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Dibyendu Bhattacharya commented on SPARK-7477: ---------------------------------------------- I tried Hierarchical Storage on Tachyon ( http://tachyon-project.org/Hierarchy-Storage-on-Tachyon.html ) , and that seems to have worked and I did not see any any Spark Job failed due to BlockNotFoundException. below is my Hierarchical Storage settings.. -Dtachyon.worker.hierarchystore.level.max=2 -Dtachyon.worker.hierarchystore.level0.alias=MEM -Dtachyon.worker.hierarchystore.level0.dirs.path=$TACHYON_RAM_FOLDER -Dtachyon.worker.hierarchystore.level0.dirs.quota=$TACHYON_WORKER_MEMORY_SIZE -Dtachyon.worker.hierarchystore.level1.alias=HDD -Dtachyon.worker.hierarchystore.level1.dirs.path=/mnt/tachyon -Dtachyon.worker.hierarchystore.level1.dirs.quota=50GB -Dtachyon.worker.allocate.strategy=MAX_FREE -Dtachyon.worker.evict.strategy=LRU > TachyonBlockManager Store Block in TRY_CACHE mode which gives > BlockNotFoundException when blocks are evicted from cache > ----------------------------------------------------------------------------------------------------------------------- > > Key: SPARK-7477 > URL: https://issues.apache.org/jira/browse/SPARK-7477 > Project: Spark > Issue Type: Bug > Components: Block Manager > Affects Versions: 1.4.0 > Reporter: Dibyendu Bhattacharya > > With Spark Streaming on Tachyon as the OFF_HEAP block store > I have used the low level Receiver based Kafka consumer > (http://spark-packages.org/package/dibbhatt/kafka-spark-consumer) for Spark > Streaming to pull from Kafka and write Blocks to Tachyon > What I see TachyonBlockManager.scala put the blocks in WriteType.TRY_CACHE > configuration . And because of this Blocks ate evicted from Tachyon Cache and > when Spark try to find the block it throws BlockNotFoundException . > When I modified the WriteType to CACHE_THROUGH , BlockDropException is gone , > but it impact the throughput .. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org