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https://issues.apache.org/jira/browse/SPARK-11167?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-11167.
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Resolution: Incomplete
> Incorrect type resolution on heterogeneous data structures
> ----------------------------------------------------------
>
> Key: SPARK-11167
> URL: https://issues.apache.org/jira/browse/SPARK-11167
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Affects Versions: 1.6.0
> Reporter: Maciej Szymkiewicz
> Priority: Major
> Labels: bulk-closed
>
> If structure contains heterogeneous incorrectly assigns type of the
> encountered element as type of a whole structure. This problem affects both
> lists:
> {code}
> SparkR:::infer_type(list(a=1, b="a")
> ## [1] "array<double>"
> SparkR:::infer_type(list(a="a", b=1))
> ## [1] "array<string>"
> {code}
> and environments:
> {code}
> SparkR:::infer_type(as.environment(list(a=1, b="a")))
> ## [1] "map<string,double>"
> SparkR:::infer_type(as.environment(list(a="a", b=1)))
> ## [1] "map<string,string>"
> {code}
> This results in errors during data collection and other operations on
> DataFrames:
> {code}
> ldf <- data.frame(row.names=1:2)
> ldf$foo <- list(list("1", 2), list(3, 4))
> sdf <- createDataFrame(sqlContext, ldf)
> collect(sdf)
> ## 15/10/17 17:58:57 ERROR Executor: Exception in task 0.0 in stage 9.0 (TID
> 9)
> ## scala.MatchError: 2.0 (of class java.lang.Double)
> ## ...
> {code}
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