Github user falaki commented on a diff in the pull request:
https://github.com/apache/spark/pull/15375#discussion_r82446808
--- Diff: R/pkg/R/context.R ---
@@ -123,19 +126,48 @@ parallelize <- function(sc, coll, numSlices = 1) {
if (numSlices > length(coll))
numSlices <- length(coll)
+ sizeLimit <- as.numeric(sparkR.conf(
+ "spark.r.maxAllocationLimit",
+ toString(.Machine$integer.max / 2) # Default to a safe default: 200MB
+ ))
+ objectSize <- object.size(coll)
+
+ # For large objects we make sure the size of each slice is also smaller
than sizeLimit
+ numSlices <- max(numSlices, ceiling(objectSize / sizeLimit))
+
sliceLen <- ceiling(length(coll) / numSlices)
slices <- split(coll, rep(1: (numSlices + 1), each =
sliceLen)[1:length(coll)])
# Serialize each slice: obtain a list of raws, or a list of lists
(slices) of
# 2-tuples of raws
serializedSlices <- lapply(slices, serialize, connection = NULL)
- jrdd <- callJStatic("org.apache.spark.api.r.RRDD",
- "createRDDFromArray", sc, serializedSlices)
+ # The PRC backend cannot handle arguments larger than 2GB (INT_MAX)
+ # If serialized data is safely less than that threshold we send it over
the PRC channel.
+ # Otherwise, we write it to a file and send the file name
+ if (objectSize < sizeLimit) {
+ jrdd <- callJStatic("org.apache.spark.api.r.RRDD",
"createRDDFromArray", sc, serializedSlices)
+ } else {
+ fileName <- writeToTempFile(serializedSlices)
+ jrdd <- callJStatic(
+ "org.apache.spark.api.r.RRDD", "createRDDFromFile", sc, fileName,
as.integer(numSlices))
+ file.remove(fileName)
--- End diff --
Good point. Done!
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