Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/15231#discussion_r80425776
--- Diff: R/pkg/R/utils.R ---
@@ -698,6 +698,21 @@ isSparkRShell <- function() {
grepl(".*shell\\.R$", Sys.getenv("R_PROFILE_USER"), perl = TRUE)
}
+captureJVMException <- function(e) {
+ stacktrace <- as.character(e)
+ if (any(grep("java.lang.IllegalArgumentException: ", stacktrace))) {
--- End diff --
Thanks! @felixcheung I will address all other comments above. However, for
this one, I was thinking hard but it seems not easy because we won't know if
given data source is valid or not in R side first.
I might be able to do this only for internal data sources or known
databricks datasources such as "redshift" or "xml" like.. creating a map for
our internal data sources and then checking a path is given or not. However, I
am not sure if it is a good idea to manage another list for datasources.
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