A question about the parallelism in h2o.grid() function

I try to use the h2o.grid() function from the h2o package to do some tuning using R, when I set the parameter parallelism larger then 1, it always shows the warning

Some models were not built due to a failure, for more details run `summary(grid_object, show_stack_traces = TRUE)

And the model_ids in the final grid object includes many models end with _cv_1, _cv_2 etc, and the number of the models is not equal to the setting of my max_models in search_criteria list, I think they are just the models in the cv process, not the final model.

When I set parallelism larger than 1:

When I leave the parallelism default or set it to 1, the result is normal, all models end with _model_1, _model_2 etc.

When I leave the "parallelism" default or set it to 1:

Here is my code:

# set the grid
rf_h2o_grid <- list(mtries = seq(3, ncol(train_h2o), 4),
                    max_depth = c(5, 10, 15, 20))

# set the search_criteria
sc <- list(strategy = "RandomDiscrete", 
           seed = 100,
           max_models = 5
           )

# random grid tuning
rf_h2o_grid_tune_random <- h2o.grid(
  algorithm = "randomForest", 
  x = x, 
  y = y,
  training_frame = train_h2o,
  nfolds = 5,                     # use cv to validate the parameters
  fold_assignment = "Stratified",   
  ntrees = 100,
  seed = 100,
  hyper_params = rf_h2o_grid,
  search_criteria = sc
  # parallelism = 6           # when I set it larger than 1, the result always includes some "cv_" models
  )

So how can I use the parallelism correctly in h2o.grid()? Thanks for helping!

This is an actual issue with parallelism in grid search, previously noticed but not reported correctly. Thanks for raising this, we'll try to fix it soon: see https://h2oai.atlassian.net/browse/PUBDEV-7886 if you want to track progress.

Until proper fix, you must avoid using both CV and parallelism in your grids.

Regarding the following error:

Some models were not built due to a failure, for more details run `summary(grid_object, show_stack_traces = TRUE)

if the error is reproducible, you should be getting more details by running the grid with verbose=True. Adding the entire error message to the ticket above might also help.