sparklyr: create new column with mutate function

I'm very surprised if this kind of problems cannot be solved with sparklyr:

iris_tbl <- copy_to(sc, aDataFrame)

# date_vector is a character vector of element
# in this format: YYYY-MM-DD (year, month, day)
for (d in date_vector) {
   ...
   aDataFrame %>% mutate(newValue=gsub("-","",d)))
   ...
}

I receive this error:

Error: org.apache.spark.sql.AnalysisException: Undefined function: 'GSUB'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 2 pos 86
    at org.apache.spark.sql.catalyst.catalog.SessionCatalog.failFunctionLookup(SessionCatalog.scala:787)
    at org.apache.spark.sql.hive.HiveSessionCatalog.lookupFunction0(HiveSessionCatalog.scala:200)
    at org.apache.spark.sql.hive.HiveSessionCatalog.lookupFunction(HiveSessionCatalog.scala:172)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$6$$anonfun$applyOrElse$39.apply(Analyzer.scala:884)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun$applyOrElse$6$$anonfun$applyOrElse$39.apply(Analyzer.scala:884)
    at org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:48)
    at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$13$$anonfun

But with this line:

aDataFrame %>% mutate(newValue=toupper("hello"))

things work. Some help?

Solution

I would strongly recommend you read the sparklyr documentation before proceeding. In particular, you're going to want to read the section on how R is translated to SQL (http://spark.rstudio.com/dplyr.html#sql_translation). In short, a very limited subset of R functions are available for use on sparklyr dataframes, and gsub is not one of those functions (but toupper is). If you really need gsub you're going to have to collect the data in to a local dataframe, then gsub it (you can still use mutate), then copy_to back to spark.