[jira] [Closed] (SPARK-32888) reading a parallized rdd with two identical records results in a zero count df when read via spark.read.csv

["Punit Shah (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-32888?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Punit Shah closed SPARK-32888.
------------------------------

Resolved by adding documentation

> reading a parallized rdd with two identical records results in a zero count df when read via spark.read.csv
> -----------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-32888
>                 URL: https://issues.apache.org/jira/browse/SPARK-32888
>             Project: Spark
>          Issue Type: Documentation
>          Components: Spark Core
>    Affects Versions: 2.4.5, 2.4.6, 2.4.7, 3.0.0, 3.0.1
>            Reporter: Punit Shah
>            Assignee: L. C. Hsieh
>            Priority: Minor
>             Fix For: 2.4.8, 3.0.2, 3.1.0
>
>
> * Imagine a two-row csv file like so (where the header and first record are duplicate rows):
> aaa,bbb
> aaa,bbb
>  * The following is pyspark code
>  * create a parallelized rdd like: {color:#FF0000}prdd = spark.read.text("test.csv").rdd.flatMap(lambda x : x){color}
>  * {color:#172b4d}create a df like so: {color:#de350b}mydf = spark.read.csv(prdd, header=True){color}{color}
>  * {color:#172b4d}{color:#de350b}df.count(){color:#172b4d} will result in a record count of zero (when it should be 1){color}{color}{color}



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