HyukjinKwon commented on a change in pull request #23746: [SPARK-26761][SQL][R]
Vectorized R gapply() implementation
URL: https://github.com/apache/spark/pull/23746#discussion_r255871315
##########
File path: R/pkg/inst/worker/worker.R
##########
@@ -181,17 +185,37 @@ if (isEmpty != 0) {
colNames, computeFunc, data)
} else {
# gapply mode
+ outputs <- list()
for (i in 1:length(data)) {
# Timing reading input data for execution
inputElap <- elapsedSecs()
output <- compute(mode, partition, serializer, deserializer,
keys[[i]],
colNames, computeFunc, data[[i]])
computeElap <- elapsedSecs()
- outputResult(serializer, output, outputCon)
+ if (deserializer == "arrow") {
+ outputs[[length(outputs) + 1L]] <- output
Review comment:
```r
outputA <- list()
outputB <- list()
testA <- function() {
options(digits.secs = 6) # milliseconds
start.time <- Sys.time()
output <- list()
for (i in 1:10000) {
output[[length(output) + 1L]] <- 1
}
end.time <- Sys.time()
time.taken <- end.time - start.time
print(time.taken)
output
}
testB <- function() {
options(digits.secs = 6) # milliseconds
start.time <- Sys.time()
output <- list()
for (i in 1:10000) {
output <- append(output, 1)
}
end.time <- Sys.time()
time.taken <- end.time - start.time
print(time.taken)
output
}
require(testthat)
outputA <- testA()
outputB <- testB()
expect_equal(outputA, outputB)
```
Looks direct assignement is faster:
```
Time difference of 0.008903027 secs
Time difference of 0.5212681 secs
```
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