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R/tests/testdir_hdfs_xlarge/runit_GLM_airlines_billion_xlarge.R
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#---------------------------------------------------------------------- | ||
# Purpose: This test exercises HDFS operations from R. | ||
#---------------------------------------------------------------------- | ||
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setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f"))) | ||
source('../findNSourceUtils.R') | ||
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ipPort <- get_args(commandArgs(trailingOnly = TRUE)) | ||
myIP <- ipPort[[1]] | ||
myPort <- ipPort[[2]] | ||
hdfs_name_node <- Sys.getenv(c("NAME_NODE")) | ||
print(hdfs_name_node) | ||
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library(RCurl) | ||
library(testthat) | ||
library(h2o) | ||
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heading("BEGIN TEST") | ||
conn <- h2o.init(ip=myIP, port=myPort, startH2O = FALSE) | ||
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hdfs_data_file = "/datasets/airlinesbillion.csv" | ||
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#---------------------------------------------------------------------- | ||
# Single file cases. | ||
#---------------------------------------------------------------------- | ||
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heading("Testing single file importHDFS") | ||
url <- sprintf("hdfs://%s%s", hdfs_name_node, hdfs_data_file) | ||
parse_time <- system.time(data.hex <- h2o.importFile(conn, url)) | ||
paste("Time it took to parse", parse_time[[1]]) | ||
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data1.hex <- data.hex | ||
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n <- nrow(data.hex) | ||
print(n) | ||
if (n != 1166952590) { | ||
stop("nrows is wrong") | ||
} | ||
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#Constructing validation and train sets by sampling (20/80) | ||
#creating a column as tall as airlines(nrow(air)) | ||
s <- h2o.runif(data.hex) # Useful when number of rows too large for R to handle | ||
data.train <- data.hex[s <= 0.8,] | ||
data.valid <- data.hex[s > 0.8,] | ||
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## Response = Distance | ||
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myY = "C19" | ||
#myX = setdiff(names(data.hex), c(myY, "")) | ||
myX = c("C20", "C21", "C22", "C23", "C24", "C25", "C26", "C27", "C28", "C29") | ||
## Build GLM Model and compare AUC with h2o1 | ||
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#glm_irlsm_time <- system.time(data_irlsm.glm <- h2o.glm(x = myX, y = myY, data = data.train, validation=data.valid, family = "gaussian", solver = "IRLSM")) | ||
glm_time <- system.time(data.glm <- h2o.glm(x = myX, y = myY, data = data.train, family = "gaussian")) | ||
data.glm | ||
paste("Time it took to build GLM ", glm_time[[1]]) | ||
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PASS_BANNER() |
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package water.api; | ||
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import water.DTask; | ||
import water.H2O; | ||
import water.H2ONode; | ||
import water.RPC; | ||
import water.util.Log; | ||
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public class GarbageCollect extends Request { | ||
private static class GCTask extends DTask<GCTask> { | ||
public GCTask() { | ||
} | ||
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@Override public void compute2() { | ||
Log.info("Calling System.gc() now..."); | ||
System.gc(); | ||
Log.info("System.gc() finished"); | ||
tryComplete(); | ||
} | ||
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@Override public byte priority() { | ||
return H2O.MIN_HI_PRIORITY; | ||
} | ||
} | ||
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@Override public RequestBuilders.Response serve(){ | ||
for (H2ONode node : H2O.CLOUD._memary) { | ||
GCTask t = new GCTask(); | ||
new RPC<GCTask>(node, t).call().get(); | ||
} | ||
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return RequestBuilders.Response.doneEmpty(); | ||
} | ||
} |
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