This is similar to a previous question, but the answers there don't satisfy my needs and my question is slightly different:
I currently use gzip compression for some very large files which contain sorted data. When the files are not compressed, binary search is a handy and efficient way to support seeking to a location in the sorted data.
But when the files are compressed, things get tricky. I recently found out about zlib's Z_FULL_FLUSH
option, which can be used during compression to insert "sync points" in the compressed output (inflateSync()
can then begin reading from various points in the file). This is OK, though files I already have would have to be recompressed to add this feature (and strangely gzip
doesn't have an option for this, but I'm willing to write my own compression program if I must).
It seems from one source that even Z_FULL_FLUSH
is not a perfect solution...not only is it not supported by all gzip archives, but the very idea of detecting sync points in archives may produce false positives (either by coincidence with the magic number for sync points, or due to the fact that Z_SYNC_FLUSH
also produces sync points but they are not usable for random access).
Is there a better solution? I'd like to avoid having auxiliary files for indexing if possible, and explicit, default support for quasi-random access would be helpful (even if it's large-grained--like being able to start reading at each 10 MB interval). Is there another compression format with better support for random reads than gzip?
Edit: As I mentioned, I wish to do binary search in the compressed data. I don't need to seek to a specific (uncompressed) position--only to seek with some coarse granularity within the compressed file. I just want support for something like "Decompress the data starting roughly 50% (25%, 12.5%, etc.) of the way into this compressed file."
ZIP. The most common and wide-spread archive format is, without a doubt, ZIP. ZIP files are very versatile.
The winner by pure compression is 7z, which isn't surprising to us. We've seen 7z come on the top of file compression benchmarks time and time again. If you want to compress something to use as little space as possible, you should definitely use 7z.
Archival programs are used often to back up data. You would use archives to backup a folder or a number of files into a single file and compress them as well. This allows you to save space and then store that individual file on a floppy or other removable media.
A compressed file is a collection of files and directories that are stored in one file and stored in a way that uses less disk space than all the individual files and directories combined. If disk space is a concern, compress rarely-used files, or place all such files in a single archive file and compress it. Note.
Take a look at dictzip. It is compatible with gzip and allows coarse random access.
An excerpt from its man page:
dictzip compresses files using the gzip(1) algorithm (LZ77) in a manner which is completely compatible with the gzip file format. An extension to the gzip file format (Extra Field, described in 2.3.1.1 of RFC 1952) allows extra data to be stored in the header of a compressed file. Programs like gzip and zcat will ignore this extra data. However, [dictzcat --start] will make use of this data to perform pseudo-random access on the file.
I have the package dictzip in Ubuntu. Or its source code is in a dictd-*.tar.gz. Its license is GPL. You are free to study it.
I improved dictzip to have no file size limit. My implementation is under MIT license.
I don't know of any compressed file format which would support random access to a specific location in the uncompressed data (well, except for multimedia formats), but you can brew your own.
For example, bzip2 compressed files are composed of independent compressed blocks of size <1MB uncompressed, which are delimited by sequences of magic bytes, so you could parse the bzip2 file, get the block boundaries and then just uncompress the right block. This would need some indexing to remember where do the blocks start.
Still, I think the best solution would be to split your file into chunks of your choice, and then compressing it with some archiver, like zip or rar, which support random access to individual files in the archive.
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