使用spark或hive读取avro文件时出现无效的同步错误

vngu2lb8  于 2021-06-24  发布在  Hive
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我有一个avro文件,它是使用javaapi创建的,当编写器在文件中写入数据时,由于机器重新启动,程序意外关闭。现在,当我尝试使用spark/hive读取此文件时,它读取一些数据,然后抛出以下错误(org.apache.avro.avroruntimeexception:java.io.ioexception:invalid sync!)–

INFO DAGScheduler: ShuffleMapStage 1 (count at DataReaderSpark.java:41) failed in 7.420 s due to Job aborted due to stage failure: Task 1 in stage 1.0 failed 1 times, most recent failure: Lost task 1.0 in stage 1.0 (TID 2, localhost, executor driver): org.apache.avro.AvroRuntimeException: java.io.IOException: Invalid sync!
        at org.apache.avro.file.DataFileStream.hasNext(DataFileStream.java:210)
        at com.databricks.spark.avro.DefaultSource$$anonfun$buildReader$1$$anon$1.hasNext(DefaultSource.scala:215)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
        at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:106)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.agg_doAggregateWithoutKey$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$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 scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
        at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
        at org.apache.spark.scheduler.Task.run(Task.scala:109)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748) Caused by: java.io.IOException: Invalid sync!
        at org.apache.avro.file.DataFileStream.nextRawBlock(DataFileStream.java:293)
        at org.apache.avro.file.DataFileStream.hasNext(DataFileStream.java:198)
        ... 16 more

我认为最后的记录是错误的。我只是想知道是否有一种方法可以通过跳过最后一条记录来读取这个文件而不出现异常/错误。

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