[
https://issues.apache.org/jira/browse/SPARK-11167?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14978007#comment-14978007
]
Sun Rui commented on SPARK-11167:
---------------------------------
It seems time-consuming and not desirable to going through the entire input
data to infer the tightest type or to check if heterogeneous values exist. I
agree with [~zero323] that it is practical to issue a warning in such case.
Users should be responsible for homogeneous input data. Otherwise, there maybe
runtime exception on type mismatch thrown by Spark.
> 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
>
> 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}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
