使用带有Spark 1.4.0和Tachyon 0.6.4的OFF_HEAP存储时出错

Question

我试图在spark 1.4.0和tachyon 0.6.4上使用off heap storage来保持我的RDD这样做:

val a = sqlContext.parquetFile("a1.parquet")
a.persist(org.apache.spark.storage.StorageLevel.OFF_HEAP)
a.count()

之后我得到以下异常.

有什么想法吗？

15/06/16 10:14:53 INFO : Tachyon client (version 0.6.4) is trying to connect master @ localhost/127.0.0.1:19998
15/06/16 10:14:53 INFO : User registered at the master localhost/127.0.0.1:19998 got UserId 3
15/06/16 10:14:53 INFO TachyonBlockManager: Created tachyon directory at /tmp_spark_tachyon/spark-6b2512ab-7bb8-47ca-b6e2-8023d3d7f7dc/driver/spark-tachyon-20150616101453-ded3
15/06/16 10:14:53 INFO BlockManagerInfo: Added rdd_10_3 on ExternalBlockStore on localhost:33548 (size: 0.0 B)
15/06/16 10:14:53 INFO BlockManagerInfo: Added rdd_10_1 on ExternalBlockStore on localhost:33548 (size: 0.0 B)
15/06/16 10:14:53 ERROR TransportRequestHandler: Error while invoking RpcHandler#receive() on RPC id 5710423667942934352
org.apache.spark.storage.BlockNotFoundException: Block rdd_10_3 not found
    at org.apache.spark.storage.BlockManager.getBlockData(BlockManager.scala:306)
    at org.apache.spark.network.netty.NettyBlockRpcServer$$anonfun$2.apply(NettyBlockRpcServer.scala:57)
    at org.apache.spark.network.netty.NettyBlockRpcServer$$anonfun$2.apply(NettyBlockRpcServer.scala:57)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
    at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
    at org.apache.spark.network.netty.NettyBlockRpcServer.receive(NettyBlockRpcServer.scala:57)
    at org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:114)
    at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:87)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:101)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319)
    at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:254)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333)

我也尝试了同样的文本文件,我能够在tachyon中坚持它.问题是持久化DataFrame最初从镶木地板中读取.

Answer 1

似乎有一个相关的错误报告：https://issues.apache.org/jira/browse/SPARK-10314

由于似乎有一个针对此问题的拉取请求，因此可能有机会很快修复此问题。

从这个线程https://groups.google.com/forum/#!topic/tachyon-users/xb8zwqIjIa4来看，Spark 似乎正在使用 TRY_CACHE 模式写入 Tachyon，因此当从缓存中逐出时，数据似乎会丢失。