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https://issues.apache.org/jira/browse/SPARK-30530?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17017290#comment-17017290
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Maxim Gekk commented on SPARK-30530:
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[~jlowe] Thank you for the bug report. I will take a look at it.
> CSV load followed by "is null" filter produces incorrect results
> ----------------------------------------------------------------
>
> Key: SPARK-30530
> URL: https://issues.apache.org/jira/browse/SPARK-30530
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Jason Darrell Lowe
> Priority: Major
>
> Trying to filter on is null from values loaded from a CSV file has regressed
> recently and now produces incorrect results.
> Given a CSV file with the contents:
> {noformat:title=floats.csv}
> 100.0,1.0,
> 200.0,,
> 300.0,3.0,
> 1.0,4.0,
> ,4.0,
> 500.0,,
> ,6.0,
> -500.0,50.5
> {noformat}
> Filtering this data for the first column being null should return exactly two
> rows, but it is returning extraneous rows with nulls:
> {noformat}
> scala> val schema = StructType(Array(StructField("floats", FloatType,
> true),StructField("more_floats", FloatType, true)))
> schema: org.apache.spark.sql.types.StructType =
> StructType(StructField(floats,FloatType,true),
> StructField(more_floats,FloatType,true))
> scala> val df = spark.read.schema(schema).csv("floats.csv")
> df: org.apache.spark.sql.DataFrame = [floats: float, more_floats: float]
> scala> df.filter("floats is null").show
> +------+-----------+
> |floats|more_floats|
> +------+-----------+
> | null| null|
> | null| null|
> | null| null|
> | null| null|
> | null| 4.0|
> | null| null|
> | null| 6.0|
> +------+-----------+
> {noformat}
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