Errors when using OFF_HEAP Storage with Spark 1.4.0 and Tachyon 0.6.4

Question

I am trying to persist my RDD using off heap storage on spark 1.4.0 and tachyon 0.6.4 doing it like this :

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

Afterwards I am getting the following exception.

Any ideas on that?

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) 

I have also tried the same with the text file and I was able to persist it in tachyon. The problem is with persisting DataFrame originally read from parquet.

Answer 1

There seems to be a related bug report: https://issues.apache.org/jira/browse/SPARK-10314

Since there seems to be a pull request for this, there might be a chance to soon get a fix for this.

From this thread, https://groups.google.com/forum/#!topic/tachyon-users/xb8zwqIjIa4, it looks like Spark is using TRY_CACHE mode to write to Tachyon so the data seems to get lost when evicted from the cache.