sparksql读取hive数据报错：java.lang.RuntimeException: serious problem

问题：

Caused by: java.util.concurrent.ExecutionException: java.lang.IndexOutOfBoundsException: Index: 0
    at java.util.concurrent.FutureTask.report(FutureTask.java:122)
    at java.util.concurrent.FutureTask.get(FutureTask.java:192)
    at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.generateSplitsInfo(OrcInputFormat.java:1016)
    ... 65 more
Caused by: java.lang.IndexOutOfBoundsException: Index: 0
    at java.util.Collections$EmptyList.get(Collections.java:4454)
    at org.apache.hadoop.hive.ql.io.orc.OrcProto$Type.getSubtypes(OrcProto.java:12240)
    at org.apache.hadoop.hive.ql.io.orc.ReaderImpl.getColumnIndicesFromNames(ReaderImpl.java:651)
    at org.apache.hadoop.hive.ql.io.orc.ReaderImpl.getRawDataSizeOfColumns(ReaderImpl.java:634)
    at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.populateAndCacheStripeDetails(OrcInputFormat.java:927)
    at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.call(OrcInputFormat.java:836)
    at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$SplitGenerator.call(OrcInputFormat.java:702)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:748)
java.lang.RuntimeException: serious problem
    at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.generateSplitsInfo(OrcInputFormat.java:1021)
    at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.getSplits(OrcInputFormat.java:1048)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:200)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:46)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
    at scala.Option.getOrElse(Option.scala:121)

原因：

sparksql生成的hive表有空文件，但是sparksql读取空文件的时候，因为表示orc格式的，导致sparksql解析orc文件出错。但是用hive却可以正常读取。

解决办法：

暂时不知道怎么解决，这里先记录一下，等找到方法再回来补充