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https://issues.apache.org/jira/browse/SPARK-13905?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15195066#comment-15195066
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Apache Spark commented on SPARK-13905:
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User 'sun-rui' has created a pull request for this issue:
https://github.com/apache/spark/pull/11726
> Change implementation of as.data.frame() to avoid conflict with the ones in
> the R base package
> ----------------------------------------------------------------------------------------------
>
> Key: SPARK-13905
> URL: https://issues.apache.org/jira/browse/SPARK-13905
> Project: Spark
> Issue Type: Improvement
> Components: SparkR
> Affects Versions: 1.6.1
> Reporter: Sun Rui
>
> SparkR provides a method as.data.frame() to collect a SparkR DataFrame into a
> local data.frame. But it conflicts the methods with the same name in the R
> base package.
> For example,
> {code}
> code as follows -
> countData <- matrix(1:100,ncol=4)
> condition <- factor(c("A","A","B","B"))
> dds <- DESeqDataSetFromMatrix(countData, DataFrame(condition), ~ condition)
> Works if i dont initialize the sparkR environment.
> if I do library(SparkR) and sqlContext <- sparkRSQL.init(sc) it gives
> following error
> > dds <- DESeqDataSetFromMatrix(countData, as.data.frame(condition), ~
> > condition)
> Error in DataFrame(colData, row.names = rownames(colData)) :
> cannot coerce class "data.frame" to a DataFrame
> {code}
> The implementation of as.data.frame() in SparkR can be improved to avoid
> conflict with those in the R base package.
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