[GitHub] felixcheung commented on a change in pull request #23787: [SPARK-26830][SQL][R] Vectorized R dapply() implementation

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felixcheung commented on a change in pull request #23787: [SPARK-26830][SQL][R] Vectorized R dapply() implementation
URL: https://github.com/apache/spark/pull/23787#discussion_r259236795
 
 

 ##########
 File path: R/pkg/R/DataFrame.R
 ##########
 @@ -1437,6 +1437,29 @@ dapplyInternal <- function(x, func, schema) {
     schema <- structType(schema)
   }
 
+  arrowEnabled <- sparkR.conf("spark.sql.execution.arrow.enabled")[[1]] == "true"
+  if (arrowEnabled) {
+    requireNamespace1 <- requireNamespace
+    if (!requireNamespace1("arrow", quietly = TRUE)) {
+      stop("'arrow' package should be installed.")
+    }
+    # Currenty Arrow optimization does not support raw for now.
+    # Also, it does not support explicit float type set by users.
+    if (inherits(schema, "structType")) {
+      if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "FloatType"))) {
+        stop("Arrow optimization with dapply do not support FloatType yet.")
+      }
+      if (any(sapply(schema$fields(), function(x) x$dataType.toString() == "BinaryType"))) {
+        stop("Arrow optimization with dapply do not support BinaryType yet.")
+      }
+    } else if (is.null(schema)) {
+      stop(paste0("Arrow optimization does not support 'dapplyCollect' yet. Please use ",
+                  "'collect' and 'dapply' APIs instead."))
 
 Review comment:
   this isn't quite the same though, for example, dapply will need the user to pass in a schema. should we suggest turning off arrow then use dapplyCollect? I'm actually not sure - maybe suggest both in the message?

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