Thanks everyone for your help in advance! I am very new to Spark and have been using Databricks (Runtime Version 5.0, includes Apache Spark 2.4.0, Scala 2.11).
I have been trying to load some XML files using spark-xml (2.11.0.5.0), and encountering the following sparkException:
org.apache.spark.SparkException: Job aborted due to stage failure:
Task 5 in stage 0.0 failed 4 times, most recent failure: Lost task
5.3 in stage 0.0 (TID 17, 10.106.234.32, executor 0):
java.lang.NullPointerException
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:37)
at com.databricks.spark.xml.XmlRecordReader.readUntilStartElement(XmlInputFormat.scala:156)
at com.databricks.spark.xml.XmlRecordReader.next(XmlInputFormat.scala:131)
at com.databricks.spark.xml.XmlRecordReader.nextKeyValue(XmlInputFormat.scala:119)
at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:236)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithoutKey_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:619)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.run(Task.scala:124)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$11.apply(Executor.scala:459)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1401)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:465)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
It is weird that there was no issue loading the files the day before using exact same configs of the cluster:
- Databricks runtime version: 5.0 (includes Apache Spark 2.4.0, Scala 2.11)
- Driver and worker type: i3.xlarge - 30.5 GB Memory, 4 Cores, 1 DBU
Each of the uncompressed XML files range from 70M to 130M in size and there are 8 of them. I hope to load them into one dataset.
I got the data as follows and uploaded them to Databricks:
wget ftp://ftp.nlm.nih.gov/nlmdata/sample/medline/*.gz
gunzip *.gz
Here is the code:
import com.databricks.spark.xml._
import org.apache.spark.sql.{Dataset, SparkSession}
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.io.{Text, LongWritable}
def loadMedline(spark: SparkSession, path: String) = {
import spark.implicits._
/* conf: org.apache.hadoop.conf.Configuration = Configuration:
* core-default.xml, core-site.xml, mapred-default.xml,
* mapred-site.xml, yarn-default.xml, yarn-site.xml,
* hdfs-default.xml, hdfs-site.xml
*/
@transient val conf = new Configuration()
conf.set(XmlInputFormat.START_TAG_KEY, "<MedlineCitation>")
conf.set(XmlInputFormat.END_TAG_KEY, "</MedlineCitation>")
/* sc: org.apache.spark.SparkContext */
val sc = spark.sparkContext
/* records: org.apache.spark.rdd.RDD[(org.apache.hadoop.io.LongWritable, org.apache.hadoop.io.Text)] =
* dbfs:/FileStore/tables/ch7_medline/ NewHadoopRDD[0] at newAPIHadoopFile at command-2335143412865645:1
*/
val records = sc.newAPIHadoopFile(path, classOf[XmlInputFormat],
classOf[LongWritable], classOf[Text])
/* returns: org.apache.spark.sql.Dataset[String] = [value: string] */
records.map(line => line._2.toString).toDS()
}
/* medlineRaw: org.apache.spark.sql.Dataset[String] = [value: string] */
val medlineRaw = loadMedline(spark, "dbfs:/FileStore/tables/ch7_medline/")
medlineRaw.count() // <--- got the error here
Again thank you very much! Looked around for quite a while but still couldn't get it working.