Converting a Document Term Matrix into a Matrix with lots of data causes overflow

问题

Let's do some Text Mining

Here I stand with a document term matrix (from the tm Package)

dtm <- TermDocumentMatrix(
     myCorpus,
     control = list(
         weight = weightTfIdf,
         tolower=TRUE,
         removeNumbers = TRUE,
         minWordLength = 2,
         removePunctuation = TRUE,
         stopwords=stopwords("german")
      ))

When I do a

typeof(dtm)

I see that it is a "list" and the structure looks like

Docs
Terms        1 2 ...
  lorem      0 0 ...
  ipsum      0 0 ...
  ...        .......

So I try a

wordMatrix = as.data.frame( t(as.matrix(  dtm )) )

That works for 1000 Documents.

But when I try to use 40000 it doesn't anymore.

I get this error:

Fehler in vector(typeof(x$v), nr * nc) : Vektorgröße kann nicht NA sein
Zusätzlich: Warnmeldung:
In nr * nc : NAs durch Ganzzahlüberlauf erzeugt

Error in vector ... : Vector can't be NA Additional: In nr * nc NAs created by integer overflow

So I looked at as.matrix and it turns out that somehow the function converts it to a vector with as.vector and than to a matrix. The convertion to a vector works but not the one from the vector to the matrix dosen't.

Do you have any suggestions what could be the problem?

Thanks, The Captain

回答1:

Integer overflow tells you exactly what the problem is : with 40000 documents, you have too much data. It is in the conversion to a matrix that the problem begins btw, which can be seen if you look at the code of the underlying function :

class(dtm)
[1] "TermDocumentMatrix"    "simple_triplet_matrix"

getAnywhere(as.matrix.simple_triplet_matrix)

A single object matching ‘as.matrix.simple_triplet_matrix’ was found
...
function (x, ...) 
{
    nr <- x$nrow
    nc <- x$ncol
    y <- matrix(vector(typeof(x$v), nr * nc), nr, nc)
   ...
}

This is the line referenced by the error message. What's going on, can be easily simulated by :

as.integer(40000 * 60000) # 40000 documents is 40000 rows in the resulting frame
[1] NA
Warning message:
NAs introduced by coercion

The function vector() takes an argument with the length, in this case nr*nc If this is larger than appx. 2e9 ( .Machine$integer.max ), it will be replaced by NA. This NA is not valid as an argument for vector().

Bottomline : You're running into the limits of R. As for now, working in 64bit won't help you. You'll have to resort to different methods. One possibility would be to continue working with the list you have (dtm is a list), selecting the data you need using list manipulation and go from there.

PS : I made a dtm object by

require(tm)
data("crude")
dtm <- TermDocumentMatrix(crude,
                          control = list(weighting = weightTfIdf,
                                         stopwords = TRUE))

回答2:

Here is a very very simple solution I discovered recently

DTM=t(TDM)#taking the transpose of Term-Document Matrix though not necessary but I prefer DTM over TDM
M=as.big.matrix(x=as.matrix(DTM))#convert the DTM into a bigmemory object using the bigmemory package 
M=as.matrix(M)#convert the bigmemory object again to a regular matrix
M=t(M)#take the transpose again to get TDM

Please note that taking transpose of TDM to get DTM is absolutely optional, it's my personal preference to play with matrices this way

P.S.Could not answer the question 4 years back as I was just a fresh entry in my college

回答3:

Based on Joris Meys answer, I've found the solution. "vector()" documentation regarding "length" argument

... For a long vector, i.e., length > .Machine$integer.max, it has to be of type "double"...

So we can make a tiny fix of the as.matrix():

as.big.matrix <- function(x) {
  nr <- x$nrow
  nc <- x$ncol
  # nr and nc are integers. 1 is double. Double * integer -> double
  y <- matrix(vector(typeof(x$v), 1 * nr * nc), nr, nc)
  y[cbind(x$i, x$j)] <- x$v
  dimnames(y) <- x$dimnames
  y
}

来源：https://stackoverflow.com/questions/6860715/converting-a-document-term-matrix-into-a-matrix-with-lots-of-data-causes-overflo

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memory-management

text

matrix

mining