Use output of boot2docker ip instead of localhost

nagyistoce · Jan 17, 2015 · 9687cd0 · 9687cd0
1 parent 8b9a8f2
commit 9687cd0
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diff --git a/R/examples/H2ODeepLearningNextML.R b/R/examples/H2ODeepLearningNextML.R
@@ -1,3 +1,5 @@
+
+
 ## Install H2O R package (same version as H2O Server)
 if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
 if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }
@@ -6,7 +8,7 @@ install.packages("h2o", repos=(c("http://h2o-release.s3.amazonaws.com/h2o/rel-mi
 ## Load H2O R libary
 library(h2o)
 
-## Connect to H2O Server
+## Connect to H2O Server (replace localhost with output of `boot2docker ip`)
 h2oServer <- h2o.init(ip="localhost", port=8996)
 
 

diff --git a/R/examples/manycols.R b/R/examples/manycols.R
@@ -13,7 +13,7 @@ library(h2o)
 #hadoop fs -rm -r myDir
 #hadoop jar h2odriver_hdp2.1.jar water.hadoop.h2odriver -libjars ../h2o.jar -n 8 -mapperXmx 40g -output myDir -baseport 61111 -data_max_factor_levels 65000 -chunk_bits 24
 
-h2oCluster <- h2o.init(ip="mr-0xd1", port=61111)
+h2oCluster <- h2o.init(ip="mr-0xd1", port=6FedEx1111)
 
 # Read data from HDFS
 data.hex <- h2o.importFile(h2oCluster, "hdfs://mr-0xd6/datasets/15Mx2.2k.csv")