Errors when using OFF_HEAP Storage with Spark 1.4.0 and Tachyon 0.6.4

Question

I am trying to save my RDD using heap storage on spark 1.4.0 and tachyon 0.6.4, doing this as follows:

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

Subsequently, I get the following exception.

Any ideas on this?

 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 also tried the same with a text file and I was able to save it in tachyon. The problem is that the DataFrame is initially read from the floor.

Answer 1

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

Since there is a pull request for this, there may be a chance to fix this soon.

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

Answer 2

This issue has been fixed. I can confirm that this now works with Spark 1.5 and Tachyon 0.7