[jira] [Resolved] (SPARK-6334) spark-local dir not getting cleared during ALS
[ https://issues.apache.org/jira/browse/SPARK-6334?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng resolved SPARK-6334. -- Resolution: Duplicate I marked this one as duplicated as the solution will be provided by SPARK-6717. > spark-local dir not getting cleared during ALS > -- > > Key: SPARK-6334 > URL: https://issues.apache.org/jira/browse/SPARK-6334 > Project: Spark > Issue Type: Bug > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Antony Mayi > Attachments: als-diskusage.png, gc.png > > > when running bigger ALS training spark spills loads of temp data into the > local-dir (in my case yarn/local/usercache/antony.mayi/appcache/... - running > on YARN from cdh 5.3.2) eventually causing all the disks of all nodes running > out of space (in my case I have 12TB of available disk capacity before > kicking off the ALS but it all gets used (and yarn kills the containers when > reaching 90%). > even with all recommended options (configuring checkpointing and forcing GC > when possible) it still doesn't get cleared. > here is my (pseudo)code (pyspark): > {code} > sc.setCheckpointDir('/tmp') > training = > sc.pickleFile('/tmp/dataset').repartition(768).persist(StorageLevel.MEMORY_AND_DISK) > model = ALS.trainImplicit(training, 50, 15, lambda_=0.1, blocks=-1, alpha=40) > sc._jvm.System.gc() > {code} > the training RDD has about 3.5 billions of items (~60GB on disk). after about > 6 hours the ALS will consume all 12TB of disk space in local-dir data and > gets killed. my cluster has 192 cores, 1.5TB RAM and for this task I am using > 37 executors of 4 cores/28+4GB RAM each. > this is the graph of disk consumption pattern showing the space being all > eaten from 7% to 90% during the ALS (90% is when YARN kills the container): > !als-diskusage.png! -- 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
[jira] [Resolved] (SPARK-6334) spark-local dir not getting cleared during ALS
[ https://issues.apache.org/jira/browse/SPARK-6334?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiangrui Meng resolved SPARK-6334. -- Resolution: Duplicate SPARK-5955 was merged. So if you can use the latest master, you can set checkpoint interval to control the shuffle files. I'm closing this issue since there exists a workaround and it is fixed in master. > spark-local dir not getting cleared during ALS > -- > > Key: SPARK-6334 > URL: https://issues.apache.org/jira/browse/SPARK-6334 > Project: Spark > Issue Type: Bug > Components: MLlib >Affects Versions: 1.2.0 >Reporter: Antony Mayi > Attachments: als-diskusage.png > > > when running bigger ALS training spark spills loads of temp data into the > local-dir (in my case yarn/local/usercache/antony.mayi/appcache/... - running > on YARN from cdh 5.3.2) eventually causing all the disks of all nodes running > out of space (in my case I have 12TB of available disk capacity before > kicking off the ALS but it all gets used (and yarn kills the containers when > reaching 90%). > even with all recommended options (configuring checkpointing and forcing GC > when possible) it still doesn't get cleared. > here is my (pseudo)code (pyspark): > {code} > sc.setCheckpointDir('/tmp') > training = > sc.pickleFile('/tmp/dataset').repartition(768).persist(StorageLevel.MEMORY_AND_DISK) > model = ALS.trainImplicit(training, 50, 15, lambda_=0.1, blocks=-1, alpha=40) > sc._jvm.System.gc() > {code} > the training RDD has about 3.5 billions of items (~60GB on disk). after about > 6 hours the ALS will consume all 12TB of disk space in local-dir data and > gets killed. my cluster has 192 cores, 1.5TB RAM and for this task I am using > 37 executors of 4 cores/28+4GB RAM each. > this is the graph of disk consumption pattern showing the space being all > eaten from 7% to 90% during the ALS (90% is when YARN kills the container): > !als-diskusage.png! -- 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