library(rredis)

# Get a message sent from Mike's machine.
host="192.168.1.65"
redisConnect(host="<PUT IP ADDRESS HERE>")

redisRPush("example1", "Hello from Mike's Mac")

# Now send a message back to Mike's Mac

redisLPop("example1")

cm <- c()
for (i in 1:redisLLen("colmeans")) {
  cm <- c(cm, redisBLPop("colmeans", timeout=10)$colmeans)
}

library(doRedis)
library(itertools)

registerDoRedis(queue="ClinicCluster", host=host)
numberCols <- 100
x <- matrix(rnorm(1000), ncol=numberCols)

cm <- foreach(j=isplitVector(1:numberCols, chunkSize=10), .combine=c) %dopar% {
  print("thanks for your cycles!")
  apply(x[, j, drop=FALSE], 2, mean)
}

# Airline example

depDelays <- foreach (airlineYear=1987:1988, .combine=c) %dopar% {
  # Grab the file.
  fileName <- paste(airlineYear, ".csv.bz2", sep="")
  print(paste("Grabbing file", fileName))
  system(
    paste('wget http://stat-computing.org/dataexpo/2009/', fileName, sep=""))
  print("file downloaded, creating data frame")
  # Read in first 1000 rows of the the data frame
  x <- read.csv(bzfile(paste(airlineYear, ".csv.bz2", sep="")), nrows=10000)
  print("returning result, thanks for the cycles")
  # Delete the file
  unlink(fileName)
  # Return the mean departure delay
  mean(x$DepDelay, na.rm=TRUE)
}