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https://issues.apache.org/jira/browse/SPARK-41855?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17653917#comment-17653917
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Apache Spark commented on SPARK-41855:
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User 'zhengruifeng' has created a pull request for this issue:
https://github.com/apache/spark/pull/39360
> `createDataFrame` doesn't handle None/NaN properly
> --------------------------------------------------
>
> Key: SPARK-41855
> URL: https://issues.apache.org/jira/browse/SPARK-41855
> Project: Spark
> Issue Type: Sub-task
> Components: Connect, PySpark
> Affects Versions: 3.4.0
> Reporter: Ruifeng Zheng
> Priority: Major
>
> {code:python}
> data = [Row(id=1, value=float("NaN")), Row(id=2, value=42.0),
> Row(id=3, value=None)]
> # +---+-----+
> # | id|value|
> # +---+-----+
> # | 1| NaN|
> # | 2| 42.0|
> # | 3| null|
> # +---+-----+
> cdf = self.connect.createDataFrame(data)
> sdf = self.spark.createDataFrame(data)
> print()
> print()
> print(cdf._show_string(100, 100, False))
> print()
> print(cdf.schema)
> print()
> print(sdf._jdf.showString(100, 100, False))
> print()
> print(sdf.schema)
> self.compare_by_show(cdf, sdf)
> {code}
> {code:java}
> +---+-----+
> | id|value|
> +---+-----+
> | 1| null|
> | 2| 42.0|
> | 3| null|
> +---+-----+
> StructType([StructField('id', LongType(), True), StructField('value',
> DoubleType(), True)])
> +---+-----+
> | id|value|
> +---+-----+
> | 1| NaN|
> | 2| 42.0|
> | 3| null|
> +---+-----+
> StructType([StructField('id', LongType(), True), StructField('value',
> DoubleType(), True)])
> {code}
> this issue is due to that `createDataFrame` can't handle None/NaN properly:
> 1, in the conversion from local data to pd.DataFrame, it automatically
> converts both None and NaN to NaN
> 2, then in the conversion from pd.DataFrame to pa.Table, it always converts
> NaN to null
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