[jira] [Updated] (SPARK-36917) java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.rdd.MapPartitionsRDD.f of type scala.Function3 in instance of org.apache.spark.rdd.MapPartitionsRDD

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-36917?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-36917:
---------------------------------
    Target Version/s:   (was: 3.1.2)

> java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.rdd.MapPartitionsRDD.f of type scala.Function3 in instance of org.apache.spark.rdd.MapPartitionsRDD
> -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-36917
>                 URL: https://issues.apache.org/jira/browse/SPARK-36917
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core, Spark Submit
>    Affects Versions: 3.1.2
>         Environment: Ubuntu 20
> Spark3.1.2-hadoop3.2
> Hadoop 3.1
>            Reporter: Davide Benedetto
>            Priority: Major
>              Labels: hadoop, java, serializable, spark, spark-conf, ubuntu
>
> My spark Job fails with this error:
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (davben-lubuntu executor 2): java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.rdd.MapPartitionsRDD.f of type scala.Function3 in instance of org.apache.spark.rdd.MapPartitionsRDD
> My OS Linux Ubuntu 20 is in this way organized: I have two user: /home/davben and /home/hadoop. Into hadoop user I have installed hadoop 3.1 and spark-3.1.2-hadoop3.2.  Both users refers to java-8-openjdk Java installation. The Spark job is launched from user davben on eclipse IDE  in this way:
> I create the spark conf and the spark session
>  
> {code:java}
> System.setProperty("hadoop.home.dir", "/home/hadoop/hadoop");
> SparkConf sparkConf = new SparkConf()
> .setAppName("simple")
> .setMaster("yarn")
> .set("spark.executor.memory", "1g")
> .set("deploy.mode", "cluster")
> .set("spark.yarn.stagingDir", "hdfs://localhost:9000/user/hadoop/") .set("spark.hadoop.fs.defaultFS","hdfs://localhost:9000") .set("spark.hadoop.yarn.resourcemanager.hostname","localhost") .set("spark.hadoop.yarn.resourcemanager.scheduler.address","localhost:8030") .set("spark.hadoop.yarn.resourcemanager.address ","localhost:8032") .set("spark.hadoop.yarn.resourcemanager.webapp.address","localhost:8088") .set("spark.hadoop.yarn.resourcemanager.admin.address","localhost:8083")
> SparkSession spark = SparkSession.builder().config(sparkConf).getOrCreate();{code}
> Then I create a dataset with two entries:
>  
> {code:java}
> List<Row> rows = new ArrayList<>(); 
> rows.add(RowFactory.create("a", "b"));
> rows.add(RowFactory.create("a", "a"));
> StructType structType = new StructType(); 
> structType = structType.add("edge_1", DataTypes.StringType, false);
> structType = structType.add("edge_2", DataTypes.StringType, false); ExpressionEncoder<Row> edgeEncoder = RowEncoder.apply(structType);
> Dataset<Row> edge = spark.createDataset(rows, edgeEncoder);
> {code}
> Then I print the content of the current dataset edge
> {code:java}
>  edge.show();
> {code}
>  
> Then I perform a map transformation on edge that upper cases the values of the two entries and return the result in edge2
> {code:java}
>  Dataset<Row> edge2 = edge.map(new MyFunction2(), edgeEncoder);{code}
> The following is the code of MyFunction2
> {code:java}
> public class MyFunction2 implements MapFunction<Row, Row>, scala.Serializable { 
> private static final long serialVersionUID = 1L;
> @Override public Row call(Row v1) throws Exception { 
> String el1 = v1.get(0).toString().toUpperCase(); 
> String el2 = v1.get(1).toString().toUpperCase(); 
> return RowFactory.create(el1,el2); 
> }
> }{code}
> Finally I show the content of edge2
> {code:java}
> edge2.show();
> {code}
> I can confirm that, checking on the hadoop UI a localhost:8088, the job is submitted correctly, and
> what sounds strange is that the first show is returned correctly in my console, but the second one fails returning the up mentioned error.
>  
>  
>  
>  



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