3

我在不是很大的 DataFrame 上使用 toPandas() ，但出现以下异常：

18/10/31 19:13:19 ERROR Executor: Exception in task 127.2 in stage 13.0 (TID 2264)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
    File "/home/hadoop/spark2.3.1/python/lib/pyspark.zip/pyspark/worker.py", line 230, in main
      process()
    File "/home/hadoop/spark2.3.1/python/lib/pyspark.zip/pyspark/worker.py", line 225, in process
      serializer.dump_stream(func(split_index, iterator), outfile)
    File "/home/hadoop/spark2.3.1/python/lib/pyspark.zip/pyspark/serializers.py", line 261, in dump_stream
      batch = _create_batch(series, self._timezone)
    File "/home/hadoop/spark2.3.1/python/lib/pyspark.zip/pyspark/serializers.py", line 239, in _create_batch
      arrs = [create_array(s, t) for s, t in series]
    File "/home/hadoop/spark2.3.1/python/lib/pyspark.zip/pyspark/serializers.py", line 239, in <listcomp>
      arrs = [create_array(s, t) for s, t in series]
    File "/home/hadoop/spark2.3.1/python/lib/pyspark.zip/pyspark/serializers.py", line 237, in create_array
      return pa.Array.from_pandas(s, mask=mask, type=t)
    File "pyarrow/array.pxi", line 474, in pyarrow.lib.Array.from_pandas
    File "pyarrow/array.pxi", line 169, in pyarrow.lib.array
    File "pyarrow/array.pxi", line 69, in pyarrow.lib._ndarray_to_array
    File "pyarrow/error.pxi", line 81, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Floating point value truncated
        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298)
        at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:171)
        at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.read(ArrowPythonRunner.scala:121)
        at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
        at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
        at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage19.agg_doAggregateWithKeys_0$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage19.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:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

有时，可以忽略此异常，我可以获得正确的结果，但更多时候，程序退出了。有谁知道这个神秘的错误？

4

2 回答 2

3

我遇到了同样的错误。我认为@bryanc 是正确的，您需要安全地转换类型。在我的情况下，数据在 bigint 中，而函数需要浮点/双精度。所以我做了

from pyspark.sql.types import DoubleType
df = df.withColumn("x_dbl", df["x"].cast(DoubleType()))

遵循如何在 pyspark 中将 Dataframe 列从 String 类型更改为 Double 类型的方法

然后，我没有在“x”上应用该函数，而是在“x_dbl”上做了，它起作用了。希望这可以帮助！

于 2019-01-07T23:44:03.627 回答
1

你用的是什么版本的pyarrow？我相信从 0.11.0 版本开始，不安全的类型转换会引发错误。

于 2018-11-01T21:52:04.110 回答