPut = newBytes
case _ =>
}
// Keep track of which blocks are dropped from memory
if (putLevel.useMemory) {
result.droppedBlocks.foreach { updatedBlocks += _ }
}
// 获取到一个Block对应的BlockStatus
val putBlockStatus = getCurrentBlockStatus(blockId, putBlockInfo)
if (putBlockStatus.storageLevel != StorageLevel.NONE) {
// Now that the block is in either the memory, tachyon, or disk store,
// let other threads read it, and tell the master about it.
marked = true
putBlockInfo.markReady(size)
if (tellMaster) {
// 调用reportBlockStatus()方法，将新写入的block数据，发送到BlockManagerMaster，以便于进行block元数据的同步和维护
reportBlockStatus(blockId, putBlockInfo, putBlockStatus)
}
updatedBlocks += ((blockId, putBlockStatus))
}
} finally {
// If we failed in putting the block to memory/disk, notify other possible readers
// that it has failed, and then remove it from the block info map.
if (!marked) {
// Note that the remove must happen before markFailure otherwise another thread
// could've inserted a new BlockInfo before we remove it.
blockInfo.remove(blockId)
putBlockInfo.markFailure()
logWarning(s"Putting block $blockId failed")
}
}
}
logDebug("Put block %s locally took %s".format(blockId, Utils.getUsedTimeMs(startTimeMs)))
// Either we're storing bytes and we asynchronously started replication, or we're storing
// values and need to serialize and replicate them now:
// 如果持久化是定义了_2这种后缀，说明需要对block进行replica，然后传输到其他节点上
if (putLevel.replication > 1) {
data match {
case ByteBufferValues(bytes) =>
if (replicationFuture != null) {
Await.ready(replicationFuture, Duration.Inf)
}
case _ =>
val remoteStartTime = System.currentTimeMillis
// Serialize the block if not already done
if (bytesAfterPut == null) {
if (valuesAfterPut == null) {
throw new SparkException(
"Underlying put returned neither an Iterator nor bytes! This shouldn't happen.")
}
bytesAfterPut = dataSerialize(blockId, valuesAfterPut)
}
// 调用replicate()方法进行复制操作
replicate(blockId, bytesAfterPut, putLevel)
logDebug("Put block %s remotely took %s"
.format(blockId, Utils.getUsedTimeMs(remoteStartTime)))
}
}
BlockManager.dispose(bytesAfterPut)
if (putLevel.replication > 1) {
logDebug("Putting block %s with replication took %s"
.format(blockId, Utils.getUsedTimeMs(startTimeMs)))
} else {
logDebug("Putting block %s without replication took %s"
.format(blockId, Utils.getUsedTimeMs(startTimeMs)))
}
updatedBlocks
}
看看DiskStore的putBytes()方法
override def putBytes(blockId: BlockId, _bytes: ByteBuffer, level: StorageLevel): PutResult = {
// So that we do not modify the input offsets !
// duplicate does not copy buffer, so inexpensive
val bytes = _bytes.duplicate()
logDebug(s"Attempting to put block $blockId")
val startTime = System.currentTimeMillis
val file = diskManager.getFile(blockId)
// 使用Java NIO将数据写入磁盘文件
val channel = new FileOutputStream(file).getChannel
while (bytes.remaining > 0) {
channel.write(bytes)
}
channel.close()
val finishTime = System.currentTimeMillis
logDebug("Block %s stored as %s file on disk in %d ms".format(
file.getName, Utils.bytesToString(bytes.limit), finishTime - startTime))
PutResult(bytes.limit(), Right(bytes.duplicate()))
}
看看MemoryStore的putBytes()方法
再看MemoryStore的putBytes()方法之前，先看下MemoryStore里的一个map
// MemoryStore中维护的entries map 其实就是真正存放每个block的数据
// 每个Block在内存中的数据，用MemoryEntry代表
private val entries = new LinkedHashMap[BlockId, MemoryEntry](32, 0.75f, true)
接着看MemoryStore的putBytes()方法
override def putBytes(blockId: BlockId, _bytes: ByteBuffer, level: StorageLevel): PutResult = {
// Work on a duplicate - since the original input might be used elsewhere.
val bytes = _bytes.duplicate()
bytes.rewind()
if (level.deserialized) {
val values = blockManager.dataDeserialize(blockId, bytes)
putIterator(blockId, values, level, returnValues = true)
} else {
val putAttempt = tryToPut(blockId, bytes, bytes.limit, deserialized = false)
PutResult(bytes.limit(), Right(bytes.duplicate()), putAttempt.droppedBlocks)
}
}
看putIterator()方法
override def putIterator(
blockId: BlockId,
values: Iterator[Any],
level: StorageLevel,
returnValues: Boolean): PutResult = {
putIterator(blockId, values, level, returnValues, allowPersistToDisk = true)
}
继续看putIterator()方法
private[storage] def putIterator(
blockId: BlockId,
values: Iterator[Any],
level: StorageLevel,
returnValues: Boolean,
allowPersistToDisk: Boolean): PutResult = {
val droppedBlocks = new ArrayBuffer[(BlockId, BlockStatus)]
val unrolledValues = unrollSafely(blockId, values, droppedBlocks)
unrolledValues match {
case Left(arrayValues) =>
// Values are fully unrolled in memory, so store them as an array
val res = putArray(blockId, arrayValues, level, returnValues)
droppedBlocks ++= res.droppedBlocks
PutResult(res.size, res.data, droppedBlocks)
case Right(iteratorValues) =>
// Not enough space to unroll this block; drop to disk if applicable
if (level.useDisk && allowPersistToDisk) {
logWarning(s"Persisting block $blockId to disk instead.")
val res = blockManager.diskStore.putIterator(blockId, iteratorValues, level, returnValues)
PutResult(res.size, res.data, droppedBlocks)
} else {
PutResult(0, Left(iteratorValues), droppedBlocks)
}
}
}
看putArray()方法
override def putArray(
blockId: BlockId,
values: Array[Any],
level: StorageLevel,
returnValues: Boolean): PutResult = {
if (level.deserialized) {
val sizeEstimate = SizeEstimator.estimate(values.asInstanceOf[AnyRef])
val putAttempt = tryToPut(blockId, values, sizeEstimate, deserialized = true)
PutResult(sizeEstimate, Left(values.iterator), putAttempt.droppedBlocks)
} else {
val bytes = blockManager.dataSerialize(blockId, values.iterator)
val putAttempt = tryToPut(blockId, bytes, bytes.limit, deserialized = false)
PutResult(bytes.limit(), Right(bytes.duplicate()), putAttempt.droppedBlocks)
}
}
看tryToPut()方法，优先放入内存，不行的话，尝试移除部分旧数据，再将block存入，真正存数据的方法
private def tryToPut(
blockId: BlockId,
value: Any,
size: Long,
deserialized: Boolean): ResultWithDroppedBlocks = {
/* TODO: Its possible to optimize the locking by locking entries only when selecting blocks
* to be dropped. Once the to-be-dropped blocks have been selected, and lock on entries has
* been released, it must be ensured that those to-be-dropped blocks are not double counted
* for freeing up more space for another block that needs to be put. Only then the actually
* dropping of blocks (and writing to disk if necessary) can proceed in parallel. */
var putSuccess = false
val droppedBlocks = new ArrayBuffer[(BlockId, BlockStatus)]
// 进行多线程并发同步，这里必须进行多线程并发同步，因为可能你刚判断内存足够，但是其他线程就放入了数据，然后你往内存中放数据，直接OOM内存溢出
accountingLock.synchronized {
// 调用ensureFreeSpace()方法，判断内存是否够用，如果不够用，此时会将部分数据用dropFromMemory()方法尝试写入磁盘，但是如果持久化级别不支持磁盘，那么数据丢失
val freeSpaceResult = ensureFreeSpace(blockId, size)
val enoughFreeSpace = freeSpaceResult.success
droppedBlocks ++= freeSpaceResult.droppedBlocks
// 将数据写入内存的时候，首先调用enoughFreeSpace()方法，判断内存是否足够放入数据
if (enoughFreeSpace) {
// 给数据创建一份MemoryEntry
val entry = new MemoryEntry(value, size, deserialized)
entries.synchronized {
// 将数据放入内存的entries中
entries.put(blockId, entry)
currentMemory += size
}
val valuesOrBytes = if (deserialized) "values" else "bytes"
logInfo("Block %s stored as %s in memory (estimated size %s, free %s)".format(
blockId, valuesOrBytes, Utils.bytesToString(size), Utils.bytesToString(freeMemory)))
putSuccess = true
} else {
// Tell the block manager that we couldn't put it in memory so that it can drop it to
// disk if the block allows disk storage.
val data = if (deserialized) {
Left(value.asInstanceOf[Array[Any]])
} else {
Right(value.asInstanceOf[ByteBuffer].duplicate())
}
val droppedBlockStatus = blockManager.dropFromMemory(blockId, data)
droppedBlockStatus.foreach { status => droppedBlocks += ((blockId, status)) }
}
}
ResultWithDroppedBlocks(putSuccess, droppedBlocks)
}
看看ensureFreeSpace()方法
private def ensureFreeSpace(
blockIdToAdd: BlockId,
space: Long): ResultWithDroppedBlocks = {
logInfo(s"ensureFreeSpace($space) called with curMem=$currentMemory, maxMem=$maxMemory")
val droppedBlocks = new ArrayBuffer[(BlockId, BlockStatus)]
if (space > maxMemory) {
logInfo(s"Will not store $blockIdToAdd as it is larger than our memory limit")
return ResultWithDroppedBlocks(success = false, droppedBlocks)
}
// Take into account the amount of memory currently occupied by unrolling blocks
val actualFreeMemory = freeMemory - currentUnrollMemory
// 如果当前内存不足够将这个block放入的话
if (actualFreeMemory < space) {
val rddToAdd = getRddId(blockIdToAdd)
val selectedBlocks = new ArrayBuffer[BlockId]
var selectedMemory = 0L
// This is synchronized to ensure that the set of entries is not changed
// (because of getValue or getBytes) while traversing the iterator, as that
// can lead to exceptions.
// 同步entries
entries.synchronized {
val iterator = entries.entrySet().iterator()
// 尝试从entries中，移除一部分数据
while (actualFreeMemory + selectedMemory < space && iterator.hasNext) {
val pair = iterator.next()
val blockId = pair.getKey
if (rddToAdd.isEmpty || rddToAdd != getRddId(blockId)) {
selectedBlocks += blockId
selectedMemory += pair.getValue.size
}
}
}
// 判断，如果移除一部分数据，就可以存放新的block了
if (actualFreeMemory + selectedMemory >= space) {
logInfo(s"${selectedBlocks.size} blocks selected for dropping")
// 将之前选择要移除的block数据，遍历
for (blockId <- selectedBlocks) {
val entry = entries.synchronized { entries.get(blockId) }
// This should never be null as only one thread should be dropping
// blocks and removing entries. However the check is still here for
// future safety.
if (entry != null) {
val data = if (entry.deserialized) {
Left(entry.value.asInstanceOf[Array[Any]])
} else {
Right(entry.value.asInstanceOf[ByteBuffer].duplicate())
}
// 调用dropFromMemory()方法，尝试将数据写入磁盘，但是如果block的持久化级别没有写入磁盘，那么这个数据就彻底丢了
val droppedBlockStatus = blockManager.dropFromMemory(blockId, data)
droppedBlockStatus.foreach { status => droppedBlocks += ((blockId, status)) }
}
}
return ResultWithDroppedBlocks(success = true, droppedBlocks)
} else {
logInfo(s"Will not store $blockIdToAdd as it would require dropping another block " +
"from the same RDD")
return ResultWithDroppedBlocks(success = false, droppedBlocks)
}
}
ResultWithDroppedBlocks(success = true, droppedBlocks)
}
BlockManager读数据
看看doGetLocal
/**
* 从本地获取数据
*/
private def doGetLocal(blockId: BlockId, asBlockResult: Boolean): Option[Any] = {
// 尝试获取block对应的blockInfo的锁
val info = blockInfo.get(blockId).orNull
if (info != null) {
// 对所有的blockInfo，都会进行多线程并发访问的同步操作，所以BlockInfo，相当于是对一个Block，用于作为多线程并发访问的同步监视器
info.synchronized {
// Double check to make sure the block is still there. There is a small chance that the
// block has been removed by removeBlock (which also synchronizes on the blockInfo object).
// Note that this only checks metadata tracking. If user intentionally deleted the block
// on disk or from off heap storage without using removeBlock, this conditional check will
// still pass but eventually we will get an exception because we can't find the block.
if (blockInfo.get(blockId).isEmpty) {
logWarning(s"Block $blockId had been removed")
return None
}
// If another thread is writing the block, wait for it to become ready.
// 如果其他线程在操作这个block，那么其实会卡住，等待，去获取BlockInfo的排他锁，如果始终没有获取到，返回false，就直接返回
if (!info.waitForReady()) {
// If we get here, the block write failed.
logWarning(s"Block $blockId was marked as failure.")
return None
}
val level = info.level
logDebug(s"Level for block $blockId is $level")
// Look for the block in memory
// 判断，如果持久化级别使用了内存，比如MEMORY_ONLY，MEMORY_AND_DISK，MEMORY_ONLY_SER，MEMORY_AND_DSK_SER等
// 尝试从MemoryStore中获取数据
if (level.useMemory) {
logDebug(s"Getting block $blockId from memory")
val result = if (asBlockResult) {
memoryStore.getValues(blockId).map(new BlockResult(_, DataReadMethod.Memory, info.size))
} else {
memoryStore.getBytes(blockId)
}
result match {
case Some(values) =>
return result
case None =>
logDebug(s"Block $blockId not found in memory")
}
}
// Look for the block in Tachyon
if (level.useOffHeap) {
logDebug(s"Getting block $blockId from tachyon")
if (tachyonStore.contains(blockId)) {
tachyonStore.getBytes(blockId) match {
case Some(bytes) =>
if (!asBlockResult) {
return Some(bytes)
} else {
return Some(new BlockResult(
dataDeserialize(blockId, bytes), DataReadMethod.Memory, info.size))
}
case None =>
logDebug(s"Block $blockId not found in tachyon")
}
}
}
// Look for block on disk, potentially storing it back in memory if required
// 判断，如果持久化级别使用了磁盘
if (level.useDisk) {
logDebug(s"Getting block $blockId from disk")
val bytes: ByteBuffer = diskStore.getBytes(blockId) match {
case Some(b) => b
case None =>
throw new BlockException(
blockId, s"Block $blockId not found on disk, though it should be")
}
assert(0 == bytes.position())
if (!level.useMemory) {
// If the block shouldn't be stored in memory, we can just return it
if (asBlockResult) {
return Some(new BlockResult(dataDeserialize(blockId, bytes), DataReadMethod.Disk,
info.size))
} else {
return Some(bytes)
}
} else {
// Otherwise, we also have to store something in the memory store
if (!level.deserialized || !asBlockResult) {
/* We'll store the bytes in memory if the block's storage level includes
* "memory serialized", or if it should be cached as objects in memory
* but we only requested its serialized bytes. */
val copyForMemory = ByteBuffer.allocate(bytes.limit)
copyForMemory.put(bytes)
// 如果使用了Disk级别，也使用了Memory级别，那么从disk读取出来之后，其实会尝试将其放入MemoryStore中，也就是缓存到内存中
memoryStore.putBytes(blockId, copyForMemory, level)
bytes.rewind()
}
if (!asBlockResult) {
return Some(bytes)
} else {
val values = dataDeserialize(blockId, bytes)
if (level.deserialized) {
// Cache the values before returning them
val putResult = memoryStore.putIterator(
blockId, values, level, returnValues = true, allowPersistToDisk = false)
// The put may or may not have succeeded, depending on whether there was enough
// space to unroll the block. Either way, the put here should return an iterator.
putResult.data match {
case Left(it) =>
return Some(new BlockResult(it, DataReadMethod.Disk, info.size))
case _ =>
// This only happens if we dropped the values back to disk (which is never)
throw new SparkException("Memory store did not return an iterator!")
}
} else {
return Some(new BlockResult(values, DataReadMethod.Disk, info.size))
}
}
}
}
}
} else {
logDebug(s"Block $blockId not registered locally")
}
None
}
看看doGetRemote
private def doGetRemote(blockId: BlockId, asBlockResult: Boolean): Option[Any] = {
require(blockId != null, "BlockId is null")
// 首先从BlockManagerMaster上，获取每个blockId对应的BlockManager的信息，然后会随机打乱
val locations = Random.shuffle(master.getLocations(blockId))
// 遍历每个BlockManager
for (loc <- locations) {
logDebug(s"Getting remote block $blockId from $loc")
// 使用blockTransferService进行，异步的远程网络获取，将block数据传输过来
// 连接的时候，使用BlockManager的唯一标识，就是host，port，executorId
val data = blockTransferService.fetchBlockSync(
loc.host, loc.port, loc.executorId, blockId.toString).nioByteBuffer()
if (data != null) {
if (asBlockResult) {
return Some(new BlockResult(
dataDeserialize(blockId, data),
DataReadMethod.Network,
data.limit()))
} else {
return Some(data)
}
}
logDebug(s"The value of block $blockId is null")
}
logDebug(s"Block $blockId not found")
None
}
看看DiskStore的getBytes()方法
private def getBytes(file: File, offset: Long, length: Long): Option[ByteBuffer] = {
// 底层使用的是java的nio进行文件的读写操作
val channel = new RandomAccessFile(file, "r").getChannel
try {
// For small files, directly read rather than memory map
if (length < minMemoryMapBytes) {
val buf = ByteBuffer.allocate(length.toInt)
channel.position(offset)
while (buf.remaining() != 0) {
if (channel.read(buf) == -1) {
throw new IOException("Reached EOF before filling buffer\n" +
s"offset=$offset\nfile=${file.getAbsolutePath}\nbuf.remaining=${buf.remaining}")
}
}
buf.flip()
Some(buf)
} else {
Some(channel.map(MapMode.READ_ONLY, offset, length))
}
} finally {
channel.close()
}
}
MemoryStore的getBytes()和getValues()方法
override def getBytes(blockId: BlockId): Option[ByteBuffer] = {
// entries也是多线程并发访问同步的
val entry = entries.synchronized {
// 尝试从内存中获取block数据
entries.get(blockId)
}
if (entry == null) {
// 如果没有获取到 就返回None
None
} else if (entry.deserialized) {
// 如果读取到了非序列化的数据，调用BlockManager序列化方法，将数据序列化后返回
Some(blockManager.dataSerialize(blockId, entry.value.asInstanceOf[Array[Any]].iterator))
} else {
// 否则，直接返回数据
Some(entry.value.asInstanceOf[ByteBuffer].duplicate()) // Doesn't actually copy the data
}
}
override def getValues(blockId: BlockId): Option[Iterator[Any]] = {
val entry = entries.synchronized {
entries.get(blockId)
}
if (entry == null) {
None
} else if (entry.deserialized) {
// 如果非序列化，直接返回
Some(entry.value.asInstanceOf[Array[Any]].iterator)
} else {
// 如果序列化了，那么用blockManager进行反序列化返回
val buffer = entry.value.asInstanceOf[ByteBuffer].duplicate() // Doesn't actually copy data
Some(blockManager.dataDeserialize(blockId, buffer))
}
}