Hi guys, After waiting for a day, it actually causes OOM on the spark driver. I configure the driver to have 6GB. Note that I didn't call refresh myself. The method was called when saving the dataframe in parquet format. Also I'm using partitionBy() on the DataFrameWriter to generate over 1 million files. Not sure why it OOM the driver after the job is marked _SUCCESS in the output folder.
Best Regards, Jerry On Sat, Oct 24, 2015 at 9:35 PM, Jerry Lam <chiling...@gmail.com> wrote: > Hi Spark users and developers, > > Does anyone encounter any issue when a spark SQL job produces a lot of > files (over 1 millions), the job hangs on the refresh method? I'm using > spark 1.5.1. Below is the stack trace. I saw the parquet files are produced > but the driver is doing something very intensively (it uses all the cpus). > Does it mean Spark SQL cannot be used to produce over 1 million files in a > single job? > > Thread 528: (state = BLOCKED) > - java.util.Arrays.copyOf(char[], int) @bci=1, line=2367 (Compiled frame) > - java.lang.AbstractStringBuilder.expandCapacity(int) @bci=43, line=130 > (Compiled frame) > - java.lang.AbstractStringBuilder.ensureCapacityInternal(int) @bci=12, > line=114 (Compiled frame) > - java.lang.AbstractStringBuilder.append(java.lang.String) @bci=19, > line=415 (Compiled frame) > - java.lang.StringBuilder.append(java.lang.String) @bci=2, line=132 > (Compiled frame) > - org.apache.hadoop.fs.Path.toString() @bci=128, line=384 (Compiled frame) > - > org.apache.spark.sql.sources.HadoopFsRelation$FileStatusCache$$anonfun$listLeafFiles$1.apply(org.apache.hadoop.fs.FileStatus) > @bci=4, line=447 (Compiled frame) > - > org.apache.spark.sql.sources.HadoopFsRelation$FileStatusCache$$anonfun$listLeafFiles$1.apply(java.lang.Object) > @bci=5, line=447 (Compiled frame) > - scala.collection.TraversableLike$$anonfun$map$1.apply(java.lang.Object) > @bci=9, line=244 (Compiled frame) > - scala.collection.TraversableLike$$anonfun$map$1.apply(java.lang.Object) > @bci=2, line=244 (Compiled frame) > - > scala.collection.IndexedSeqOptimized$class.foreach(scala.collection.IndexedSeqOptimized, > scala.Function1) @bci=22, line=33 (Compiled frame) > - scala.collection.mutable.ArrayOps$ofRef.foreach(scala.Function1) > @bci=2, line=108 (Compiled frame) > - > scala.collection.TraversableLike$class.map(scala.collection.TraversableLike, > scala.Function1, scala.collection.generic.CanBuildFrom) @bci=17, line=244 > (Compiled frame) > - scala.collection.mutable.ArrayOps$ofRef.map(scala.Function1, > scala.collection.generic.CanBuildFrom) @bci=3, line=108 (Interpreted frame) > - > org.apache.spark.sql.sources.HadoopFsRelation$FileStatusCache.listLeafFiles(java.lang.String[]) > @bci=279, line=447 (Interpreted frame) > - org.apache.spark.sql.sources.HadoopFsRelation$FileStatusCache.refresh() > @bci=8, line=453 (Interpreted frame) > - > org.apache.spark.sql.sources.HadoopFsRelation.org$apache$spark$sql$sources$HadoopFsRelation$$fileStatusCache$lzycompute() > @bci=26, line=465 (Interpreted frame) > - > org.apache.spark.sql.sources.HadoopFsRelation.org$apache$spark$sql$sources$HadoopFsRelation$$fileStatusCache() > @bci=12, line=463 (Interpreted frame) > - org.apache.spark.sql.sources.HadoopFsRelation.refresh() @bci=1, > line=540 (Interpreted frame) > - > org.apache.spark.sql.execution.datasources.parquet.ParquetRelation.refresh() > @bci=1, line=204 (Interpreted frame) > - > org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply$mcV$sp() > @bci=392, line=152 (Interpreted frame) > - > org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply() > @bci=1, line=108 (Interpreted frame) > - > org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1.apply() > @bci=1, line=108 (Interpreted frame) > - > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(org.apache.spark.sql.SQLContext, > org.apache.spark.sql.SQLContext$QueryExecution, scala.Function0) @bci=96, > line=56 (Interpreted frame) > - > org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(org.apache.spark.sql.SQLContext) > @bci=718, line=108 (Interpreted frame) > - > org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute() > @bci=20, line=57 (Interpreted frame) > - org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult() > @bci=15, line=57 (Interpreted frame) > - org.apache.spark.sql.execution.ExecutedCommand.doExecute() @bci=12, > line=69 (Interpreted frame) > - org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply() > @bci=11, line=140 (Interpreted frame) > - org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply() > @bci=1, line=138 (Interpreted frame) > - > org.apache.spark.rdd.RDDOperationScope$.withScope(org.apache.spark.SparkContext, > java.lang.String, boolean, boolean, scala.Function0) @bci=131, line=147 > (Interpreted frame) > - org.apache.spark.sql.execution.SparkPlan.execute() @bci=189, line=138 > (Interpreted frame) > - org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute() > @bci=21, line=933 (Interpreted frame) > - org.apache.spark.sql.SQLContext$QueryExecution.toRdd() @bci=13, > line=933 (Interpreted frame) > - > org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(org.apache.spark.sql.SQLContext, > java.lang.String, java.lang.String[], org.apache.spark.sql.SaveMode, > scala.collection.immutable.Map, org.apache.spark.sql.DataFrame) @bci=293, > line=197 (Interpreted frame) > - org.apache.spark.sql.DataFrameWriter.save() @bci=64, line=146 > (Interpreted frame) > - org.apache.spark.sql.DataFrameWriter.save(java.lang.String) @bci=24, > line=137 (Interpreted frame) > - org.apache.spark.sql.DataFrameWriter.parquet(java.lang.String) @bci=8, > line=304 (Interpreted frame) > > Best Regards, > > Jerry > > >
