为什么 data.table 通过引用更新名称（DT），即使我分配给另一个变量？

Question

I've stored the names of a data.table as a vector :

library(data.table)
set.seed(42)
DT <- data.table(x = runif(100), y = runif(100))
names1 <- names(DT)

As far as I can tell, it's a plain vanilla character vector:

str(names1)
# chr [1:2] "x" "y"

class(names1)
# [1] "character"

dput(names1)
# c("x", "y")

However, this is no ordinary character vector. It's a magic character vector! When I add a new column to my data.table , this vector gets updated!

DT[ , z := runif(100)]
names1
# [1] "x" "y" "z"

I know this has something to do with how := updates by assignment, but this still seems magic to me, as I expect <- to make a copy of the data.table 's names.

I can fix this by wrapping the names in c() :

library(data.table)
set.seed(42)
DT <- data.table(x = runif(100), y = runif(100))

names1 <- names(DT)
names2 <- c(names(DT))
all.equal(names1, names2)
# [1] TRUE

DT[ , z := runif(100)]
names1
# [1] "x" "y" "z"

names2
# [1] "x" "y"

My question is 2-fold:

1. Why doesn't names1 <- names(DT) create a copy of the data.table 's names? In other instances, we are explicitly warned that <- creates copies, both of data.table s and data.frame s.
2. What's the difference between names1 <- names(DT) and names2 <- c(names(DT)) ?

Answer 1

Update: This is now added in the documentation for ?copy in version 1.9.3. From NEWS :

14. Moved ?copy to it's own help page, and documented that dt_names <- copy(names(DT)) is necessary for dt_names to be not modified by reference as a result of updating DT by reference (ex: adding a new column by reference). Closes #512 . Thanks to Zach for this SO question and user1971988 for this SO question .

---

Part of your first question makes it a bit unclear to me as to what you really mean about <- operator (at least in the context of data.table ), especially the part: In other instances, we are explicitly warned that <- creates copies, both of data.tables and data.frames.

So, before answering your actual question, I'll briefly touch it here. In case of a data.table a <- (assignment) merely is not sufficient for copying a data.table . For example:

DT <- data.table(x = 1:5, y= 6:10)
# assign DT2 to DT
DT2 <- DT # assign by reference, no copy taken.
DT2[, z := 11:15]
# DT will also have the z column

If you want to create a copy , then you've to explicitly mention it using copy command.

DT2 <- copy(DT) # copied content to DT2
DT2[, z := 11:15] # only DT2 is affected

From CauchyDistributedRV, I understand what you mean is the assignment names(dt) <- . that'll result in the warning. I'll leave it as such.

---

Now, to answer your first question: It seems that names1 <- names(DT) also behaves similarly. I hadn't thought/known about this until now. The .Internal(inspect(.)) command is very useful here:

.Internal(inspect(names1))
# @7fc86a851480 16 STRSXP g0c7 [MARK,NAM(2)] (len=2, tl=100)
#   @7fc86a069f68 09 CHARSXP g1c1 [MARK,gp=0x61] [ASCII] [cached] "x"
#   @7fc86a0f96d8 09 CHARSXP g1c1 [MARK,gp=0x61] [ASCII] [cached] "y"

.Internal(inspect(names(DT)))
# @7fc86a851480 16 STRSXP g0c7 [MARK,NAM(2)] (len=2, tl=100)
#   @7fc86a069f68 09 CHARSXP g1c1 [MARK,gp=0x61] [ASCII] [cached] "x"
#   @7fc86a0f96d8 09 CHARSXP g1c1 [MARK,gp=0x61] [ASCII] [cached] "y"

Here, you see that they are pointing to the same memory location @7fc86a851480 . Even the truelength of names1 is 100 (which is by default allocated in data.table , check ?alloc.col for this).

truelength(names1)
# [1] 100

So basically, the assignment names1 <- names(dt) seems to happen by reference. That is, names1 is pointing to the same location as dt's column names pointer.

To answer your second question: The command c(.) seems to create a copy as there is no checking as to whether the contents result due to concatenation operation are different . That is, because c(.) operation can change the contents of the vector, it immediately results in a "copy" being made without checking if the contents are modified are not.