If I don't specify anything, it allocates 0.24Gb
Starting H2O JVM and connecting: . Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 2 seconds 711 milliseconds
H2O cluster timezone: Etc/UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.22.1.1
H2O cluster version age: 12 days
H2O cluster name: H2O_started_from_R_rstudio-user_zdn362
H2O cluster total nodes: 1
H2O cluster total memory: 0.24 GB
H2O cluster total cores: 1
H2O cluster allowed cores: 1
H2O cluster healthy: TRUE
H2O Connection ip: localhost
H2O Connection port: 54321
H2O Connection proxy: NA
H2O Internal Security: FALSE
H2O API Extensions: XGBoost, Algos, AutoML, Core V3, Core V4
R Version: R version 3.5.0 (2018-04-23)
Yesterday I remember seeing 700MB allocated by default. Strange. I can still override the default and allocate, say 600MB like so:
library(h2o)
h2o.init(max_mem_size = "600M"
h2o.clusterInfo()
#> R is connected to the H2O cluster:
#> H2O cluster uptime: 2 seconds 577 milliseconds
#> H2O cluster timezone: Etc/UTC
#> H2O data parsing timezone: UTC
#> H2O cluster version: 3.22.1.1
#> H2O cluster version age: 12 days
#> H2O cluster name: H2O_started_from_R_rstudio-user_lau902
#> H2O cluster total nodes: 1
#> H2O cluster total memory: 0.57 GB
#> H2O cluster total cores: 1
#> H2O cluster allowed cores: 1
#> H2O cluster healthy: TRUE
#> H2O Connection ip: localhost
#> H2O Connection port: 54321
#> H2O Connection proxy: NA
#> H2O Internal Security: FALSE
#> H2O API Extensions: XGBoost, Algos, AutoML, Core V3, Core V4
#> R Version: R version 3.5.0 (2018-04-23)
Flow interface does not seem to be getting through to JVM.