In data.table parlance, all set* functions change their input
by reference. That is, no copy is made at all, other than temporary
working memory, which is as large as one column.. The only other data.table
operator that modifies input by reference is :=. Check out the
See Also section below for other set* function data.table
provides.
setkey() sorts a data.table and marks it as sorted (with an
attribute sorted). The sorted columns are the key. The key can be any
columns in any order. The columns are sorted in ascending order always. The table
is changed by reference and is therefore very memory efficient.
key() returns the data.table's key if it exists, and NULL
if none exist.
haskey() returns a logical TRUE/FALSE depending on whether
the data.table has a key (or not).
setkey(x, ..., verbose=getOption("datatable.verbose"), physical = TRUE)
setkeyv(x, cols, verbose=getOption("datatable.verbose"), physical = TRUE)
setindex(...)
setindexv(...)
key(x)
indices(x, vectors = FALSE)
haskey(x)
key(x) <- value # DEPRECATED, please use setkey or setkeyv instead.A data.table.
The columns to sort by. Do not quote the column names. If
… is missing (i.e. setkey(DT)), all the columns are used.
NULL removes the key.
A character vector (only) of column names.
In (deprecated) key<-, a character vector (only) of column
names.
Output status and information.
TRUE changes the order of the data in RAM. FALSE adds a secondary key a.k.a. index.
logical scalar default FALSE, when set to TRUE
then list of character vectors is returned, each vector refers to one index.
The input is modified by reference, and returned (invisibly) so it can be used
in compound statements; e.g., setkey(DT,a)[J("foo")]. If you require a
copy, take a copy first (using DT2=copy(DT)). copy() may also
sometimes be useful before := is used to subassign to a column by
reference. See ?copy.
setkey reorders (or sorts) the rows of a data.table by the columns
provided. In versions 1.9+, for integer columns, a modified version
of base's counting sort is implemented, which allows negative values as well. It
is extremely fast, but is limited by the range of integer values being <= 1e5. If
that fails, it falls back to a (fast) 4-pass radix sort for integers, implemented
based on Pierre Terdiman's and Michael Herf's code (see links below). Similarly,
a very fast 6-pass radix order for columns of type double is also implemented.
This gives a speed-up of about 5-8x compared to 1.8.10 on setkey
and all internal order/sort operations. Fast radix sorting is also
implemented for character and bit64::integer64 types.
The sort is stable; i.e., the order of ties (if any) is preserved, in both
versions - <=1.8.10 and >= 1.9.0.
In data.table versions <= 1.8.10, for columns of type integer,
the sort is attempted with the very fast "radix" method in
sort.list. If that fails, the sort reverts to the default
method in order. For character vectors, data.table
takes advantage of R's internal global string cache and implements a very efficient
order, also exported as chorder.
In v1.7.8, the key<- syntax was deprecated. The <- method copies
the whole table and we know of no way to avoid that copy without a change in
R itself. Please use the set* functions instead, which make no copy at
all. setkey accepts unquoted column names for convenience, whilst
setkeyv accepts one vector of column names.
The problem (for data.table) with the copy by key<- (other than
being slower) is that R doesn't maintain the over allocated truelength, but it
looks as though it has. Adding a column by reference using := after a
key<- was therefore a memory overwrite and eventually a segfault; the
over allocated memory wasn't really there after key<-'s copy. data.tables
now have an attribute .internal.selfref to catch and warn about such copies.
This attribute has been implemented in a way that is friendly with
identical() and object.size().
For the same reason, please use the other set* functions which modify
objects by reference, rather than using the <- operator which results
in copying the entire object.
It isn't good programming practice, in general, to use column numbers rather
than names. This is why setkey and setkeyv only accept column names.
If you use column numbers then bugs (possibly silent) can more easily creep into
your code as time progresses if changes are made elsewhere in your code; e.g., if
you add, remove or reorder columns in a few months time, a setkey by column
number will then refer to a different column, possibly returning incorrect results
with no warning. (A similar concept exists in SQL, where "select * from ..."
is considered poor programming style when a robust, maintainable system is
required.) If you really wish to use column numbers, it's possible but
deliberately a little harder; e.g., setkeyv(DT,colnames(DT)[1:2]).
http://en.wikipedia.org/wiki/Radix_sort http://en.wikipedia.org/wiki/Counting_sort http://cran.at.r-project.org/web/packages/bit/index.html http://stereopsis.com/radix.html
data.table, tables, J,
sort.list, copy, setDT,
setDF, set :=, setorder,
setcolorder, setattr, setnames,
chorder, setNumericRounding
# NOT RUN {
# Type 'example(setkey)' to run these at prompt and browse output
DT = data.table(A=5:1,B=letters[5:1])
DT # before
setkey(DT,B) # re-orders table and marks it sorted.
DT # after
tables() # KEY column reports the key'd columns
key(DT)
keycols = c("A","B")
setkeyv(DT,keycols) # rather than key(DT)<-keycols (which copies entire table)
DT = data.table(A=5:1,B=letters[5:1])
DT2 = DT # does not copy
setkey(DT2,B) # does not copy-on-write to DT2
identical(DT,DT2) # TRUE. DT and DT2 are two names for the same keyed table
DT = data.table(A=5:1,B=letters[5:1])
DT2 = copy(DT) # explicit copy() needed to copy a data.table
setkey(DT2,B) # now just changes DT2
identical(DT,DT2) # FALSE. DT and DT2 are now different tables
DT = data.table(A=5:1,B=letters[5:1])
setindex(DT) # set indices
setindex(DT, A)
setindex(DT, B)
indices(DT) # get indices single vector
indices(DT, vectors = TRUE) # get indices list
# }
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