eclipse上的Scala：当数据帧读取csv时抛出java.lang.ArrayIndexOutOfBoundsException

时间：2018-11-09 11:50:33

标签： eclipse scala csv apache-spark dataframe

尝试读取一个简单的csv文件并将其加载到数据帧中会抛出java.lang.ArrayIndexOutOfBoundsException.

由于我是Scala的新手，所以我可能错过了一些琐碎的事情，但是在google和stackoverflow中进行全面搜索都不会带来任何结果。

代码如下：

    import org.apache.spark.sql.SparkSession


        object TransformInitial {
          def main(args: Array[String]): Unit = {

            val session = SparkSession.builder.master("local").appName("test").getOrCreate()
            val df = session.read.format("csv").option("header", "true").option("inferSchema", "true").option("delimiter",",").load("data_sets/small_test.csv")

            df.show()
          }
        }

small_test.csv尽可能简单：

v1,v2,v3
0,1,2
3,4,5

这是该Maven项目的实际pom：

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>
  <groupId>Scala_tests</groupId>
  <artifactId>Scala_tests</artifactId>
  <version>0.0.1-SNAPSHOT</version>
  <build>
    <sourceDirectory>src</sourceDirectory>
    <resources>
      <resource>
        <directory>src</directory>
        <excludes>
          <exclude>**/*.java</exclude>
        </excludes>
      </resource>
    </resources>
    <plugins>
      <plugin>
        <artifactId>maven-compiler-plugin</artifactId>
        <version>3.8.0</version>
        <configuration>
          <source>1.8</source>
          <target>1.8</target>
        </configuration>
      </plugin>
      <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core -->


    </plugins>
  </build>
  <dependencies>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.12</artifactId>
        <version>2.4.0</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.12</artifactId>
        <version>2.4.0</version>
    </dependency>

  </dependencies>
</project>

执行代码将引发以下

java.lang.ArrayIndexOutOfBoundsException:

18/11/09 12:03:31 INFO FileSourceStrategy: Pruning directories with: 
18/11/09 12:03:31 INFO FileSourceStrategy: Post-Scan Filters: (length(trim(value#0, None)) > 0)
18/11/09 12:03:31 INFO FileSourceStrategy: Output Data Schema: struct<value: string>
18/11/09 12:03:31 INFO FileSourceScanExec: Pushed Filters: 
18/11/09 12:03:31 INFO CodeGenerator: Code generated in 413.859722 ms
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$1(TraversableLike.scala:241)
    at scala.collection.Iterator.foreach(Iterator.scala:929)
    at scala.collection.Iterator.foreach$(Iterator.scala:929)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1417)
    at scala.collection.IterableLike.foreach(IterableLike.scala:71)
    at scala.collection.IterableLike.foreach$(IterableLike.scala:70)
    at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
    at scala.collection.TraversableLike.flatMap(TraversableLike.scala:241)
    at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:238)
    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$1(TraversableLike.scala:234)
    at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:32)
    at scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:29)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:191)
    at scala.collection.TraversableLike.map(TraversableLike.scala:234)
    at scala.collection.TraversableLike.map$(TraversableLike.scala:227)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:191)
    at com.fasterxml.jackson.module.scala.introspect.BeanIntrospector$.$anonfun$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$1(TraversableLike.scala:241)
    at scala.collection.immutable.List.foreach(List.scala:389)
    at scala.collection.TraversableLike.flatMap(TraversableLike.scala:241)
    at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:238)
    at scala.collection.immutable.List.flatMap(List.scala:352)
    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$.withScope(RDDOperationScope.scala:142)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3384)
    at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2545)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:3365)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3365)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2545)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2759)
    at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.infer(CSVDataSource.scala:232)
    at org.apache.spark.sql.execution.datasources.csv.CSVDataSource.inferSchema(CSVDataSource.scala:68)
    at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:63)
    at org.apache.spark.sql.execution.datasources.DataSource.$anonfun$getOrInferFileFormatSchema$12(DataSource.scala:183)
    at scala.Option.orElse(Option.scala:289)
    at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:180)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:373)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:223)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178)
    at TransformInitial$.main(TransformInitial.scala:9)
    at TransformInitial.main(TransformInitial.scala)

Eclipse的记录版本为2018-09（4.9.0）。

我用猫-A在csv中搜寻特殊字符。它什么也没产生。 我没有选择的余地，必须要遗忘一些琐碎的东西，但我不能对此付诸表决。

2 个答案:

答案 0 :(得分：2)

我不确定是什么导致了您的错误，因为该代码对我有用。它可能与您正在使用的 Scala 编译器的版本有关，因为您的 Maven 文件中没有有关此信息的信息。

我已经使用 SBT 将完整的解决方案发布到 GitHub 。要执行代码，您需要将 SBT ，cd安装到检出源的根文件夹中，然后运行以下命令： 

$ sbt run

顺便说一句，我更改了代码以利用更多惯用的 Scala 约定，并且还使用了csv函数来加载文件。新的 Scala 代码如下所示： 

import org.apache.spark.sql.SparkSession

// Extending App is more idiomatic than writing a "main" function.
object TransformInitial
extends App {

  val session = SparkSession.builder.master("local").appName("test").getOrCreate()

  // As of Spark 2.0, it's easier to read CSV files.
  val df = session.read.option("header", "true").option("inferSchema", "true").csv("data_sets/small_test.csv")

  df.show()

  // Shutdown gracefully.
  session.stop()
}

请注意，我还删除了多余的定界符选项。

答案 1 :(得分：1)

将scala版本降级为2.11已修复。

<dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.11</artifactId>
        <version>2.4.0</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.11</artifactId>
        <version>2.4.0</version>
    </dependency>
相关问题
最新问题