Age | Commit message (Collapse) | Author |
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Specifically all entries in the Conflicts header are saved in the
conflict table, all entries in the Provides header are saved in the
provide table (to cover conflicts with virtual packages) and packages
using dpkg-divert in preinst get a magic "_dpkg-divert" entry in their
conflict table. With this metadata it should be possible to compute
undeclared file conflicts.
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Reported-By: Stefan Kaltenbrunner
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When comparing two packages, objects would be considered duplicates
without considering whether the respective hash functions are comparable
by checking their equivalence classes. The current set of hash functions
does not expose this bug.
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Hash functions are partitioned into equivalence classes. We are
generally only interested in sharing among hash functions with the same
equivalence class, but the algorithm would compute any sharing. While
the current layout never produces the same hashes for functions in
difference equivalence classes (for different output length), that may
change in future.
Also allow hash functions, that belong to no equivalence class at all
(eqclass = NULL) as a means to add additional metadata to content
without computing any sharing for it.
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Otherwise the gzip hash cannot tell the empty stream and the
compressed empty stream apart.
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Otherwise all files smaller than 10 bytes are successfully hashed to the
hash of the empty input when using the GzipDecompressor.
Reported-By: Olly Betts
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On the main instance opening cursors equals initiating a connection.
Unfortunately sqlite3.Connection.close does not close filedescriptors.
So just open less cursors to leak filedescriptors less often.
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Leaking them can result in running out of available filedescriptors.
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* In practise there are very few compressed files with trivial hashes.
* Blacklisting these values results in false positives in the gzip
issues.
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webapp has had a relation hash_functions, that modeled "comparable
functions". Images should not be compares to other files, since it makes
no sense to store them as the RGBA stream, that is being hashed. This
comparability property resembles an equivalence relation. So the
function table gains a column eqclass. Each class is represented by a
number and functions are statically assigned to these classes. Now the
filtering happens in SQL instead of Python.
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* Rename "image_sha512" to "png_sha512".
* dedup.image.ImageHash is now a base class for image hashes such as
PNGHash and GIFHash.
* Enable both hashes in importpkg.
* Fix README.
* Add new hash combinations to webapp.
* Add "gif file not named *.gif" to issues in update_sharing.
* Add redirect for "image_sha512" to webapp for backwards
compatibility.
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They cluttered webapp.py and now vim can give proper highlighting for
the templates.
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Actual savings on the full data set are around 7%.
Conflicts:
README
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Currently this is invalid .gz files and png files not named .png.
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This should reduce the query bandwidth to the rdbms.
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This already worked quite well for package.id. On a test data set of 5%
size this transformation reduces the database size by about 4%.
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We can avoid a b-tree sort in the package comparison of the web app, if
the package index, also provides a size.
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One approach to improve performance is to reduce the database size. A
package name takes up 15 bytes in average. A number of a package takes
up two bytes. Multiply that difference with the number of references and
it should be noticeably. A small test set show a reduction by 10%.
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sharing_package_index is a sub-index of sharing_insert_index and
therefore unnecessary.
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+ Way faster on multiple cores.
+ More reliable, cause http connections do not time out when the db
blocks.
- Way slower on single core with contended io path. No clue why.
Still update_sharing.py makes up the bulk of processing time.
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The git binary changed and so did its hash. Choosing a more stable
example now: The GPL-3.
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This appears to be a huge performance boost.
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This gets back the original functionality of importpkg.py.
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importpkg.py now emits a yaml stream instead of updating the database.
The acutual updating now happens in readyaml.py. In this process
autoimport.py was significantly reworked to import packages in parallel.
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