当我尝试使用pyspark读取具有bigint列的Parquet地板表时，它给出了一个错误。有什么建议吗？

df=spark.table("db.table").filter("partitiondate='2020-10-22'");
df.count()   // this works
df.show(1)  // Gives error

[阶段5:=============>（1+1）/4]20/10/23 14:14:04警告调度器.tasksetmanager:阶段5.0中丢失任务0.0（tid 275，anp-r12wn03.c03.hadoop.td.com，executor 13）：java.lang.unsupportedoperationexception:parquet.column.values.dictionary.plainvaluesdictionary$plainbinarydictionary位于parquet.column.dictionary.decodetolong（dictionary）。java:52)在org.apache.spark.sql.execution.vectoried.onheapcolumnvector.getlong（onheapcolumnvector。java:295)在org.apache.spark.sql.execution.vectoried.columnarbatch$row.getlong（columnarbatch。java:191)位于org.apache.spark.sql.catalyst.expressions.generatedclass$specificansafeprojection.apply6$（未知源），位于org.apache.spark.sql.catalyst.expressions.generatedclass$specificansafeprojection.apply（未知源）org.apache.spark.sql.catalyst.expressions.generatedclass$specificansafeprojection.apply（未知源代码）位于scala.collection.iterator$$anon$11.next（iterator）。scala:409)在scala.collection.iterator$$anon$11.next（iterator。scala:409)在org.apache.spark.sql.execution.sparkplan$$anonfun$2.apply（sparkplan。scala:235)在org.apache.spark.sql.execution.sparkplan$$anonfun$2.apply（sparkplan。scala:228)在org.apache.spark.rdd.rdd$$anonfun$mappartitionsinternal$1$$anonfun$apply$25.apply（rdd。scala:835)在org.apache.spark.rdd.rdd$$anonfun$mappartitionsinternal$1$$anonfun$apply$25.apply（rdd。scala:835)在org.apache.spark.rdd.mappartitionsrdd.compute（mappartitionsrdd。scala:49)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:323)在org.apache.spark.rdd.rdd.iterator（rdd。scala:287)在org.apache.spark.scheduler.resulttask.runtask（resulttask。scala:87)在org.apache.spark.scheduler.task.run（task。scala:109)在org.apache.spark.executor.executor$taskrunner.run（executor。scala:380)位于java.util.concurrent.threadpoolexecutor.runworker（threadpoolexecutor。java:1149)在java.util.concurrent.threadpoolexecutor$worker.run（threadpoolexecutor。java:624)在java.lang.thread.run（线程。java:748)
[第五阶段：============================>（2+2）/4]20/1