<p>我在S3中有拼花数据,由nyc_date以<code>s3://mybucket/mykey/nyc_date=Y-m-d/*.gz.parquet</code>格式分区。</p>
<p>我有一个DateType列<code>event_date</code>,当我试图使用EMR从S3读取和写入hdfs时,由于某种原因,该列会抛出此错误。</p>
<pre><code>from pyspark.sql import SparkSession
spark = SparkSession.builder.enableHiveSupport().getOrCreate()
df = spark.read.parquet('s3a://mybucket/mykey/')
df.limit(100).write.parquet('hdfs:///output/', compression='gzip')
</code></pre>
<p>错误:</p>
<pre><code>java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainBinaryDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:48)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:233)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:389)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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:745)
</code></pre>
<p>我发现:</p>
<ul>
<li><strong>本地工作:-)</strong>:我以相同的格式在本地复制了一些数据,可以很好地查询。</li>
<li><strong>避免选择event_date works:-)</strong>:选择除<code>event_date</code>之外的所有50+列不会导致任何错误。</li>
<li><strong>显式读取路径抛出错误:-(</strong>:将读取路径更改为<code>'s3a://mybucket/mykey/*/*.gz.parquet'</code>仍抛出错误。</li>
<li><strong>指定架构仍会引发错误:-(</strong>:加载前指定架构仍会导致相同的错误。</li>
<li>我可以将包括东方数据在内的数据加载到数据仓库中:-)。</li>
</ul>
<p>很奇怪,这只会导致DateType列出错。我没有其他日期类型列。</p>
<p>使用Spark 2.0.2和EMR 5.2.0。</p>