You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/09/15 23:39:01 UTC
[jira] [Assigned] (SPARK-32888) reading a parallized rdd with two
identical records results in a zero count df when read via spark.read.csv
[ https://issues.apache.org/jira/browse/SPARK-32888?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-32888:
------------------------------------
Assignee: (was: 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
> 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}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org