R 在 data.table 列中拆分文本字符串

我有一个脚本，可以将CSV文件中的数据读入data.table，然后将一列中的文本拆分为几列.我目前正在使用lapply和strsplit函数来实现这一点.下面是一个例子:

library("data.table")
df = data.table(PREFIX = c("A_B","A_C","A_D","B_A","B_C","B_D"),
                VALUE  = 1:6)
dt = as.data.table(df)

# split PREFIX into new columns
dt$PX = as.character(lapply(strsplit(as.character(dt$PREFIX), split="_"), "[", 1))
dt$PY = as.character(lapply(strsplit(as.character(dt$PREFIX), split="_"), "[", 2))

dt 
#    PREFIX VALUE PX PY
# 1:    A_B     1  A  B
# 2:    A_C     2  A  C
# 3:    A_D     3  A  D
# 4:    B_A     4  B  A
# 5:    B_C     5  B  C
# 6:    B_D     6  B  D 

在上面的示例中，列PREFIX被拆分为两个新的列PX和PY，分别位于"u"字符上.

Even though this works just fine, I was wondering if there is a better (more efficient) way to do this using data.table. My real datasets have >=10M+ rows, so time/memory efficiency becomes really important.

更新:

按照@Frank的建议，我创建了一个更大的测试用例，并使用了建议的命令，但stringr::str_split_fixed比最初的方法花费的时间要长得多.

library("data.table")
library("stringr")
system.time ({
    df = data.table(PREFIX = rep(c("A_B","A_C","A_D","B_A","B_C","B_D"), 1000000),
                    VALUE  = rep(1:6, 1000000))
    dt = data.table(df)
})
#   user  system elapsed 
#  0.682   0.075   0.758 

system.time({ dt[, c("PX","PY") := data.table(str_split_fixed(PREFIX,"_",2))] })
#    user  system elapsed 
# 738.283   3.103 741.674 

rm(dt)
system.time ( {
    df = data.table(PREFIX = rep(c("A_B","A_C","A_D","B_A","B_C","B_D"), 1000000),
                     VALUE = rep(1:6, 1000000) )
    dt = as.data.table(df)
})
#    user  system elapsed 
#   0.123   0.000   0.123 

# split PREFIX into new columns
system.time ({
    dt$PX = as.character(lapply(strsplit(as.character(dt$PREFIX), split="_"), "[", 1))
    dt$PY = as.character(lapply(strsplit(as.character(dt$PREFIX), split="_"), "[", 2))
})
#    user  system elapsed 
#  33.185   0.000  33.191 

因此，str_split_fixed法需要大约20倍的时间.