Sorting: order from ff vectors

Returns order with regard to one or more ff vectors

Usage

fforder(...
, index = NULL
, use.index = NULL
, aux = NULL
, auxindex = NULL
, has.na = TRUE
, na.last = TRUE
, decreasing = FALSE
, BATCHBYTES = getOption("ffmaxbytes")
, VERBOSE = FALSE
)

Arguments

...

one of more ff vectors which define the order

index

an optional ff integer vector used to store the order output

use.index

A boolean flag telling fforder whether to use the positions in 'index' as input. If you do this, it is your responsibility to assure legal positions - otherwise you risk a crash.

aux

An optional named list of ff vectors that can be used for temporary copying – the names of the list identify the vmodes for which the respective ff vector is suitable.

auxindex

An optional ff intger vector for temporary storage of integer positions.

has.na

boolean scalar telling fforder whether the vector might contain NAs. Note that you risk a crash if there are unexpected NAs with has.na=FALSE

na.last

boolean scalar telling fforder whether to order NAs last or first. Note that 'boolean' means that there is no third option NA as in order

decreasing

boolean scalar telling fforder whether to order increasing or decreasing

BATCHBYTES

maximum number of RAM bytes fforder should try not to exceed

VERBOSE

cat some info about the ordering

Details

fforder tries to order the vector in-RAM, if not possible it uses (a yet simple) out-of-memory algorithm. Like ramorder the in-RAM ordering method is choosen depending on context information.

Value

An ff vector with the positions that ore required to sort the input as specified – with an attribute na.count with as many values as columns in ...

Author

Jens Oehlschlägel

See also

ramorder, ffsort, ffdforder, ffindexget

Examples

   x <- ff(sample(1e5, 1e6, TRUE))
   y <- ff(sample(1e5, 1e6, TRUE))
   d <- ffdf(x, y)

   i <- fforder(y)
   y[i]
#> ff (open) integer length=1000000 (1000000)
#>       [1]       [2]       [3]       [4]       [5]       [6]       [7]       [8] 
#>         1         1         1         1         1         1         1         1 
#>            [999993]  [999994]  [999995]  [999996]  [999997]  [999998]  [999999] 
#>         :    100000    100000    100000    100000    100000    100000    100000 
#> [1000000] 
#>    100000 
   i <- fforder(x, index=i)
   x[i]
#> ff (open) integer length=1000000 (1000000)
#>       [1]       [2]       [3]       [4]       [5]       [6]       [7]       [8] 
#>         1         1         1         1         1         1         1         1 
#>            [999993]  [999994]  [999995]  [999996]  [999997]  [999998]  [999999] 
#>         :    100000    100000    100000    100000    100000    100000    100000 
#> [1000000] 
#>    100000 
   d[i,]
#> ffdf (all open) dim=c(1000000,2), dimorder=c(1,2) row.names=NULL
#> ffdf virtual mapping
#>   PhysicalName VirtualVmode PhysicalVmode  AsIs VirtualIsMatrix
#> x            x      integer       integer FALSE           FALSE
#> y            y      integer       integer FALSE           FALSE
#>   PhysicalIsMatrix PhysicalElementNo PhysicalFirstCol PhysicalLastCol
#> x            FALSE                 1                1               1
#> y            FALSE                 2                1               1
#>   PhysicalIsOpen
#> x           TRUE
#> y           TRUE
#> ffdf data
#>              x      y
#> 1            1   2209
#> 2            1  15556
#> 3            1  38650
#> 4            1  42592
#> 5            1  47528
#> 6            1  58202
#> 7            1  67100
#> 8            1  69662
#> :            :      :
#> 999993  100000  51225
#> 999994  100000  54259
#> 999995  100000  58982
#> 999996  100000  64533
#> 999997  100000  72528
#> 999998  100000  75553
#> 999999  100000  88491
#> 1000000 100000  89196

   i <- fforder(x, y)
   d[i,]
#> ffdf (all open) dim=c(1000000,2), dimorder=c(1,2) row.names=NULL
#> ffdf virtual mapping
#>   PhysicalName VirtualVmode PhysicalVmode  AsIs VirtualIsMatrix
#> x            x      integer       integer FALSE           FALSE
#> y            y      integer       integer FALSE           FALSE
#>   PhysicalIsMatrix PhysicalElementNo PhysicalFirstCol PhysicalLastCol
#> x            FALSE                 1                1               1
#> y            FALSE                 2                1               1
#>   PhysicalIsOpen
#> x           TRUE
#> y           TRUE
#> ffdf data
#>              x      y
#> 1            1   2209
#> 2            1  15556
#> 3            1  38650
#> 4            1  42592
#> 5            1  47528
#> 6            1  58202
#> 7            1  67100
#> 8            1  69662
#> :            :      :
#> 999993  100000  51225
#> 999994  100000  54259
#> 999995  100000  58982
#> 999996  100000  64533
#> 999997  100000  72528
#> 999998  100000  75553
#> 999999  100000  88491
#> 1000000 100000  89196

   i <- ffdforder(d)
   d[i,]
#> ffdf (all open) dim=c(1000000,2), dimorder=c(1,2) row.names=NULL
#> ffdf virtual mapping
#>   PhysicalName VirtualVmode PhysicalVmode  AsIs VirtualIsMatrix
#> x            x      integer       integer FALSE           FALSE
#> y            y      integer       integer FALSE           FALSE
#>   PhysicalIsMatrix PhysicalElementNo PhysicalFirstCol PhysicalLastCol
#> x            FALSE                 1                1               1
#> y            FALSE                 2                1               1
#>   PhysicalIsOpen
#> x           TRUE
#> y           TRUE
#> ffdf data
#>              x      y
#> 1            1   2209
#> 2            1  15556
#> 3            1  38650
#> 4            1  42592
#> 5            1  47528
#> 6            1  58202
#> 7            1  67100
#> 8            1  69662
#> :            :      :
#> 999993  100000  51225
#> 999994  100000  54259
#> 999995  100000  58982
#> 999996  100000  64533
#> 999997  100000  72528
#> 999998  100000  75553
#> 999999  100000  88491
#> 1000000 100000  89196

   rm(x, y, d, i)
   gc()
#>           used (Mb) gc trigger  (Mb) max used  (Mb)
#> Ncells 1246647 66.6    2239654 119.7  2239654 119.7
#> Vcells 2292819 17.5    8388608  64.0  8387257  64.0