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The ffapply functions support convenient batched processing of ff objects
such that each single batch or chunk will not exhaust RAM
and such that batchs have sizes as similar as possible, see bbatch.
Differing from R's standard apply which applies a FUNction,
the ffapply functions do apply an EXPRession and provide two indices FROM="i1" and TO="i2",
which mark beginning and end of the batch and can be used in the applied expression.
Note that the ffapply functions change the two indices in their parent frame, to avoid conflicts you can use different names through FROM="i1" and TO="i2".
For support of creating return values see details.
ffvecapply(EXPR, X = NULL, N = NULL, VMODE = NULL, VBYTES = NULL, RETURN = FALSE
, CFUN = NULL, USE.NAMES = TRUE, FF_RETURN = TRUE, BREAK = ".break"
, FROM = "i1", TO = "i2"
, BATCHSIZE = .Machine$integer.max, BATCHBYTES = getOption("ffbatchbytes")
, VERBOSE = FALSE)
ffrowapply(EXPR, X = NULL, N = NULL, NCOL = NULL, VMODE = NULL, VBYTES = NULL
, RETURN = FALSE, RETCOL = NCOL, CFUN = NULL, USE.NAMES = TRUE, FF_RETURN = TRUE
, FROM = "i1", TO = "i2"
, BATCHSIZE = .Machine$integer.max, BATCHBYTES = getOption("ffbatchbytes")
, VERBOSE = FALSE)
ffcolapply(EXPR, X = NULL, N = NULL, NROW = NULL, VMODE = NULL, VBYTES = NULL
, RETURN = FALSE, RETROW = NROW, CFUN = NULL, USE.NAMES = TRUE, FF_RETURN = TRUE
, FROM = "i1", TO = "i2"
, BATCHSIZE = .Machine$integer.max, BATCHBYTES = getOption("ffbatchbytes")
, VERBOSE = FALSE)
ffapply(EXPR = NULL, AFUN = NULL, MARGIN = NULL, X = NULL, N = NULL, DIM = NULL
, VMODE = NULL, VBYTES = NULL, RETURN = FALSE, CFUN = NULL, USE.NAMES = TRUE
, FF_RETURN = TRUE, IDIM = "idim"
, FROM = "i1", TO = "i2", BREAK = ".break"
, BATCHSIZE = .Machine$integer.max, BATCHBYTES = getOption("ffbatchbytes")
, VERBOSE = FALSE)see details
the expression to be applied
ffapply only: alternatively to EXPR the name of a function to be applied, automatically converted to EXPR
ffapply only: the margins along which to loop in ffapply
an ff object from which several parameters can be derived, if they are not given directly: N, NCOL, NROW, DIM, VMODE, VBYTES, FF_RETURN
the total number of elements in the loop, e.g. number of elements in ffvecapply or number of rows in ffrowapply
ffrowapply only: the number of columns needed to calculate batch sizes
ffcolapply only: the number of rows needed to calculate batch sizes
ffapply only: the dimension of the array needed to calculate batch sizes
the vmode needed to prepare the RETURN object and to derive VBYTES if they are not given directly
the bytes per cell -- see .rambytes -- to calculate the RAM requirements per cell
the max number of bytes per batch, default getOption("ffbatchbytes")
an additional restriction on the number of loop elements, default=.Machine$integer.max
the name of the index that marks the beginning of the batch, default 'i1', change if needed to avoid naming-conflicts in the calling frame
the name of the index that marks the end of the batch, default 'i2', change if needed to avoid naming-conflicts in the calling frame
ffapply only: the name of an R variable used for loop-switching, change if needed to avoid naming-conflicts in the calling frame
ffapply only: the name of an R object in the calling frame that triggers break out of the batch loop, if 1) it exists 2) is.logical and 3) is TRUE
TRUE to prepare a return value (default FALSE)
name of a collapsing function, see CFUN
NULL gives return vector[1:N], RETCOL gives return matrix[1:N, 1:RETCOL]
NULL gives return vector[1:N], RETROW gives return matrix[1:RETROW, 1:N]
FALSE to return a ram object, TRUE to return an ff object, or an ff object that is ffsuitable to absorb the return data
FALSE to suppress attaching names or dimnames to the result
TRUE to verbose the batches
Jens Oehlschlägel
ffvecapply is the simplest ffapply method for ff_vectors. ffrowapply and ffcolapply is for ff_matrix,
and ffapply is the most general method for ff_arrays and ff_vectors.
There are many ways to change the return value of the ffapply functions.
In its simplest usage -- batched looping over an expression -- they don't return anything, see invisible.
If you switch RETURN=TRUE in ffvecapply then it is assumed that all looped expressions together return one vector of length N,
and via parameter FF_RETURN, you can decide whether this vector is in ram or is an ff object (or even which ff object to use).
ffrowapply and ffcolapply additionally have parameter RETCOL resp. RETROW which defaults to returning a matrix of the original size;
in order to just return a vector of length N set this to NULL, or specify a number of columns/rows for the return matrix.
It is assumed that the expression will return appropriate pieces for this return structure (see examples).
If you specify RETURN=TRUE and a collapsing function name CFUN, then it is assumed that the batched expressions return aggregated information,
which is first collected in a list, and finally the collapsing function is called on this list: do.call(CFUN, list). If you want to return the unmodified list,
you have to specify CFUN="list" for obvious reasons.
ffapply allows usages not completly unlike apply: you can specify the name of a function AFUN to be applied over MARGIN.
However note that you must specify RETURN=TRUE in order to get a return value.
Also note that currently ffapply assumes that your expression returns exactly one value per cell in DIM[MARGINS].
If you want to return something more complicated, you MUST specify a CFUN="list" and your return value will be a list with dim attribute DIM[MARGINS].
This means that for a function AFUN returning a scalar, ffapply behaves very similar to apply, see examples.
Note also that ffapply might create a object named '.ffapply.dimexhausted' in its parent frame,
and it uses a variable in the parent frame for loop-switching between dimensions, the default name 'idim' can be changed using the IDIM parameter.
Finally you can break out of the implied loops by assigning TRUE to a variable with the name in BREAK.
apply, expression, bbatch, repfromto, ffsuitable
message("ffvecapply examples")
x <- ff(vmode="integer", length=100)
message("loop evaluate expression without returning anything")
ffvecapply(x[i1:i2] <- i1:i2, X=x, VERBOSE=TRUE)
ffvecapply(x[i1:i2] <- i1:i2, X=x, BATCHSIZE=20, VERBOSE=TRUE)
ffvecapply(x[i1:i2] <- i1:i2, X=x, BATCHSIZE=19, VERBOSE=TRUE)
message("lets return the combined expressions as a new ff object")
ffvecapply(i1:i2, N=length(x), VMODE="integer", RETURN=TRUE, BATCHSIZE=20)
message("lets return the combined expressions as a new ram object")
ffvecapply(i1:i2, N=length(x), VMODE="integer", RETURN=TRUE, FF_RETURN=FALSE, BATCHSIZE=20)
message("lets return the combined expressions in existing ff object x")
x[] <- 0L
ffvecapply(i1:i2, N=length(x), VMODE="integer", RETURN=TRUE, FF_RETURN=x, BATCHSIZE=20)
x
message("aggregate and collapse")
ffvecapply(summary(x[i1:i2]), X=x, RETURN=TRUE, CFUN="list", BATCHSIZE=20)
ffvecapply(summary(x[i1:i2]), X=x, RETURN=TRUE, CFUN="crbind", BATCHSIZE=20)
ffvecapply(summary(x[i1:i2]), X=x, RETURN=TRUE, CFUN="cmean", BATCHSIZE=20)
message("how to do colSums with ffrowapply")
x <- ff(1:1000, vmode="integer", dim=c(100, 10))
ffrowapply(colSums(x[i1:i2,,drop=FALSE]), X=x, RETURN=TRUE, CFUN="list", BATCHSIZE=20)
ffrowapply(colSums(x[i1:i2,,drop=FALSE]), X=x, RETURN=TRUE, CFUN="crbind", BATCHSIZE=20)
ffrowapply(colSums(x[i1:i2,,drop=FALSE]), X=x, RETURN=TRUE, CFUN="csum", BATCHSIZE=20)
message("further ffrowapply examples")
x <- ff(1:1000, vmode="integer", dim=c(100, 10))
message("loop evaluate expression without returning anything")
ffrowapply(x[i1:i2, ] <- i1:i2, X=x, BATCHSIZE=20)
message("lets return the combined expressions as a new ff object (x unchanged)")
ffrowapply(2*x[i1:i2, ], X=x, RETURN=TRUE, BATCHSIZE=20)
message("lets return a single row aggregate")
ffrowapply(t(apply(x[i1:i2,,drop=FALSE], 1, mean)), X=x, RETURN=TRUE, RETCOL=NULL, BATCHSIZE=20)
message("lets return a 6 column aggregates")
y <- ffrowapply( t(apply(x[i1:i2,,drop=FALSE], 1, summary)), X=x
, RETURN=TRUE, RETCOL=length(summary(0)), BATCHSIZE=20)
colnames(y) <- names(summary(0))
y
message("determine column minima if a complete column does not fit into RAM")
ffrowapply(apply(x[i1:i2,], 2, min), X=x, RETURN=TRUE, CFUN="pmin", BATCHSIZE=20)
message("ffapply examples")
x <- ff(1:720, dim=c(8,9,10))
dimnames(x) <- dummy.dimnames(x)
message("apply function with scalar return value")
apply(X=x[], MARGIN=3:2, FUN=sum)
apply(X=x[], MARGIN=2:3, FUN=sum)
ffapply(X=x, MARGIN=3:2, AFUN="sum", RETURN=TRUE, BATCHSIZE=8)
message("this is what CFUN is based on")
ffapply(X=x, MARGIN=2:3, AFUN="sum", RETURN=TRUE, CFUN="list", BATCHSIZE=8)
message("apply functions with vector or array return value currently have limited support")
apply(X=x[], MARGIN=3:2, FUN=summary)
message("you must use CFUN, the rest is up to you")
y <- ffapply(X=x, MARGIN=3:2, AFUN="summary", RETURN=TRUE, CFUN="list", BATCHSIZE=8)
y
y[[1]]
rm(x); gc()
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