FULL OF WIN

gistfile1.r

> map <- expression({
+   lapply(seq_along(map.values),function(r){
+     x <- runif(map.values[[r]])
+     rhcollect(map.keys[[r]],c(n=map.values[[r]],mean=mean(x),sd=sd(x)))
+   })
+ })
> 
> z <- rhmr(map, ofolder="/tmp/test", inout=c('lapply','sequence'),
+           N=10,mapred=list(mapred.reduce.tasks=0),jobname='test')
Error: could not find function "rhmr"
> library(Rhipe)
RHIPE: Cleaning up  associated server (PID=16925)
> rhwrite(list(1,2,3),"/tmp/x",1)
Wrote 3 pairs occupying 57 bytes
[1] TRUE
> rhread("/tmp/x")
RHIPE: Read 5 pairs occupying 95 bytes, deserializing
[[1]]
[[1]][[1]]
[1] "1"

[[1]][[2]]
[1] 1


[[2]]
[[2]][[1]]
[1] "2"

[[2]][[2]]
[1] 2


[[3]]
[[3]][[1]]
[1] "3"

[[3]][[2]]
[1] 3


[[4]]
[[4]][[1]]
[1] "2"

[[4]][[2]]
[1] 2


[[5]]
[[5]][[1]]
[1] "3"

[[5]][[2]]
[1] 3


> map <- expression({
+   lapply(seq_along(map.values),function(r){
+     x <- runif(map.values[[r]])
+     rhcollect(map.keys[[r]],c(n=map.values[[r]],mean=mean(x),sd=sd(x)))
+   })
+ })
> z <- rhmr(map, ofolder="/tmp/test", inout=c('lapply','sequence'),
+           N=10,mapred=list(mapred.reduce.tasks=0),jobname='test')
> rhex(z)
----------------------------------------
Running:  $HADOOP/bin/hadoop jar /usr/local/lib/R/site-library/Rhipe/java/Rhipe.jar org.godhuli.rhipe.RHMR /tmp/Rtmpben7g6/rhipe2ed99297
----------------------------------------
10/11/19 19:22:26 INFO rhipe.RHMR: Tracking URL ----> http://master.hadoop.forward.co.uk:50030/jobdetails.jsp?jobid=job_201011110039_29400
10/11/19 19:22:26 INFO mapred.JobClient: Running job: job_201011110039_29400
10/11/19 19:22:27 INFO mapred.JobClient:  map 0% reduce 0%
10/11/19 19:22:38 INFO mapred.JobClient:  map 100% reduce 0%
10/11/19 19:22:40 INFO mapred.JobClient: Job complete: job_201011110039_29400
10/11/19 19:22:40 INFO mapred.JobClient: Counters: 11
10/11/19 19:22:40 INFO mapred.JobClient:   Job Counters 
10/11/19 19:22:40 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=9799
10/11/19 19:22:40 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0
10/11/19 19:22:40 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0
10/11/19 19:22:40 INFO mapred.JobClient:     Launched map tasks=2
10/11/19 19:22:40 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=0
10/11/19 19:22:40 INFO mapred.JobClient:   FileSystemCounters
10/11/19 19:22:40 INFO mapred.JobClient:     HDFS_BYTES_READ=138
10/11/19 19:22:40 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=988
10/11/19 19:22:40 INFO mapred.JobClient:   Map-Reduce Framework
10/11/19 19:22:40 INFO mapred.JobClient:     Map input records=10
10/11/19 19:22:40 INFO mapred.JobClient:     Spilled Records=0
10/11/19 19:22:40 INFO mapred.JobClient:     Map output records=10
10/11/19 19:22:40 INFO mapred.JobClient:     SPLIT_RAW_BYTES=138
result:256
$state
[1] TRUE

$counters
$counters$FileSystemCounters
   HDFS_BYTES_READ HDFS_BYTES_WRITTEN 
               138                988 

$counters$`Job Counters `
   Total time spent by all maps waiting after reserving slots (ms) 
                                                                 0 
Total time spent by all reduces waiting after reserving slots (ms) 
                                                                 0 
                                                 SLOTS_MILLIS_MAPS 
                                                              9799 
                                              SLOTS_MILLIS_REDUCES 
                                                                 0 
                                                Launched map tasks 
                                                                 2 

$counters$`Map-Reduce Framework`
 Map input records Map output records    Spilled Records    SPLIT_RAW_BYTES 
                10                 10                  0                138 

$counters$job_time
[1] 14.076


> res <- rhread('/tmp/test/p*')
RHIPE: Read 10 pairs occupying 700 bytes, deserializing
> colres  <- do.call('rbind', lapply(res,"[[",2))
> colres
       n      mean        sd
 [1,]  1 0.1205761        NA
 [2,]  2 0.1635505 0.1230097
 [3,]  3 0.7054041 0.4043578
 [4,]  4 0.6265748 0.3632526
 [5,]  5 0.6605429 0.3868235
 [6,]  6 0.5150720 0.2967631
 [7,]  7 0.5233840 0.2131576
 [8,]  8 0.5925578 0.2602574
 [9,]  9 0.6118205 0.3150155
[10,] 10 0.7093372 0.2202394