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https://issues.apache.org/jira/browse/SPARK-32888?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-32888:
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Assignee: Apache Spark
> 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: Apache Spark
> Priority: Minor
>
> * 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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