Create key on a data.table
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
number of columns. The columns are always sorted in ascending order. The table
is changed by reference and setkey is very memory efficient.
There are three reasons setkey is desirable: i) binary search and joins are faster
when they detect they can use an existing key, ii) grouping by a leading subset of the key
columns is faster because the groups are already gathered contiguously in RAM, iii)
simpler shorter syntax; e.g. DT["id",] finds the group "id" in the first column
of DT's key using binary search. It may be helpful to think of a key as
super-charged rownames: multi-column and multi-type rownames.
In data.table parlance, all set* functions change their input
by reference. That is, no copy is made at all other than for 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* functions data.table
provides.
setindex creates an index for the provided columns. This index is simply an
ordering vector of the dataset's rows according to the provided columns. This order vector
is stored as an attribute of the data.table and the dataset retains the original order
of rows in memory. See the vignette("datatable-secondary-indices-and-auto-indexing") for more details.
key returns the data.table's key if it exists; NULL if none exists.
haskey returns TRUE/FALSE if the data.table has a key.
setkey(x, ..., verbose=getOption("datatable.verbose"), physical = TRUE)
setkeyv(x, cols, verbose=getOption("datatable.verbose"), physical = TRUE)
setindex(...)
setindexv(x, cols, verbose=getOption("datatable.verbose"))
key(x)
indices(x, vectors = FALSE)
haskey(x)x |
A |
... |
The columns to sort by. Do not quote the column names. If |
cols |
A character vector of column names. For |
verbose |
Output status and information. |
physical |
|
vectors |
|
setkey reorders (i.e. sorts) the rows of a data.table by the columns
provided. The sort method used has developed over the years and we have contributed
to base R too; see sort. Generally speaking we avoid any type
of comparison sort (other than insert sort for very small input) preferring instead
counting sort and forwards radix. We also avoid hash tables.
Note that setkey always uses "C-locale"; see the Details in the help for setorder for more on why.
The sort is stable; i.e., the order of ties (if any) is preserved.
For character vectors, data.table takes advantage of R's internal global string cache, also exported as chorder.
The input is modified by reference and returned (invisibly) so it can be used
in compound statements; e.g., setkey(DT,a)[.("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.
In general, it's good practice to use column names rather than numbers. 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 is possible but
deliberately a little harder; e.g., setkeyv(DT,names(DT)[1:2]).
If you wanted to use grep to select key columns according to
a pattern, note that you can just set value = TRUE to return a character vector instead of the default integer indices.
data.table, tables, J,
sort.list, copy, setDT,
setDF, set :=, setorder,
setcolorder, setattr, setnames,
chorder, setNumericRounding
# Type 'example(setkey)' to run these at the 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)
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 listPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.