[jira] [Commented] (SPARK-29058) Reading csv file with DROPMALFORMED showing incorrect record count

["Suchintak Patnaik (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-29058?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17051524#comment-17051524 ] 

Suchintak Patnaik commented on SPARK-29058:
-------------------------------------------

[~hyukjin.kwon] Any update on this issue?

> Reading csv file with DROPMALFORMED showing incorrect record count
> ------------------------------------------------------------------
>
>                 Key: SPARK-29058
>                 URL: https://issues.apache.org/jira/browse/SPARK-29058
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, SQL
>    Affects Versions: 2.3.0
>            Reporter: Suchintak Patnaik
>            Priority: Minor
>
> The spark sql csv reader is dropping malformed records as expected, but the record count is showing as incorrect.
> Consider this file (fruit.csv)
> {code}
> apple,red,1,3
> banana,yellow,2,4.56
> orange,orange,3,5
> {code}
> Defining schema as follows:
> {code}
> schema = "Fruit string,color string,price int,quantity int"
> {code}
> Notice that the "quantity" field is defined as integer type, but the 2nd row in the file contains a floating point value, hence it is a corrupt record.
> {code}
> >>> df = spark.read.csv(path="fruit.csv",mode="DROPMALFORMED",schema=schema)
> >>> df.show()
> +------+------+-----+--------+
> | Fruit| color|price|quantity|
> +------+------+-----+--------+
> | apple|   red|    1|       3|
> |orange|orange|    3|       5|
> +------+------+-----+--------+
> >>> df.count()
> 3
> {code}
> Malformed record is getting dropped as expected, but incorrect record count is getting displayed.
> Here the df.count() should give value as 2
>  
>  



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