我正在使用Spark 3.0.1和用户提供的Hadoop 3.2.0和Scala 2.12.10在Kubernetes上运行。
读取压缩为snappy的 parquet 文件时一切正常，但是当我尝试读取压缩为 zstd 的 parquet 文件时，几个任务在以下错误下失败：
java.io.IOException: Decompression error: Version not supported
at com.github.luben.zstd.ZstdInputStream.readInternal(ZstdInputStream.java:164)
at com.github.luben.zstd.ZstdInputStream.read(ZstdInputStream.java:120)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:246)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:286)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.ObjectInputStream$PeekInputStream.read(ObjectInputStream.java:2781)
at java.io.ObjectInputStream$PeekInputStream.readFully(ObjectInputStream.java:2797)
at java.io.ObjectInputStream$BlockDataInputStream.readShort(ObjectInputStream.java:3274)
at java.io.ObjectInputStream.readStreamHeader(ObjectInputStream.java:934)
at java.io.ObjectInputStream.(ObjectInputStream.java:396)
at org.apache.spark.MapOutputTracker$.deserializeObject$1(MapOutputTracker.scala:954)
at org.apache.spark.MapOutputTracker$.deserializeMapStatuses(MapOutputTracker.scala:964)
at org.apache.spark.MapOutputTrackerWorker.$anonfun$getStatuses$2(MapOutputTracker.scala:856)
at org.apache.spark.util.KeyLock.withLock(KeyLock.scala:64)
at org.apache.spark.MapOutputTrackerWorker.getStatuses(MapOutputTracker.scala:851)
at org.apache.spark.MapOutputTrackerWorker.getMapSizesByExecutorId(MapOutputTracker.scala:808)
at org.apache.spark.shuffle.sort.SortShuffleManager.getReader(SortShuffleManager.scala:128)
at org.apache.spark.sql.execution.ShuffledRowRDD.compute(ShuffledRowRDD.scala:185)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
我没有得到的是，这些任务在重试后会成功，但并非总是如此，因此我的工作经常失败。如前所述，如果我使用与 snappy 相同的数据集压缩，一切正常。
我还尝试构建 Spark 和 Hadoop，更改 zstd-jni 版本，但仍然会发生相同的行为。
有谁知道可能会发生什么？
谢谢！