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benchmark({
  key_to_lookup <- select_random_key()
  time(data_table[.(key_to_lookup), nomatch = 0L])
})

##     min     max    mean 
## 0.00200 0.01200 0.00455 

darioappsilon

time(setkey(data_table, col1))
5.645

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# Try it yourself: 

environment_source <- setNames(as.list(data$col2), data$col1) 
time(as.environment(environment_source))

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benchmark({
  key_to_lookup <- select_random_key()
  time(data[which(data$col1 == key_to_lookup),])
})

##     min     max    mean 
## 0.09200 0.15800 0.10471 

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benchmark({
  key_to_lookup <- select_random_key()
  time(data[data$col1 == key_to_lookup,])
})

##     min     max    mean 
## 0.09800 0.22300 0.11424

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library(data.table)

data_table <- data.table(data)

benchmark({
  key_to_lookup <- select_random_key()
  time(data_table[col1 == key_to_lookup])
})

##     min     max    mean 

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library(dplyr)

benchmark({
  key_to_lookup <- select_random_key()
  time(data %>% filter(col1 == key_to_lookup))
})

## min max mean 
## 0.0960 0.2440 0.1124 

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time <- function(...) { 
  time_measurement <- system.time(eval(...)) 
  time_measurement[["user.self"]] 
} 

benchmark <- function(..., n = 100) { 
  times <- replicate(n, ...) 
  c(min = min(times), max = max(times), mean = mean(times)) 
}

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library(tibble) 

random_string_column <- function(n) { 
  stringi::stri_rand_strings(n = n, length = 8) 
} 

random_data_frame <- function(n) tibble( 
  col1 = random_string_column(n), 
  col2 = random_string_column(n) 
) 

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d$make_sound(sound = "Woooof!")