the demo("bench-merge") cannot be run for various reasons

[knbknb]

This command:

demo(package = .packages(all.available = TRUE))  

yields

Demos in package ‘dplyr’:
bench-merge                         Benchmark merging between R and python
bench-rbind                         Benchmark various flavours of rbind
bench-set                           Benchmark set operations on data frames

However, demo "bench-merge" cannot be run by an ordinary user, at least not by me.
(The 2 other demos work properly, though).

I was able to almost make bench-merge run.

I know some python, so I already had a working pandas module installed.
In R, First I had to install some missing packages, microbenchmark. R told me what's needed.
Then I had to create a subdirectory demo/pandas in the package directory
I had to issue a setwd("${r_pkg_directory}/dplyr/demo/"), because this dir did not exist.
Then I had to clone the git repository demo/pandas/bench_merge.py , because this .py file does not get installed by install.packages("dplyr"). The I copied pandas.py from the cloned repo to ${r_pkg_directory}/dplyr/demo/pandas.
I also installed the development version of dplyr because I hoped that would give me all missing files.
Then I was able to run the demo, but now R segfaults.

I think the easiest workaround would be to change the "description" line from

 Benchmark merging between R and python

to something like

 Benchmark merging between R and python (internal demo, for developers only)

Some info about my computing environment.

packageVersion("dplyr")
[1] ‘0.4.3.9000’

R> getwd()
[1] "/home/knb/code/git/dplyr/demo"
R> demo("bench-merge")


    demo(bench-merge)
    ---- ~~~~~~~~~~~

Type     to start : 

R> # Compare base, data table, dplyr and pandas
R> #
R> # To install pandas on OS X:
R> # * brew update && brew install python
R> # * pip install --upgrade setuptools
R> # * pip install --upgrade pip
R> # * pip install pandas
R> 
R> library(dplyr)

R> library(data.table)

R> library(microbenchmark)

R> library(reshape2)

R> set.seed(1014)

R> # Generate sample data ---------------------------------------------------------
R> 
R> random_strings <- function(n, m) {
+   mat <- matrix(sample(letters, m * n, rep = TRUE), ncol = m)
+   apply(mat, 1, paste, collapse = "")
+ }

R> N <- 10000

R> indices  <- random_strings(N, 10)

R> indices2 <- random_strings(N, 10)

R> left <- data.frame(
+   key = rep(indices[1:8000], 10),
+   key2 = rep(indices2[1:8000], 10),
+   value = rnorm(80000)
+ )

R> right <- data.frame(
+   key = indices[2001:10000],
+   key2 = indices2[2001:10000],
+   value2 = rnorm(8000)
+ )

R> write.csv(left, "pandas/left.csv", row.names = FALSE)

R> write.csv(right, "pandas/right.csv", row.names = FALSE)

R> # Equivalent functions for each technique --------------------------------------
R> 
R> base <- list(
+   setup = function(x, y) list(x = x, y = y),
+   
+   left  = function(x, y) base::merge(x, y, all.x = TRUE),
+   right = function(x, y) base::merge(x, y, all.y = TRUE),
+   inner = function(x, y) base::merge(x, y)
+ )

R> data.table <- list(
+   setup = function(x, y) {
+     list(
+       x = data.table(x, key = c("key", "key2")),
+       y = data.table(y, key = c("key", "key2"))
+     )
+   },
+   
+   left  = function(x, y) x[y],
+   right = function(x, y) y[x],
+   inner = function(x, y) merge(x, y, all = FALSE)
+ )

R> dplyr <- list(
+   setup = function(x, y) list(x = x, y = y),
+   
+   left  = function(x, y) left_join(x, y, by = c("key", "key2")),
+   right = function(x, y) NULL,
+   inner = function(x, y) inner_join(x, y, by = c("key", "key2"))
+ )

R> techniques <- list(base = base, data.table = data.table, dplyr = dplyr)

R> # Aggregate results ------------------------------------------------------------
R> 
R> niter <- 10

R> r <- lapply(names(techniques), function(nm) {
+   tech <- techniques[[nm]]
+   df <- tech$setup(left, right)
+   m <- microbenchmark(
+     left = tech$left(df$x, df$y),
+     right = tech$right(df$x, df$y),
+     inner = tech$inner(df$x, df$y),
+     times = niter
+   )
+   
+   means <- tapply(m$time, m$expr, FUN = mean) / 1e9
+   data.frame(type = names(means), mean = means, tech = nm, 
+     row.names = NULL, stringsAsFactors = FALSE)
+ })

 *** caught segfault ***
address 0x2710, cause 'memory not mapped'

Traceback:
 1: .Call("dplyr_left_join_impl", PACKAGE = "dplyr", x, y, by_x,     by_y)
 2: left_join_impl(x, y, by$x, by$y)
 3: left_join.tbl_df(tbl_df(x), y, by = by, copy = copy, ...)
 4: left_join(tbl_df(x), y, by = by, copy = copy, ...)
 5: as.data.frame(left_join(tbl_df(x), y, by = by, copy = copy, ...))
 6: left_join.data.frame(x, y, by = c("key", "key2"))
 7: left_join(x, y, by = c("key", "key2"))
 8: tech$left(df$x, df$y)
 9: microbenchmark(left = tech$left(df$x, df$y), right = tech$right(df$x,     df$y), inner = tech$inner(df$x, df$y), times = niter)
10: FUN(X[[i]], ...)
11: lapply(names(techniques), function(nm) {    tech <- techniques[[nm]]    df <- tech$setup(left, right)    m <- microbenchmark(left = tech$left(df$x, df$y), right = tech$right(df$x,         df$y), inner = tech$inner(df$x, df$y), times = niter)    means <- tapply(m$time, m$expr, FUN = mean)/1e+09    data.frame(type = names(means), mean = means, tech = nm,         row.names = NULL, stringsAsFactors = FALSE)})
12: eval(expr, envir, enclos)
13: eval(ei, envir)
14: withVisible(eval(ei, envir))
15: source(available, echo = echo, max.deparse.length = Inf, keep.source = TRUE,     encoding = encoding)
16: demo("bench-merge")

Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection: 2
Warning messages:
1: In inner_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
2: In inner_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
3: In inner_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
4: In inner_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
5: In inner_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
6: In inner_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
7: In left_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
8: In left_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector

R version 3.2.2 (2015-08-14)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 15.10

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] colorout_1.1-1

[hadley]

Fixed in eb45d04

[lock]

This old issue has been automatically locked. If you believe you have found a related problem, please file a new issue (with reprex) and link to this issue. https://reprex.tidyverse.org/