如何修复java.lang.ClassCastException:无法将scala.collection.immutable.List的实例分配给字段类型scala.collection.Seq？

Question

这个错误是最难追查的.我不确定发生了什么.我正在我的位置机器上运行Spark集群.所以整个火花集群都在一个主机下127.0.0.1,我在独立模式下运行

JavaPairRDD<byte[], Iterable<CassandraRow>> cassandraRowsRDD= javaFunctions(sc).cassandraTable("test", "hello" )
   .select("rowkey", "col1", "col2", "col3",  )
   .spanBy(new Function<CassandraRow, byte[]>() {
        @Override
        public byte[] call(CassandraRow v1) {
            return v1.getBytes("rowkey").array();
        }
    }, byte[].class);

Iterable<Tuple2<byte[], Iterable<CassandraRow>>> listOftuples = cassandraRowsRDD.collect(); //ERROR HAPPENS HERE
Tuple2<byte[], Iterable<CassandraRow>> tuple = listOftuples.iterator().next();
byte[] partitionKey = tuple._1();
for(CassandraRow cassandraRow: tuple._2()) {
    System.out.println("************START************");
    System.out.println(new String(partitionKey));
    System.out.println("************END************");
}

这个错误是最难追查的.它显然发生在cassandraRowsRDD.collect(),我不知道为什么？

16/10/09 23:36:21 ERROR Executor: Exception in task 2.3 in stage 0.0 (TID 21)
java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.List$SerializationProxy to field org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$dependencies_ of type scala.collection.Seq in instance of org.apache.spark.rdd.MapPartitionsRDD
    at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
    at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
    at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:75)
    at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:114)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:85)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
    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)

这是我使用的版本

Scala code runner version 2.11.8  // when I run scala -version or even ./spark-shell


compile group: 'org.apache.spark' name: 'spark-core_2.11' version: '2.0.0'
compile group: 'org.apache.spark' name: 'spark-streaming_2.11' version: '2.0.0'
compile group: 'org.apache.spark' name: 'spark-sql_2.11' version: '2.0.0'
compile group: 'com.datastax.spark' name: 'spark-cassandra-connector_2.11' version: '2.0.0-M3': 

我的gradle文件在介绍一些名为"提供"的内容后看起来像这样,实际上似乎并不存在,但谷歌说要创建一个,所以我的build.gradle看起来像这样

group 'com.company'
version '1.0-SNAPSHOT'

apply plugin: 'java'
apply plugin: 'idea'

repositories {
    mavenCentral()
    mavenLocal()
}

configurations {
    provided
}
sourceSets {
    main {
        compileClasspath += configurations.provided
        test.compileClasspath += configurations.provided
        test.runtimeClasspath += configurations.provided
    }
}

idea {
    module {
        scopes.PROVIDED.plus += [ configurations.provided ]
    }
}

dependencies {
    compile 'org.slf4j:slf4j-log4j12:1.7.12'
    provided group: 'org.apache.spark', name: 'spark-core_2.11', version: '2.0.0'
    provided group: 'org.apache.spark', name: 'spark-streaming_2.11', version: '2.0.0'
    provided group: 'org.apache.spark', name: 'spark-sql_2.11', version: '2.0.0'
    provided group: 'com.datastax.spark', name: 'spark-cassandra-connector_2.11', version: '2.0.0-M3'
}



jar {
    from { configurations.provided.collect { it.isDirectory() ? it : zipTree(it) } }
   // with jar
    from sourceSets.test.output
    manifest {
        attributes 'Main-Class': "com.company.batchprocessing.Hello"
    }
    exclude 'META-INF/.RSA', 'META-INF/.SF', 'META-INF/*.DSA'
    zip64 true
}

Answer 1

我有同样的问题,可以通过将我的应用程序的jar添加到spark的classpath来解决它

spark = SparkSession.builder()
        .appName("Foo")
        .config("spark.jars", "target/scala-2.11/foo_2.11-0.1.jar")

Answer 2

我遇到了同样的异常，并深入研究了多个相关的 Jiras（9219、12675、18075）。

我认为异常名称令人困惑，真正的问题是spark集群和驱动程序应用程序之间的环境设置不一致。

例如，我使用以下行启动了我的 Spark 集群conf/spark-defaults.conf：

spark.master                     spark://master:7077

当我spark-submit用一行启动我的驱动程序（甚至程序以 开头）时：

sparkSession.master("spark://<master ip>:7077")

其中<master ip>是节点的正确 IP 地址master，但由于这种简单的不一致，程序将失败。

因此，我建议所有驱动程序应用程序都启动spark-submit并且不要复制驱动程序代码中的任何配置（除非您需要覆盖某些配置）。也就是说，只需spark-submit在运行的 Spark 集群中以相同的方式设置您的环境。

Answer 3

您的 call() 方法应该返回 byte[] ，如下所示。

@Override
public byte[] call(CassandraRow v1) {
  return v1.getBytes("rowkey").array();
}

如果您仍然遇到问题，请检查 Jira https://issues.apache.org/jira/browse/SPARK-9219中提到的依赖项版本