## What changes were proposed in this pull request?
This PR adds a new function in SparkR called `sparkLapply(list, function)`. This function implements a distributed version of `lapply` using Spark as a backend.
TODO:
- [x] check documentation
- [ ] check tests
Trivial example in SparkR:
```R
sparkLapply(1:5, function(x) { 2 * x })
```
Output:
```
[[1]]
[1] 2
[[2]]
[1] 4
[[3]]
[1] 6
[[4]]
[1] 8
[[5]]
[1] 10
```
Here is a slightly more complex example to perform distributed training of multiple models. Under the hood, Spark broadcasts the dataset.
```R
library("MASS")
data(menarche)
families <- c("gaussian", "poisson")
train <- function(family){glm(Menarche ~ Age , family=family, data=menarche)}
results <- sparkLapply(families, train)
```
## How was this patch tested?
This PR was tested in SparkR. I am unfamiliar with R and SparkR, so any feedback on style, testing, etc. will be much appreciated.
cc falaki davies
Author: Timothy Hunter <timhunter@databricks.com>
Closes#12426 from thunterdb/7264.
769a909d13