How much machines are there in your standalone cluster? I am not using tachyon.
GC can not help me... Can anyone help ? my configuration: spark.deploy.spreadOut false spark.eventLog.enabled true spark.executor.cores 24 spark.ui.retainedJobs 10 spark.ui.retainedStages 10 spark.history.retainedApplications 5 spark.deploy.retainedApplications 10 spark.deploy.retainedDrivers 10 spark.streaming.ui.retainedBatches 10 spark.sql.thriftserver.ui.retainedSessions 10 spark.sql.thriftserver.ui.retainedStatements 100 spark.file.transferTo false spark.driver.maxResultSize 4g spark.sql.hive.metastore.jars=/spark/spark-1.4.1/hive/* spark.eventLog.dir hdfs://mycluster/user/spark/historylog spark.history.fs.logDirectory hdfs://mycluster/user/spark/historylog spark.driver.extraClassPath=/spark/spark-1.4.1/extlib/* spark.executor.extraClassPath=/spark/spark-1.4.1/extlib/* spark.sql.parquet.binaryAsString true spark.serializer org.apache.spark.serializer.KryoSerializer spark.kryoserializer.buffer 32 spark.kryoserializer.buffer.max 256 spark.shuffle.consolidateFiles true spark.io.compression.codec org.apache.spark.io.LZ4CompressionCodec ------------------ ???????? ------------------ ??????: "Igor Berman";<igor.ber...@gmail.com>; ????????: 2015??8??3??(??????) ????7:56 ??????: "Sea"<261810...@qq.com>; ????: "Barak Gitsis"<bar...@similarweb.com>; "Ted Yu"<yuzhih...@gmail.com>; "user@spark.apache.org"<user@spark.apache.org>; "rxin"<r...@databricks.com>; "joshrosen"<joshro...@databricks.com>; "davies"<dav...@databricks.com>; ????: Re: About memory leak in spark 1.4.1 in general, what is your configuration? use --conf "spark.logConf=true" we have 1.4.1 in production standalone cluster and haven't experienced what you are describingcan you verify in web-ui that indeed spark got your 50g per executor limit? I mean in configuration page.. might be you are using offheap storage(Tachyon)? On 3 August 2015 at 04:58, Sea <261810...@qq.com> wrote: "spark uses a lot more than heap memory, it is the expected behavior." It didn't exist in spark 1.3.x What does "a lot more than" means? It means that I lose control of it! I try to apply 31g, but it still grows to 55g and continues to grow!!! That is the point! I have tried set memoryFraction to 0.2??but it didn't help. I don't know whether it will still exist in the next release 1.5, I wish not. ------------------ ???????? ------------------ ??????: "Barak Gitsis";<bar...@similarweb.com>; ????????: 2015??8??2??(??????) ????9:55 ??????: "Sea"<261810...@qq.com>; "Ted Yu"<yuzhih...@gmail.com>; ????: "user@spark.apache.org"<user@spark.apache.org>; "rxin"<r...@databricks.com>; "joshrosen"<joshro...@databricks.com>; "davies"<dav...@databricks.com>; ????: Re: About memory leak in spark 1.4.1 spark uses a lot more than heap memory, it is the expected behavior.in 1.4 off-heap memory usage is supposed to grow in comparison to 1.3 Better use as little memory as you can for heap, and since you are not utilizing it already, it is safe for you to reduce it. memoryFraction helps you optimize heap usage for your data/application profile while keeping it tight. On Sun, Aug 2, 2015 at 12:54 PM Sea <261810...@qq.com> wrote: spark.storage.memoryFraction is in heap memory, but my situation is that the memory is more than heap memory ! Anyone else use spark 1.4.1 in production? ------------------ ???????? ------------------ ??????: "Ted Yu";<yuzhih...@gmail.com>; ????????: 2015??8??2??(??????) ????5:45 ??????: "Sea"<261810...@qq.com>; ????: "Barak Gitsis"<bar...@similarweb.com>; "user@spark.apache.org"<user@spark.apache.org>; "rxin"<r...@databricks.com>; "joshrosen"<joshro...@databricks.com>; "davies"<dav...@databricks.com>; ????: Re: About memory leak in spark 1.4.1 http://spark.apache.org/docs/latest/tuning.html does mention spark.storage.memoryFraction in two places. One is under Cache Size Tuning section. FYI On Sun, Aug 2, 2015 at 2:16 AM, Sea <261810...@qq.com> wrote: Hi, Barak It is ok with spark 1.3.0, the problem is with spark 1.4.1. I don't think spark.storage.memoryFraction will make any sense, because it is still in heap memory. ------------------ ???????? ------------------ ??????: "Barak Gitsis";<bar...@similarweb.com>; ????????: 2015??8??2??(??????) ????4:11 ??????: "Sea"<261810...@qq.com>; "user"<user@spark.apache.org>; ????: "rxin"<r...@databricks.com>; "joshrosen"<joshro...@databricks.com>; "davies"<dav...@databricks.com>; ????: Re: About memory leak in spark 1.4.1 Hi,reducing spark.storage.memoryFraction did the trick for me. Heap doesn't get filled because it is reserved.. My reasoning is: I give executor all the memory i can give it, so that makes it a boundary. From here i try to make the best use of memory I can. storage.memoryFraction is in a sense user data space. The rest can be used by the system. If you don't have so much data that you MUST store in memory for performance, better give spark more space.. ended up setting it to 0.3 All that said, it is on spark 1.3 on cluster hope that helps On Sat, Aug 1, 2015 at 5:43 PM Sea <261810...@qq.com> wrote: Hi, all I upgrage spark to 1.4.1, many applications failed... I find the heap memory is not full , but the process of CoarseGrainedExecutorBackend will take more memory than I expect, and it will increase as time goes on, finally more than max limited of the server, the worker will die..... Any can help?? Mode??standalone spark.executor.memory 50g 25583 xiaoju 20 0 75.5g 55g 28m S 1729.3 88.1 2172:52 java 55g more than 50g I apply -- -Barak -- -Barak
