我试图在spark 1.4.0和tachyon 0.6.4上使用off heap storage来保存我的RDD,就像这样:
val a = sqlContext.parquetFile("a1.parquet")
a.persist(org.apache.spark.storage.StorageLevel.OFF_HEAP)
a.count()
之后我收到以下异常。
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)
我也尝试过同样的文本文件,我能够在tachyon中坚持下去。问题是持久化DataFrame最初从镶木地板中读取。
答案 0 :(得分:1)
似乎有相关的错误报告:https://issues.apache.org/jira/browse/SPARK-10314
由于似乎有一个拉取请求,因此很可能很快得到修复。
在这个帖子https://groups.google.com/forum/#!topic/tachyon-users/xb8zwqIjIa4中,看起来Spark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。
答案 1 :(得分:0)
此问题现已解决。 我现在可以用Spark 1.5和Tachyon 0.7确认这个工作。