ā08-23-2022 09:21 AM
We are getting the below error for runtime 10.x and 11.x when writing to s3 via saveAsNewAPIHadoopFile function. The same jobs are running fine on runtime 9.x and 7.x. The difference betwen 9.x and 10.x is the former has hadoop 2.7 bindings with spark 3.1 whereas latter has hadoop 3.2 bindings with spark 3.2. Is databricks runtime missing some jars? Any help is appreciated.
java.lang.RuntimeException: java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3a.commit.S3ACommitterFactory not found
at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2720)
at org.apache.hadoop.mapreduce.lib.output.PathOutputCommitterFactory.getCommitterFactory(PathOutputCommitterFactory.java:179)
at org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.getOutputCommitter(FileOutputFormat.java:336)
at org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.setupCommitter(HadoopMapReduceCommitProtocol.scala:116)
at org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.setupJob(HadoopMapReduceCommitProtocol.scala:195)
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:83)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsNewAPIHadoopDataset$1(PairRDDFunctions.scala:1078)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:125)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:411)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopDataset(PairRDDFunctions.scala:1076)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsNewAPIHadoopFile$2(PairRDDFunctions.scala:995)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:125)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:411)
at org.apache.spark.rdd.PairRDDFunctions.saveAsNewAPIHadoopFile(PairRDDFunctions.scala:986)
ā08-23-2022 01:48 PM
Why are you using that saveAsNewAPI function?
ā08-23-2022 02:27 PM
We have some internal OutputFileFormatter for mainframe and fixedlength data formats to support our Data Integration and Data Quality tools. We have been using them for legacy reasons and it was working till 9.x runtime version.
ā08-27-2022 11:48 AM
We can reproduce the above error for runtime 10.x and 11.x using the below code in a notebook.
import org.apache.hadoop.io.IntWritable
import org.apache.hadoop.io.Text
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat
import org.apache.spark.rdd.PairRDDFunctions
val l = List((10,"a"),(20,"b"),(30,"c"),(40,"d"))
val rdd = sc.parallelize(l)
val rddWritable = rdd.map(x=> (new IntWritable(x._1), new Text(x._2)))
val pairRDD = new PairRDDFunctions(rddWritable)
pairRDD.saveAsNewAPIHadoopFile("s3a://bucket/testout.dat",
classOf[IntWritable],
classOf[Text],
classOf[TextOutputFormat[IntWritable,Text]],
spark.sparkContext.hadoopConfiguration)
ā08-28-2022 09:25 AM
We have resolved this issue by using s3 scheme instead of s3a i.e. pairRDD.saveAsNewAPIHadoopFile("s3://bucket/testout.dat",
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