Sidhartha created SPARK-26558:
---------------------------------
Summary: java.util.NoSuchElementException while saving data into
HDFS using Spark
Key: SPARK-26558
URL: https://issues.apache.org/jira/browse/SPARK-26558
Project: Spark
Issue Type: Bug
Components: Spark Core, Spark Submit
Affects Versions: 2.0.0
Reporter: Sidhartha
h1. How to fix java.util.NoSuchElementException while saving data into HDFS
using Spark ?
I'm trying to ingest a greenplum table into HDFS using spark-greenplum reader.
Below are the versions of Spark & Scala I am using:
spark-core: 2.0.0
spark-sql: 2.0.0
Scala version: 2.11.8
To do that, I wrote the following code:
{code:java}
val conf = new
SparkConf().setAppName("TEST_YEAR").set("spark.executor.heartbeatInterval",
"1200s") .set("spark.network.timeout", "12000s")
.set("spark.sql.inMemoryColumnarStorage.compressed", "true")
.set("spark.shuffle.compress", "true") .set("spark.shuffle.spill.compress",
"true") .set("spark.sql.orc.filterPushdown", "true") .set("spark.serializer",
"org.apache.spark.serializer.KryoSerializer")
.set("spark.kryoserializer.buffer.max", "512m") .set("spark.serializer",
classOf[org.apache.spark.serializer.KryoSerializer].getName)
.set("spark.streaming.stopGracefullyOnShutdown", "true")
.set("spark.yarn.driver.memoryOverhead", "8192")
.set("spark.yarn.executor.memoryOverhead", "8192")
.set("spark.sql.shuffle.partitions", "400")
.set("spark.dynamicAllocation.enabled", "false")
.set("spark.shuffle.service.enabled", "true")
.set("spark.sql.tungsten.enabled", "true") .set("spark.executor.instances",
"12") .set("spark.executor.memory", "13g") .set("spark.executor.cores", "4")
.set("spark.files.maxPartitionBytes", "268435468") val flagCol = "del_flag" val
spark =
SparkSession.builder().config(conf).master("yarn").enableHiveSupport().config("hive.exec.dynamic.partition",
"true").config("hive.exec.dynamic.partition.mode", "nonstrict").getOrCreate()
import spark.implicits._ val dtypes = spark.read.format("jdbc").option("url",
hiveMetaConURL).option("dbtable", "(select source_type, hive_type from
hivemeta.types) as gpHiveDataTypes").option("user",
metaUserName).option("password", metaPassword).load() val spColsDF =
spark.read.format("jdbc").option("url", hiveMetaConURL) .option("dbtable",
"(select source_columns, precision_columns, partition_columns from
hivemeta.source_table where tablename='gpschema.empdocs') as colsPrecision")
.option("user", metaUserName).option("password", metaPassword).load() val
dataMapper = dtypes.as[(String, String)].collect().toMap val gpCols =
spColsDF.select("source_columns").map(row =>
row.getString(0)).collect.mkString(",") val gpColumns =
gpCols.split("\\|").map(e => e.split("\\:")).map(s => s(0)).mkString(",") val
splitColumns = gpCols.split("\\|").toList val precisionCols =
spColsDF.select("precision_columns").collect().map(_.getString(0)).mkString(",")
val partition_columns = spColsDF.select("partition_columns").collect.flatMap(x
=> x.getAs[String](0).split(",")) val prtn_String_columns =
spColsDF.select("partition_columns").collect().map(_.getString(0)).mkString(",")
val partCList = prtn_String_columns.split(",").map(x => col(x)) var
splitPrecisionCols = precisionCols.split(",") for (i <- splitPrecisionCols) {
precisionColsText += i.concat(s"::${textType} as ").concat(s"${i}_text")
textList += s"${i}_text:${textType}" } val pCols =
precisionColsText.mkString(",") val allColumns = gpColumns.concat("," + pCols)
val allColumnsSeq = allColumns.split(",").toSeq val allColumnsSeqC =
allColumnsSeq.map(x => column(x)) val gpColSeq = gpColumns.split(",").toSeq def
prepareFinalDF(splitColumns: List[String], textList: ListBuffer[String],
allColumns: String, dataMapper: Map[String, String], partition_columns:
Array[String], spark: SparkSession): DataFrame = { val yearDF =
spark.read.format("io.pivotal.greenplum.spark.GreenplumRelationProvider").option("url",
connectionUrl) .option("dbtable", "empdocs") .option("dbschema","gpschema")
.option("user", devUserName).option("password", devPassword)
.option("partitionColumn","header_id") .load() .where("year=2017 and month=12")
.select(gpColSeq map col:_*) .withColumn(flagCol, lit(0)) val totalCols:
List[String] = splitColumns ++ textList val allColsOrdered =
yearDF.columns.diff(partition_columns) ++ partition_columns val allCols =
allColsOrdered.map(colname => org.apache.spark.sql.functions.col(colname)) val
resultDF = yearDF.select(allCols: _*) val stringColumns =
resultDF.schema.fields.filter(x => x.dataType == StringType).map(s => s.name)
val finalDF = stringColumns.foldLeft(resultDF) { (tempDF, colName) =>
tempDF.withColumn(colName, regexp_replace(regexp_replace(col(colName),
"[\r\n]+", " "), "[\t]+", " ")) } finalDF } val dataDF =
prepareFinalDF(splitColumns, textList, allColumns, dataMapper,
partition_columns, spark)
dataDF.write.format("csv").save("hdfs://usrdev/apps/hive/warehouse/empdocs/") }
}
{code}
When I submit the job, I see the tasks at below lines complete:
{code:java}
val dataMapper = dtypes.as[(String, String)].collect().toMap val gpCols =
spColsDF.select("source_columns").map(row =>
row.getString(0)).collect.mkString(",") val precisionCols =
spColsDF.select("precision_columns").collect().map(_.getString(0)).mkString(",")
val partition_columns = spColsDF.select("partition_columns").collect.flatMap(x
=> x.getAs[String](0).split(",")) val prtn_String_columns =
spColsDF.select("partition_columns").collect().map(_.getString(0)).mkString(",")
{code}
[link title|http://example.com/]
Once the task of saving the prepared dataframe starts, which is:
{noformat}
dataDF.write.format("csv").save("hdfs://usrdev/apps/hive/warehouse/empdocs/"){noformat}
job ends with the exception: \{{}}
{noformat}
java.util.NoSuchElementException{noformat}
I am submitting the job using below spark-submit command:
{code:java}
SPARK_MAJOR_VERSION=2 spark-submit --class com.partition.source.YearPartition
--master=yarn --conf spark.ui.port=4090 --driver-class-path
/home/hdpdevusr/jars/greenplum-spark_2.11-1.3.0.jar --conf
spark.jars=/home/hdpdevusr/jars/greenplum-spark_2.11-1.3.0.jar --executor-cores
3 --executor-memory 13G --keytab /home/hdpdevusr/hdpdevusr.keytab --principal
hdpdev...@usrdev.com --files
/usr/hdp/current/spark2-client/conf/hive-site.xml,testconnection.properties
--name Splinter --conf
spark.executor.extraClassPath=/home/hdpdevusr/jars/greenplum-spark_2.11-1.3.0.jar
splinter_2.11-0.1.jar{code}
I see the command launches the executors as per the specified numbers in the
code which is 12 executors with 4 cores each.
Only 5 out of 48 tasks will complete and the job ends with the exception:
{code:java}
[Stage 5:> (0 + 48) / 64]18/12/27 10:29:10 WARN TaskSetManager: Lost task 6.0
in stage 5.0 (TID 11, executor 11): java.util.NoSuchElementException: None.get
at scala.None$.get(Option.scala:347) at scala.None$.get(Option.scala:345) at
io.pivotal.greenplum.spark.jdbc.Jdbc$.copyTable(Jdbc.scala:43) at
io.pivotal.greenplum.spark.externaltable.GreenplumRowIterator.liftedTree1$1(GreenplumRowIterator.scala:110)
at
io.pivotal.greenplum.spark.externaltable.GreenplumRowIterator.<init>(GreenplumRowIterator.scala:109)
at io.pivotal.greenplum.spark.GreenplumRDD.compute(GreenplumRDD.scala:49) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at
org.apache.spark.scheduler.Task.run(Task.scala:108) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745) Caused by:
org.apache.spark.SparkException: Job 5 cancelled because killed via the Web UI
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1517)
at
org.apache.spark.scheduler.DAGScheduler.handleJobCancellation(DAGScheduler.scala:1457)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleStageCancellation$1.apply$mcVI$sp(DAGScheduler.scala:1446)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleStageCancellation$1.apply(DAGScheduler.scala:1439)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleStageCancellation$1.apply(DAGScheduler.scala:1439)
at
scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofInt.foreach(ArrayOps.scala:234) at
org.apache.spark.scheduler.DAGScheduler.handleStageCancellation(DAGScheduler.scala:1439)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1701)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630) at
org.apache.spark.SparkContext.runJob(SparkContext.scala:2029) at
org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply$mcV$sp(FileFormatWriter.scala:186)
... 44 more 18/12/27 10:30:53 WARN ShutdownHookManager: ShutdownHook '$anon$2'
timeout, java.util.concurrent.TimeoutException
java.util.concurrent.TimeoutException at
java.util.concurrent.FutureTask.get(FutureTask.java:205) at
org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:67)
18/12/27 10:30:53 ERROR Utils: Uncaught exception in thread pool-6-thread-1
java.lang.InterruptedException at java.lang.Object.wait(Native Method) at
java.lang.Thread.join(Thread.java:1249) at
java.lang.Thread.join(Thread.java:1323) at
org.apache.spark.scheduler.LiveListenerBus.stop(LiveListenerBus.scala:199) at
org.apache.spark.SparkContext$$anonfun$stop$6.apply$mcV$sp(SparkContext.scala:1919)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1317) at
org.apache.spark.SparkContext.stop(SparkContext.scala:1918) at
org.apache.spark.SparkContext$$anonfun$2.apply$mcV$sp(SparkContext.scala:581)
at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:216)
at
org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ShutdownHookManager.scala:188)
at
org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188)
at
org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:188)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1948) at
org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply$mcV$sp(ShutdownHookManager.scala:188)
at
org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188)
at
org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:188)
at scala.util.Try$.apply(Try.scala:192) at
org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:188)
at
org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:178)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at
java.util.concurrent.FutureTask.run(FutureTask.java:266) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745){code}
I don't understand where did it go wrong whether in code or in any
configuration applied in the job.
I posted the same on Stackoverflow as well. For executor images, the below link
can be referred:[
https://stackoverflow.com/questions/54002002/how-to-fix-java-util-nosuchelementexception-while-saving-data-into-hdfs-using-sp/54002423?noredirect=1#comment94843141_54002423|http://example.com]
Could anyone let me know how to fix this exception ?
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