fmatch.Rd
fmatch
is a faster version of the built-in match
()
function. It is slightly faster than the built-in version because it
uses more specialized code, but in addition it retains the hash table
within the table object such that it can be re-used, dramatically reducing
the look-up time especially for large tables.
Although fmatch
can be used separately, in general it is also
safe to use: match <- fmatch
since it is a drop-in
replacement. Any cases not directly handled by fmatch
are passed
to match
with a warning.
fmatch.hash
is identical to fmatch
but it returns the table
object with the hash table attached instead of the result, so it can be
used to create a table object in cases where direct modification is
not possible.
%fin%
is a version of the built-in %in%
function
that uses fmatch
instead of match
().
fmatch(x, table, nomatch = NA_integer_, incomparables = NULL)
fmatch.hash(x, table, nomatch = NA_integer_, incomparables = NULL)
x %fin% table
See match
for the purpose and details of the
match
function. fmatch
is a drop-in replacement for
the match
function with the focus on
performance. incomparables
are not supported by fmatch
and will be passed down to match
.
The first match against a table results in a hash table to be computed
from the table. This table is then attached as the ".match.hash"
attribute of the table so that it can be re-used on subsequent calls
to fmatch
with the same table.
The hashing algorithm used is the same as the match
function in
R, but it is re-implemented in a slightly different way to improve its
performance at the cost of supporting only a subset of types (integer,
real and character). For any other types fmatch
falls back to
match
(with a warning).
fmatch
: A vector of the same length as x
- see
match
for details.
fmatch.hash
: table
, possibly coerced to match the type
of x
, with the hash table attached.
%fin%
: A logical vector the same length as x
- see
%in%
for details.
fmatch
modifies the table
by attaching an attribute to
it. It is expected that the values will not change unless that
attribute is dropped. Under normal circumstances this should not have
any effect from user's point of view, but there is a theoretical
chance of the cache being out of sync with the table in case the table
is modified directly (e.g. by some C code) without removing
attributes.
In cases where the table
object cannot be modified (or such
modification would not survive) fmatch.hash
can be used to build
the hash table and return table
object including the hash
table. In that case no lookup is done and x
is only used to
determine the type into which table
needs to be coerced.
Also fmatch
does not convert to a common encoding so strings
with different representation in two encodings don't match.
# some random speed comparison examples:
# first use integer matching
x = as.integer(rnorm(1e6) * 1000000)
s = 1:100
# the first call to fmatch is comparable to match
system.time(fmatch(s,x))
#> user system elapsed
#> 0.019 0.000 0.019
# but the subsequent calls take no time!
system.time(fmatch(s,x))
#> user system elapsed
#> 0.000 0.000 0.001
system.time(fmatch(-50:50,x))
#> user system elapsed
#> 0 0 0
system.time(fmatch(-5000:5000,x))
#> user system elapsed
#> 0 0 0
# here is the speed of match for comparison
system.time(base::match(s, x))
#> user system elapsed
#> 0.029 0.000 0.030
# the results should be identical
identical(base::match(s, x), fmatch(s, x))
#> [1] TRUE
# next, match a factor against the table
# this will require both x and the factor
# to be cast to strings
s = factor(c("1","1","2","foo","3",NA))
# because the casting will have to allocate a string
# cache in R, we run a dummy conversion to take
# that out of the equation
dummy = as.character(x)
# now we can run the speed tests
system.time(fmatch(s, x))
#> user system elapsed
#> 0.317 0.000 0.317
system.time(fmatch(s, x))
#> user system elapsed
#> 0 0 0
# the cache is still valid for string matches as well
system.time(fmatch(c("foo","bar","1","2"),x))
#> user system elapsed
#> 0 0 0
# now back to match
system.time(base::match(s, x))
#> user system elapsed
#> 0.382 0.000 0.382
identical(base::match(s, x), fmatch(s, x))
#> [1] TRUE
# finally, some reals to match
y = rnorm(1e6)
s = c(y[sample(length(y), 100)], 123.567, NA, NaN)
system.time(fmatch(s, y))
#> user system elapsed
#> 0.034 0.000 0.034
system.time(fmatch(s, y))
#> user system elapsed
#> 0 0 0
system.time(fmatch(s, y))
#> user system elapsed
#> 0 0 0
system.time(base::match(s, y))
#> user system elapsed
#> 0.039 0.000 0.038
identical(base::match(s, y), fmatch(s, y))
#> [1] TRUE
# this used to fail before 0.1-2 since nomatch was ignored
identical(base::match(4L, 1:3, nomatch=0), fmatch(4L, 1:3, nomatch=0))
#> [1] TRUE