java - 并行化列表时 Spark 抛出 ArrayIndexOutOfBoundsException

标签 java arrays list apache-spark indexoutofboundsexception

我已尝试创建 QuickSort 的 Spark 实现以针对串行实现进行测试。我已经使串行实现正常工作,但并行实现在尝试并行化整数列表时抛出 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)

下面是Sorter中抛出异常的方法

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);
    ...
}

由 Main 中的以下代码调用。

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();

    ...
}

如果上下文不够,我正在使用的完整代码可在 Github 上找到.

任何人都可以告诉我我做错了什么以获得此异常以及我可以做些什么来修复它吗?

最佳答案

将你的paranamer升级到2.8,这是因为你的jdk版本是1.8

根据 paranamer

Release 2.8 - Aug 26 2015 - JDK 8 compatibility improvements, and removal of Codehaus dependencies in build

所以在 pom.xml 中添加这个依赖:

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

关于java - 并行化列表时 Spark 抛出 ArrayIndexOutOfBoundsException,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/53787624/

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