Question

我尝试创建QuickSort的Spark实现以针对串行实现进行测试。我已经实现了串行实现，但是在尝试并行化整数列表时，并行实现会抛出ArrayIndexOutOfBoundsException。

Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 10582
at com.thoughtworks.paranamer.BytecodeReadingParanamer$ClassReader.accept(BytecodeReadingParanamer.java:563)
at com.thoughtworks.paranamer.BytecodeReadingParanamer$ClassReader.access$200(BytecodeReadingParanamer.java:338)
at com.thoughtworks.paranamer.BytecodeReadingParanamer.lookupParameterNames(BytecodeReadingParanamer.java:103)
at com.thoughtworks.paranamer.CachingParanamer.lookupParameterNames(CachingParanamer.java:90)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.getCtorParams(BeanIntrospector.scala:44)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.$anonfun$apply$1(BeanIntrospector.scala:58)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.$anonfun$apply$1$adapted(BeanIntrospector.scala:58)
at scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:240)
at scala.collection.Iterator.foreach(Iterator.scala:937)
at scala.collection.Iterator.foreach$(Iterator.scala:937)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1425)
at scala.collection.IterableLike.foreach(IterableLike.scala:70)
at scala.collection.IterableLike.foreach$(IterableLike.scala:69)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike.flatMap(TraversableLike.scala:240)
at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:237)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.findConstructorParam$1(BeanIntrospector.scala:58)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.$anonfun$apply$19(BeanIntrospector.scala:176)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233)
at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:32)
at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:29)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:194)
at scala.collection.TraversableLike.map(TraversableLike.scala:233)
at scala.collection.TraversableLike.map$(TraversableLike.scala:226)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:194)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.$anonfun$apply$14(BeanIntrospector.scala:170)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.$anonfun$apply$14$adapted(BeanIntrospector.scala:169)
at scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:240)
at scala.collection.immutable.List.foreach(List.scala:388)
at scala.collection.TraversableLike.flatMap(TraversableLike.scala:240)
at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:237)
at scala.collection.immutable.List.flatMap(List.scala:351)
at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.apply(BeanIntrospector.scala:169)
at com.fasterxml.jackson.module.scala.introspect.ScalaAnnotationIntrospector$._descriptorFor(ScalaAnnotationIntrospectorModule.scala:22)
at com.fasterxml.jackson.module.scala.introspect.ScalaAnnotationIntrospector$.fieldName(ScalaAnnotationIntrospectorModule.scala:30)
at com.fasterxml.jackson.module.scala.introspect.ScalaAnnotationIntrospector$.findImplicitPropertyName(ScalaAnnotationIntrospectorModule.scala:78)
at com.fasterxml.jackson.databind.introspect.AnnotationIntrospectorPair.findImplicitPropertyName(AnnotationIntrospectorPair.java:467)
at com.fasterxml.jackson.databind.introspect.POJOPropertiesCollector._addFields(POJOPropertiesCollector.java:351)
at com.fasterxml.jackson.databind.introspect.POJOPropertiesCollector.collectAll(POJOPropertiesCollector.java:283)
at com.fasterxml.jackson.databind.introspect.POJOPropertiesCollector.getJsonValueMethod(POJOPropertiesCollector.java:169)
at com.fasterxml.jackson.databind.introspect.BasicBeanDescription.findJsonValueMethod(BasicBeanDescription.java:223)
at com.fasterxml.jackson.databind.ser.BasicSerializerFactory.findSerializerByAnnotations(BasicSerializerFactory.java:348)
at com.fasterxml.jackson.databind.ser.BeanSerializerFactory._createSerializer2(BeanSerializerFactory.java:210)
at com.fasterxml.jackson.databind.ser.BeanSerializerFactory.createSerializer(BeanSerializerFactory.java:153)
at com.fasterxml.jackson.databind.SerializerProvider._createUntypedSerializer(SerializerProvider.java:1203)
at com.fasterxml.jackson.databind.SerializerProvider._createAndCacheUntypedSerializer(SerializerProvider.java:1157)
at com.fasterxml.jackson.databind.SerializerProvider.findValueSerializer(SerializerProvider.java:481)
at com.fasterxml.jackson.databind.SerializerProvider.findTypedValueSerializer(SerializerProvider.java:679)
at com.fasterxml.jackson.databind.ser.DefaultSerializerProvider.serializeValue(DefaultSerializerProvider.java:107)
at com.fasterxml.jackson.databind.ObjectMapper._configAndWriteValue(ObjectMapper.java:3559)
at com.fasterxml.jackson.databind.ObjectMapper.writeValueAsString(ObjectMapper.java:2927)
at org.apache.spark.rdd.RDDOperationScope.toJson(RDDOperationScope.scala:52)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:145)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.SparkContext.withScope(SparkContext.scala:699)
at org.apache.spark.SparkContext.parallelize(SparkContext.scala:716)
at org.apache.spark.api.java.JavaSparkContext.parallelize(JavaSparkContext.scala:134)
at org.apache.spark.api.java.JavaSparkContext.parallelize(JavaSparkContext.scala:146)
at Sorter.parallelSort(Sorter.java:83)
at Main.main(Main.java:33)

以下是Sorter中引发异常的方法。

private final List<T> unsorted;
private final String master;

...

public List<T> parallelSort() {
    SparkConf conf = new SparkConf().setAppName("QuickSort").setMaster(master);
    JavaSparkContext sc = new JavaSparkContext(conf);

    JavaRDD<T> data = sc.parallelize(unsorted);
    ...
}

以下是来自Main的以下代码调用的

public static void main(String[] args) {
    ...

    List<Integer> ints = new ArrayList<>();

    ...

    Sorter<Integer> sorter = new Sorter<>(ints, "local[*]");
    List<Integer> serialSorted = sorter.serialSort();
    List<Integer> parallelSorted = sorter.parallelSort();

    ...
}

如果上下文还不够，可以在Github上找到我正在使用的完整代码。

任何人都可以告诉我我做错了什么以获取此异常以及如何解决该异常吗？

Answer 1

将您的paranamer升级到2.8，这是由于您的jdk版本为1.8

根据paranamer

版本2.8-2015年8月26日-改进了JDK 8的兼容性，并删除了构建中的Codehaus依赖项

因此在pom.xml中添加此依赖项：

<dependency>
    <groupId>com.thoughtworks.paranamer</groupId>
    <artifactId>paranamer</artifactId>
    <version>2.8</version>
</dependency>

Answer 2

可能与此问题有关

https://github.com/paul-hammant/paranamer/issues/17

Answer 3

您已使用spark-core_2.12。尝试使用spark-core_2.11，它对我有用。

<dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-core_2.12</artifactId> <version>LATEST</version> </dependency>

并行化列表时发火花引发ArrayIndexOutOfBoundsException

3 个答案: