【转】Spark源码分析之-Storage模块

原文地址：http://blog.csdn.net/aiuyjerry/article/details/8595991

Storage模块主要负责数据存取，包括MapReduce Shuffle中间结果、MapReduce task中间stage结果、cache结果。下面从架构和源码细节上来分析Storage模块的实现。Storage模块主要由两大部分组成：

• BlockManager部分主要负责Master和Slave之间的block通信，主要包括BlockManager状态上报、心跳，add, remove, update block.
• BlockStore部分主要负责数据存取，Spark根据不同选择可以在Memory或(和)Disk中存储序列化数据.

Storage模块类图如下所示：

       

• SparkEnv创建时会实例化BlockManagerMaster对象和BlockManager对象。
• BlockManagerMaster对象会根据自己是master还是slave来创建BlockManagerMasterActor或是连接到BlockManagerMasterActor。
• BlockManager承担两种角色：
• 1. 负责向BlockManagerMaster上报block信息，保持心跳和接收block信息
  2. 负责通过BlockStore从Memory或Disk读取、写入block数据
• BlockManagerMessages封装与master传输的meta信息的具体格式。
• Slave通过BlockManager向BlockManagerMaster注册自己，在注册自己时会创建BlockManagerSlaveActor，用来Master向Slave通信，目前唯一request是请求Slave删除block。
• BlockManagerWorker则负责Slave之间的通信，包括get, put非本地的block
• BlockMessage类封装了与Master通信的block message的具体格式，而BlockMessageArray则是批处理接口。
• BlockStore提供持久化数据的接口，DiskStore和MemoryStore实例化了BlockStore接口，实现serialize, deserialize数据到Disk或Memory。

 

Spark Storage模块master和slave之间通信的信息包括：

• Slave -------->  Master
• • RegisterBlockManager
  • HeartBeat
  • UpdateBlockInfo
  • GetLocations
  • GetLocationsMutipleBlockIds
  • GetPeers
  • RemoveExecutor
  • StopBlockManagerMaster
  • GetMemoryStatus
  • ExpireDeadHosts
  • GetStorageStatus
• Master ---------> Slave
• • RemoveBlock

 

Storage模块存取数据分析

MemoryStore：

    Memory内部使用LinkedHashMap来作为block的存储结构，其中key是block id，value是Entry类，代码如所示:

  case class Entry(value: Any, size: Long, deserialized: Boolean, var dropPending: Boolean = false)
  private val entries = new LinkedHashMap[String, Entry](32, 0.75f, true)

而内部存储会调用如下代码：

  private def tryToPut(blockId: String, value: Any, size: Long, deserialized: Boolean): Boolean = {
    putLock.synchronized {
      if (ensureFreeSpace(blockId, size)) {
        val entry = new Entry(value, size, deserialized)
        entries.synchronized { entries.put(blockId, entry) }
        currentMemory += size
        if (deserialized) {
          logInfo("Block %s stored as values to memory (estimated size %s, free %s)".format(
            blockId, Utils.memoryBytesToString(size), Utils.memoryBytesToString(freeMemory)))
        } else {
          logInfo("Block %s stored as bytes to memory (size %s, free %s)".format(
            blockId, Utils.memoryBytesToString(size), Utils.memoryBytesToString(freeMemory)))
        }
        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[ArrayBuffer[Any]])
        } else {
          Right(value.asInstanceOf[ByteBuffer].duplicate())
        }
        blockManager.dropFromMemory(blockId, data)
        false
      }
    }
  }

  private def ensureFreeSpace(blockIdToAdd: String, space: Long): Boolean = {
    logInfo("ensureFreeSpace(%d) called with curMem=%d, maxMem=%d".format(
      space, currentMemory, maxMemory))

    if (space > maxMemory) {
      logInfo("Will not store " + blockIdToAdd + " as it is larger than our memory limit")
      return false
    }

    if (maxMemory - currentMemory < space) {
      val rddToAdd = getRddId(blockIdToAdd)
      val selectedBlocks = new ArrayBuffer[String]()
      var selectedMemory = 0L

      entries.synchronized {
        val iterator = entries.entrySet().iterator()
        while (maxMemory - (currentMemory - selectedMemory) < space && iterator.hasNext) {
          val pair = iterator.next()
          val blockId = pair.getKey
          if (rddToAdd != null && rddToAdd == getRddId(blockId)) {
            logInfo("Will not store " + blockIdToAdd + " as it would require dropping another " +
              "block from the same RDD")
            return false
          }
          selectedBlocks += blockId
          selectedMemory += pair.getValue.size
        }
      }

      if (maxMemory - (currentMemory - selectedMemory) >= space) {
        logInfo(selectedBlocks.size + " blocks selected for dropping")
        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[ArrayBuffer[Any]])
            } else {
              Right(entry.value.asInstanceOf[ByteBuffer].duplicate())
            }
            blockManager.dropFromMemory(blockId, data)
          }
        }
        return true
      } else {
        return false
      }
    }
    return true
  }

    tryToPut会调用ensureFreeSpace来淘汰掉一些block，为此block的存储释放新的空间，而tryToPut会将其添加到LinkedHashMap中。如果ensureFreeSpace无法获得足够的空间去存储此block，tryToPut会调用dropFreeMemory来drop此block。

 

DiskStore：

   Spark会根据配置项spark.local.dir在本地建立目录，所有的block都会依照不同路径存储到此目录下，当spark.local.dir中配置了多个path时，Spark会根据hash将block存储到不同的path下

• 首先，Spark会根据spark.local.dir的配置在所有配置目录下建立localDir，localDir命名为spark-local-%s-%04x,其中%s是格式化后的当前时间(yyyyMMddHHmmss)，%d是一个小于65535的随机16进制数字。
• 其次，每当要存储block时，Spark会根据blockId在localDir下建立子目录和相应的文件，block存储目录的选择规律是：
• 1. 根据blockId的hash值计算出dirId和subDirId
  2. 取出或创建subDir
  3. 在subDir下面以blockId为名字创建文件

    val subDirsPerLocalDir = System.getProperty("spark.diskStore.subDirectories", "64").toInt
    val subDirs = Array.fill(localDirs.length)(new Array[File](subDirsPerLocalDir))

    // Figure out which local directory it hashes to, and which subdirectory in that
    val hash = math.abs(blockId.hashCode)
    val dirId = hash % localDirs.length
    val subDirId = (hash / localDirs.length) % subDirsPerLocalDir

    // Create the subdirectory if it doesn't already exist
    var subDir = subDirs(dirId)(subDirId)
    if (subDir == null) {
      subDir = subDirs(dirId).synchronized {
        val old = subDirs(dirId)(subDirId)
        if (old != null) {
          old
        } else {
          val newDir = new File(localDirs(dirId), "%02x".format(subDirId))
          newDir.mkdir()
          subDirs(dirId)(subDirId) = newDir
          newDir
        }
      }
    }

    new File(subDir, blockId)

• 最后，根据压缩和序列化方式选择将block存储到文件中