Spark读取CSV异常 java.lang.ArrayIndexOutOfBoundsException:62

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前言

记录一个异常

场景

Spark读取CSV文件，文件里的某些内容编码格式有问题或者有特殊字符

一种情况是 62,我碰到的这种，另一种是63,查资料查的

java.lang.ArrayIndexOutOfBoundsException:62

java.lang.ArrayIndexOutOfBoundsException:63

解决方法

情况1：
将GBK编码的文件转文UTF-8(我碰见的)，当然这种情况也可以用情况2中的解决办法解决~

情况2：

.option("multiline", "true")

或指定schema

详情参考：CSV schema inferring fails on some UTF-8 chars

注：这上面标的是2.3.0版本的Bug，在2.2.2, 2.3.1, 2.4.0已修复，我没有测试是否在这些版本修复
.option(“multiline”, “true”) 这种办法

详细异常

19/05/30 14:03:15 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.ArrayIndexOutOfBoundsException: 62
	at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
	at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
	at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
	at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
	at org.apache.spark.scheduler.Task.run(Task.scala:109)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
	at java.lang.Thread.run(Unknown Source)
19/05/30 14:03:15 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.lang.ArrayIndexOutOfBoundsException: 62
	at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
	at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
	at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
	at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
	at org.apache.spark.scheduler.Task.run(Task.scala:109)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
	at java.lang.Thread.run(Unknown Source)

Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
	at scala.Option.foreach(Option.scala:257)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2027)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2048)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2067)
	at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:363)
	at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
	at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3272)
	at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
	at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
	at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3253)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
	at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
	at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
	at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
	at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.infer(CSVDataSource.scala:148)
	at org.apache.spark.sql.execution.datasources.csv.CSVDataSource.inferSchema(CSVDataSource.scala:63)
	at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:57)
	at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:202)
	at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:202)
	at scala.Option.orElse(Option.scala:289)
	at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:201)
	at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:392)
	at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
	at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
	at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:594)
	at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:473)
	at com.hs.alipay.AlipayFeature$.main(AlipayFeature.scala:20)
	at com.hs.alipay.AlipayFeature.main(AlipayFeature.scala)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 62
	at org.apache.spark.unsafe.types.UTF8String.numBytesForFirstByte(UTF8String.java:191)
	at org.apache.spark.unsafe.types.UTF8String.numChars(UTF8String.java:206)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
	at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:253)
	at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:830)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
	at org.apache.spark.scheduler.Task.run(Task.scala:109)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
	at java.lang.Thread.run(Unknown Source)

每日英语

• 1、unified 统一的；一致标准的
• 2、analytics 英 [ænə’lɪtɪks] 美 [,ænl’ɪtɪks] n. [化学][数] 分析学；解析学
• 3、Lightning 闪电⚡ Lightning-fast 快如闪电的
• 4、scale 规模 large-scale 大规模的
• 5、achieves 实现

Apache Spark™ is a unified analytics engine for large-scale data processing.
Apache Spark™是用于大规模数据处理的统一分析引擎。

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本文由 董可伦 发表于 伦少的博客 ,采用署名-非商业性使用-禁止演绎 3.0进行许可。

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本文标题：Spark读取CSV异常 java.lang.ArrayIndexOutOfBoundsException:62

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