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Posted to issues@spark.apache.org by "Takeshi Yamamuro (Jira)" <ji...@apache.org> on 2020/08/06 00:06:00 UTC

[jira] [Commented] (SPARK-32547) Cant able to process Timestamp 0001-01-01T00:00:00.000+0000 with TimestampType

    [ https://issues.apache.org/jira/browse/SPARK-32547?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17171843#comment-17171843 ] 

Takeshi Yamamuro commented on SPARK-32547:
------------------------------------------

Thanks for the report. I checked that master/branch-2.4 has the same issue. Either one could check this? [~maxgekk] [~Qin Yao]

[https://github.com/apache/spark/blob/master/python/pyspark/sql/types.py#L195]

> Cant able to process Timestamp 0001-01-01T00:00:00.000+0000 with TimestampType
> ------------------------------------------------------------------------------
>
>                 Key: SPARK-32547
>                 URL: https://issues.apache.org/jira/browse/SPARK-32547
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 3.0.0
>            Reporter: Manjunath H
>            Priority: Major
>
> Spark Version : 3.0.0
> Below is the sample code to reproduce the problem with TimestampType.
> {code:java}
> from pyspark.sql.functions import lit
> from pyspark.sql.types import TimestampType
> df=spark.createDataFrame([(1, 'foo'),(2, 'bar'),],['id', 'txt'])
> new_df=df.withColumn("test_timestamp",lit("0001-01-01T00:00:00.000+0000").cast(TimestampType()))
> new_df.printSchema()
> root
>  |-- id: long (nullable = true)
>  |-- txt: string (nullable = true)
>  |-- test_timestamp: timestamp (nullable = true)
> new_df.show()
> +---+---+-------------------+
> | id|txt|     test_timestamp|
> +---+---+-------------------+
> |  1|foo|0001-01-01 00:00:00|
> |  2|bar|0001-01-01 00:00:00|
> +---+---+-------------------+
> {code}
>  
> new_df.rdd.isEmpty() operation is failing with *year 0 is out of range*
>  
> {code:java}
> new_df.rdd.isEmpty()
> Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
> : org.apache.spark.SparkException: Job aborted due to stage failure:  Traceback (most recent call last):
> File "/databricks/spark/python/pyspark/serializers.py", line 177, in _read_with_length
>  return self.loads(obj)
>  File "/databricks/spark/python/pyspark/serializers.py", line 466, in loads
>  return pickle.loads(obj, encoding=encoding)
>  File "/databricks/spark/python/pyspark/sql/types.py", line 1415, in <lambda>
>  return lambda *a: dataType.fromInternal(a)
>  File "/databricks/spark/python/pyspark/sql/types.py", line 635, in fromInternal
>  for f, v, c in zip(self.fields, obj, self._needConversion)]
>  File "/databricks/spark/python/pyspark/sql/types.py", line 635, in <listcomp>
>  for f, v, c in zip(self.fields, obj, self._needConversion)]
>  File "/databricks/spark/python/pyspark/sql/types.py", line 447, in fromInternal
>  return self.dataType.fromInternal(obj)
>  File "/databricks/spark/python/pyspark/sql/types.py", line 201, in fromInternal
>  return datetime.datetime.fromtimestamp(ts // 1000000).replace(microsecond=ts % 1000000)
> ValueError: year 0 is out of range{code}



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