It seems to me the fastest way to do a row/col subset of a data.table
is to use the join and nomatch
option.
Is this correct?
DT = data.table(rep(1:100, 100000), rep(1:10, 1000000))
setkey(DT, V1, V2)
system.time(DT[J(22,2), nomatch=0L])
# user system elapsed
# 0.00 0.00 0.01
system.time(subset(DT, (V1==22) & (V2==2)))
# user system elapsed
# 0.45 0.21 0.67
identical(DT[J(22,2), nomatch=0L],subset(DT, (V1==22) & (V2==2)))
# [1] TRUE
I also have one problem with the fast join based on binary search: I cannot find a way to select all items in one dimension.
Say if I want to subsequently do:
DT[J(22,2), nomatch=0] # subset on TWO dimensions
DT[J(22,), nomatch=0] # subset on ONE dimension only
# Error in list(22, ) : argument 2 is empty
without having to re-set the key to only one dimension (because I am in a loop and I don't want to rest the keys every time).
data.table
? Using the binary search based subset feature is the fastest. Note that the subset requires the option nomatch = 0L
so as to return only the matching results.
If you've two keys set on DT
and you want to subset by the first key , then you can just provide the first value in J(.)
, no need to provide anything for the 2nd key. That is:
# will return all columns where the first key column matches 22
DT[J(22), nomatch=0L]
If instead, you would like to subset by the second key , then you'll have to, as of now, provide all the unique values for the first key. That is:
# will return all columns where 2nd key column matches 2
DT[J(unique(V1), 2), nomatch=0L]
This is also shown in this SO post . Although I'd prefer that DT[J(, 2)]
to work for this case, as that seems rather intuitive.
There's also a pending feature request, FR #1007 for implementing secondary keys, which when done would take care of this.
Here is a better example:
DT = data.table(c(1,2,3,4,5), c(2,3,2,3,2))
DT
# V1 V2
# 1: 1 2
# 2: 2 3
# 3: 3 2
# 4: 4 3
# 5: 5 2
setkey(DT,V1,V2)
DT[J(unique(V1),2)]
# V1 V2
# 1: 1 2
# 2: 2 2
# 3: 3 2
# 4: 4 2
# 5: 5 2
DT[J(unique(V1),2), nomatch=0L]
# V1 V2
# 1: 1 2
# 2: 3 2
# 3: 5 2
DT[J(3), nomatch=0L]
# V1 V2
# 1: 3 2
In summary:
# key(DT) = c("V1", "V2")
# data.frame | data.table equivalent
# =====================================================================
# subset(DF, (V1 == 3) & (V2 == 2)) | DT[J(3,2), nomatch=0L]
# subset(DF, (V1 == 3)) | DT[J(3), nomatch=0L]
# subset(DF, (V2 == 2)) | DT[J(unique(V1), 2), nomatch=0L]
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