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This document contains notes about the design for groupcompress, replacement
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VersionedFiles store for use in pack based repositories. The goal is to provide
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fast, history bounded text extraction.
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The goal: Much tighter compression, maintained automatically. Considerations
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to weigh: The minimum IO to reconstruct a text with no other repository
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involved; The number of index lookups to plan a reconstruction. The minimum
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IO to reconstruct a text with another repositories assistance (affects
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network IO for fetch, which impacts incremental pulls and shallow branch
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Each delta is individually compressed against another text, and then entropy
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compressed. We index the pointers between these deltas.
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Solo reconstruction: Plan a readv via the index, read the deltas in forward
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IO, apply each delta. Total IO: sum(deltas) + deltacount*index overhead.
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Fetch/stacked reconstruction: Plan a readv via the index, using local basis
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texts where possible. Then readv locally and remote and apply deltas. Total IO
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as for solo reconstruction.
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Reasonable sizes 'amount read' from remote machines to reconstruct an arbitrary
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text: Reading 5MB for a 100K plain text is not a good trade off. Reading (say)
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500K is probably acceptable. Reading ~100K is ideal. However, its likely that
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some texts (e.g NEWS versions) can be stored for nearly-no space at all if we
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are willing to have unbounded IO. Profiling to set a good heuristic will be
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important. Also allowing users to choose to optimise for a server environment
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may make sense: paying more local IO for less compact storage may be useful.
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Index scatter gather IO. Doing hundreds or thousands of index lookups is very
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expensive, and doing that per file just adds insult to injury.
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Partioned compression amongst files.
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Scatter gather IO when reconstructing texts: linear forward IO is better.
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Merges combine texts from multiple versions to create a new version. Deltas
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add new text to existing files and remove some text from the same. Getting
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high compression means reading some base and then a chain of deltas (could
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be a tree) to gain access to the thing that the final delta was made against,
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and that delta. Rather than composing all these deltas, we can just just
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perform the final diff against the base text and the serialised invidual
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deltas. If the diff algorithm can reuse out of order lines from previous
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texts (e.g. storing AB -> BA as pointers rather than delete and add, then
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the presence of any previously stored line in a single chain can be reused.
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One such diff algorithm is xdelta, another reasonable one to consider is
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plain old zlib or lzma. We could also use bzip2. One advantage of using
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a generic compression engine is less python code. One advantage of
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preprocessing line based deltas is that we reduce the window size for the
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text repeated within lines, and that will help compression by a simple
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entropy compressor as a post processor.
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lzma appears fantastic at compression - 420MB of NEWS files down to 200KB.
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so window size appears to be a key determiner for efficiency.
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Very big objects - no delta. I plan to kick this in at 5MB initially, but
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once the codebase is up and running, we can tweak this to
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Very small objects - no delta? If they are combined with a larger zlib object
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why not? (Answer: because zlib's window is really small)
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Other objects - group by fileid (gives related texts a chance, though using a
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file name would be better long term as e.g. COPYING and COPYING from different
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projects could combine). Then by reverse topological graph(as this places more
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recent texts at the front of a chain). Alternatively, group by size, though
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that should not matter with a large enough window.
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Finally, delta the texts against the current output of the compressor. This is
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essentially a somewhat typed form of sliding window dictionary compression. An
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alternative implementation would be to just use zlib, or lzma, or bzip2
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Unfortunately, just using entropy compression forces a lot of data to be output
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by the decompressor - e.g. 420MB in the NEWS sample corpus. When we only want
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a single 55K text thats inefficient. (An initial test took several seconds with
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The fastest to implement approach is probably just 'diff output to date and add
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to entropy compressor'. This should produce reasonable results. As delta
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chain length is not a concern (only one delta to apply ever), we can simply
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cap the chain when the total read size becomes unreasonable. Given older texts
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are smaller we probably want some weighted factor of plaintext size.
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In this approach, a single entropy compressed region is read as a unit, giving
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the lower bound for IO (and how much to read is an open question - what byte
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offset of compressed data is sufficient to ensue that the delta-stream contents
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we need are reconstructable. Flushing, while possible, degrades compression(and
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adds overhead - we'd be paying 4 bytes per record guaranteed). Again - tests
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A nice possibility is to output mpdiff compatible records, which might enable
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some code reuse. This is more work than just diff (current_out, new_text), so
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can wait for the concept to be proven.
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Implementation Strategy
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+++++++++++++++++++++++
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Bring up a VersionedFiles object that implements this, then stuff it into a
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repository format. zlib as a starting compressor, though bzip2 will probably
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removed
doc/developers/groupcompress-design.txt
