Updated H2O in R, Flow won´t start - rstudio

Question

I am using H2O from via an Amazon Ubuntu EC2 AMI I created half a year ago. It works well: When needed I fire up an instance, start H2O in rstudio, go to the flow interface, do my thing and close t down again
But when I try to update H2O to the latest build I cannot access flow. Everything apparently works in rstudio but not flow. I suspect Java, a restart of rstudio and/or the H2O build that is the bleeding edge build number even if I request the latest stable version. t could have
I follow the instructions here:
http://docs.h2o.ai/h2o/latest-stable/h2o-docs/downloading.html#install-in-r
and this is the rstudio console
h2o.init()
H2O is not running yet, starting it now...
Note: In case of errors look at the following log files:
/tmp/RtmpKNp0jt/h2o_rstudio_started_from_r.out
/tmp/RtmpKNp0jt/h2o_rstudio_started_from_r.err
openjdk version "1.8.0_171"
OpenJDK Runtime Environment (build 1.8.0_171-8u171-b11-0ubuntu0.16.04.1-b11)
OpenJDK 64-Bit Server VM (build 25.171-b11, mixed mode)
Starting H2O JVM and connecting: .......... Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 22 seconds 380 milliseconds
H2O cluster timezone: Etc/UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.21.0.4364
H2O cluster version age: 3 months and 13 days !!!
H2O cluster name: H2O_started_from_R_rstudio_urm169
H2O cluster total nodes: 1
H2O cluster total memory: 0.86 GB
H2O cluster total cores: 2
H2O cluster allowed cores: 2
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 3.4.2 (2017-09-28)
Warning message:
In h2o.clusterInfo() :
Your H2O cluster version is too old (3 months and 13 days)!
Please download and install the latest version from http://h2o.ai/download/
if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
[1] "A shutdown has been triggered. "
if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }
Removing package from ‘/home/rstudio/R/x86_64-pc-linux-gnu-library/3.4’
(as ‘lib’ is unspecified)
pkgs <- c("RCurl","jsonlite")
for (pkg in pkgs) {
+ if (! (pkg %in% rownames(installed.packages()))) {
install.packages(pkg) }
+ }
install.packages("h2o", type="source", repos=(c("http://h2o-
release.s3.amazonaws.com/h2o/latest_stable_R")))
Installing package into ‘/home/rstudio/R/x86_64-pc-linux-gnu-library/3.4’
(as ‘lib’ is unspecified)
trying URL 'http://h2o-release.s3.amazonaws.com/h2o/latest_stable_R
/src/contrib/h2o_3.23.0.4471.tar.gz'
Content type 'application/x-tar' length 120706169 bytes (115.1 MB)
==================================================
downloaded 115.1 MB
* installing *source* package ‘h2o’ ...
** R
** demo
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded
* DONE (h2o)
The downloaded source packages are in
‘/tmp/RtmpKNp0jt/downloaded_packages’
library(h2o)
Error: package or namespace load failed for ‘h2o’ in get(method, envir =
home):
lazy-load database '/home/rstudio/R/x86_64-pc-linux-gnu-
library/3.4/h2o/R/h2o.rdb' is corrupt
In addition: Warning message:
In get(method, envir = home) : internal error -3 in R_decompress1
Because of the error message I restart R via the menu in rstudio
Restarting R session...
library(h2o)
----------------------------------------------------------------------
Your next step is to start H2O:
> h2o.init()
For H2O package documentation, ask for help:
> ??h2o
After starting H2O, you can use the Web UI at http://localhost:54321
For more information visit http://docs.h2o.ai
----------------------------------------------------------------------
Attaching package: ‘h2o’
The following objects are masked from ‘package:stats’:
cor, sd, var
The following objects are masked from ‘package:base’:
||, &&, %*%, apply, as.factor, as.numeric, colnames, colnames<-, ifelse,
%in%,
is.character, is.factor, is.numeric, log, log10, log1p, log2, round, signif,
trunc
h2o.init()
H2O is not running yet, starting it now...
Note: In case of errors look at the following log files:
/tmp/RtmpMdVz9z/h2o_rstudio_started_from_r.out
/tmp/RtmpMdVz9z/h2o_rstudio_started_from_r.err
openjdk version "1.8.0_181"
OpenJDK Runtime Environment (build 1.8.0_181-8u181-b13-1ubuntu0.16.04.1-b13)
OpenJDK 64-Bit Server VM (build 25.181-b13, mixed mode)
Starting H2O JVM and connecting: . Connection successful!
R is connected to the H2O cluster:
H2O cluster uptime: 1 seconds 744 milliseconds
H2O cluster timezone: Etc/UTC
H2O data parsing timezone: UTC
H2O cluster version: 3.23.0.4471
H2O cluster version age: 9 hours and 21 minutes
H2O cluster name: H2O_started_from_R_rstudio_rrc849
H2O cluster total nodes: 1
H2O cluster total memory: 0.86 GB
H2O cluster total cores: 2
H2O cluster allowed cores: 2
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 3.4.2 (2017-09-28)
From here on H2O works in rstudio but flow won´t start.
Any suggestions?

Answer 1

I suggest to update to the newest version 3.22.0.1. Then initialise the cluster so that it does not bind only to localhost: init(bind_to_localhost=False). When you initialise H2O from R or Python, the instance binds by default to localhost only which means that you can access it from RStudio because it is running on the server, but not via Flow because then you access it from your distant browser.
Another option is to start H2O independently from command line.
Beware that if you do not bind H2O to localhost only, it is then accessible to anybody who can access the port and the network interface, which can pose a significant security hole (exposing your data, models, etc.).