You perhaps know that redundancy of DNA sequences doesn't totally imply a 100% conservation of the sequences. Even sequences that are not 100% identical maybe considered redundant and the few differences between them may not result in any functional impact. So if sequences code for a protein, the selection is such that mutations may still preserve the encoded protein due to the degenracy of the genetic code. That means, you're probably filtering 100% identical sequences but there could be, biologically speaking, other redundant sequences you did not look at.

My answer will be similar to what choroba and Athanasius have suggested, but with a slight modification. The modification is, I list every ID for which sequences are identical and to ease my life a bit I am using BioPerl. Then you can easily just include into your analysis one ID to represent that cluster of sequences

use strict;
use warnings;
use Data::Dumper;
use Bio::SeqIO;

my %hash; #updated.
#Reading sequence files in Fasta format
my $in=Bio::SeqIO->new(
    -file=> "sequences.fa",
    -format=>"fasta",
    );
#getting the IDs of the identical sequences into a data structure
while(my $seq=$in->next_seq()){
    #print $seq->id,$/;
    push @{$hash{$seq->seq}}, $seq->id;
    }

#print each group of identical IDs into a separate line
foreach my $key(keys %hash){
    if(scalar @{$hash{$key}}>=1){
        print scalar @{$hash{$key}},"\t";
        print "@{$hash{$key}}","\n";
        }
    }
[download]

If your dataset is really really huge then you may want to think of clustering based on sequence-similarity as opposed to sequence-identity since you won't lose so much of the biological signals if you define a sensible similarity threshold to cluster around. There are routinely used tools that you can explore towards that purpose like cd-hits-est and uclust for example.

UPDATE: 09/09/2015: Predeclared the hash in response to the suggestion provided by Not_a_Number. Since I wrote the code out of my head without testing it I missed the variable declaration.

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