Die, python2, die.
Some generated .java files change (parameterized automata for
spell-correction).
This is because the order of python dictionaries was not well-defined
previously. A sort() was added so that the python code now generates
reproducible output (Thanks @mikemccand).
So we'll suffer a change once, but the automata are equivalent. If you
run the script again you should not see source code changes.
The relevant unit tests are exhaustive (if you trust the paper!), so we can
be confident it does not break things, even though it looks very scary.
On newer linux distros, at least, 'python' now means python3. So
we can't rely on what version of python it will invoke (at least for a
few years).
For example in Fedora Linux:
https://fedoraproject.org/wiki/Changes/Python_means_Python3
For python2.x code, explicitly call 'python2.7' and for python3.x code,
explicitly call 'python3'.
Ant variable names are cleaned up, e.g. 'python.exe' is renamed to
'python2.exe' and 'python32.exe' is renamed to 'python3.exe'. This also
makes it easy to identify remaining python 2.x code that should be
migrated to python 3.x
Previous situation:
* The snowball base classes (Among, SnowballProgram, etc) had accumulated local performance-related changes. There was a task that would also "patch" generated classes (e.g. GermanStemmer) after-the-fact.
* Snowball classes had many "non-changes" from the original such as removal of tabs addition of javadocs, license headers, etc.
* Snowball test data (inputs and expected stems) was incorporated into lucene testing, but this was maintained manually. Also files had become large, making the test too slow (Nightly).
* Snowball stopwords lists from their website were manually maintained. In some cases encoding fixes were manually applied.
* Some generated stemmers (such as Estonian and Armenian) exist in lucene, but have no corresponding `.sbl` file in snowball sources at all.
Besides this mess, snowball project is "moving along" and acquiring new languages, adding non-BSD-licensed test data, huge test data, and other complexity. So it is time to automate the integration better.
New situation:
* Lucene has a `gradle snowball` regeneration task. It works on Linux or Mac only. It checks out their repos, applies the `snowball.patch` in our repository, compiles snowball stemmers, regenerates all java code, applies any adjustments so that our build is happy.
* Tests data is automatically regenerated from the commit hash of the snowball test data repository. Not all languages are tested from their data: only where the license is simple BSD. Test data is also (deterministically) sampled, so that we don't have huge files. We just want to make sure our integration works.
* Randomized tests are still set to test every language with generated fake words. The regeneration task ensures all languages get tested (it writes a simple text file list of them).
* Stopword files are automatically regenerated from the commit hash of the snowball website repository.
* The regeneration procedure is idempotent. This way when stuff does change, you know exactly what happened. For example if test data changes to a different license, you may see a git deletion. Or if a new language/stopwords/test data gets added, you will see git additions.
Java 13 adds a new doclint check under "accessibility" that the html
header nesting level isn't crazy.
Many are incorrect because the html4-style javadocs had horrible
font-sizes, so developers used the wrong header level to work around it.
This is no issue in trunk (always html5).
Java recommends against using such structured tags at all in javadocs,
but that is a more involved change: this just "shifts" header levels
in documents to be correct.
the "missing javadocs" checker needed tweaks to work with the format
changes of java 13.
As a followup we may investigate javadoc (maybe the new doclet api). It
has its own missing checks too now, but they are black vs white (either
fully documented or not checked), whereas this python tool allows us to
"improve", e.g. enforce that all classes have doc, even if all
methods do not yet.
Current javadocs declare an HTML5 doctype: !DOCTYPE HTML. Some HTML5
features are used, but unfortunately also some constructs that do not
exist in HTML5 are used as well.
Because of this, we have no checking of any html syntax. jtidy is
disabled because it works with html4. doclint is disabled because it
works with html5. our docs are neither.
javadoc "doclint" feature can efficiently check that the html isn't
crazy. we just have to fix really ancient removed/deprecated stuff
(such as use of tt tag).
This enables the html checking in both ant and gradle. The docs are
fixed via straightforward transformations.
One exception is table cellpadding, for this some helper CSS classes
were added to make the transition easier (since it must apply padding
to inner th/td, not possible inline). I added TODOs, we should clean
this up. Most problems look like they may have been generated from a
GUI or similar and not a human.
The entire precommit task will still fail with unsupported java version
(subsequent checks do not support the newer javadocs format).
But this allows the ECJ linter to run, which checks for things such as
unused imports.
Adds some build parameters to tune how tests run. There is an example
shown by "gradle helpLocalSettings"
Default C2 off in tests as it is wasteful locally and causes slowdown of
tests runs. You can override this by setting tests.jvmargs for gradle,
or args for ant.
Some crazy lucene stress tests may need to be toned down after the
change, as they may have been doing too many iterations by default...
but this is not a new problem.
Some permissions and build hacks were made on behalf of hadoop: hacks on
top of hacks. Now that the major problems such as classpath pollution and
hadoop test code are fixed, so we can remove hacks built on top of them.
previously, entire classpath of ant (ant itself, plugins, ivy, etc) were
polluting the unit tests classpath. it leads to non-reproducible build
issues because tests classpath is different depending on things outside
of source code control.
for example, solr tests launching hadoop, hadoop launching jetty, jetty
scanning classpath -> boom
Restrict this to only minimal paths like lucene. It is the defense for directory traversal attacks.
It will also help find bad bugs where things are reading filesystem in the wrong locations.
Uwe Schindler
Mike Drob
Robert Muir
Dawid Weiss
Kevin Risden
Chris Hostetter
Tomoko Uchida
Steve Rowe
markrmiller
Varun Thacker
Jan Høydahl
Erick
Alexandre Rafalovitch
Alan Woodward