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https://issues.apache.org/jira/browse/SPARK-11319?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15199967#comment-15199967
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Yin Huai commented on SPARK-11319:
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Thank you for the doc update. We recently added a check to make sure
non-nullable column should not contain null values in Python (see
https://github.com/apache/spark/commit/d5ce61722f2aa4167a8344e1664b000c70d5a3f8
and SPARK-13740). Can you try the master and see if the new behavior meets your
requirement? Thanks!
> PySpark silently accepts null values in non-nullable DataFrame fields.
> ----------------------------------------------------------------------
>
> Key: SPARK-11319
> URL: https://issues.apache.org/jira/browse/SPARK-11319
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Reporter: Kevin Cox
>
> Running the following code with a null value in a non-nullable column
> silently works. This makes the code incredibly hard to trust.
> {code}
> In [2]: from pyspark.sql.types import *
> In [3]: sqlContext.createDataFrame([(None,)], StructType([StructField("a",
> TimestampType(), False)])).collect()
> Out[3]: [Row(a=None)]
> {code}
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