Refactoring keyword extraction to extract spans information.
Modifying the intermediate storage of converted data to use the new slop library, which is allows for easier storage of ad-hoc binary data like spans and positions.
This is a bit of a katamari damacy commit that ended up dragging along a bunch of other fairly tangentially related changes that are hard to break out into separate commits after the fact. Will push as-is to get back to being able to do more isolated work.
Decorates DocumentSentences with information about which HTML tags they are nested in, and removes some redundant data on this rather memory hungry object. Separator information is encoded as a bit set instead of an array of integers.
The change also cleans up the SentenceExtractor class a fair bit. It no longer extracts ngrams, and a significant amount of redundant operations were removed as well. This is still a pretty unpleasant class to work in, but this is the first step in making it a little bit better.
The change also restructures the internal API a bit, moving resultsFromDomain from RpcRawResultItem into RpcDecoratedResultItem, as the previous order was driving complexity in the code that generates these objects, and the consumer side of things puts all this data in the same object regardless.
Adding new ranking parameters to the API and routing them through the system, in order to permit integration of the new position data with the ranking algorithm.
The change also cleans out several parameters that no longer filled any function.
Add a new rule that crates an alternative path that omits a word if it's a stopword.
In queries where a stopword is present, and no query ngram expansion is possible, the query should not require the stopword to be present in the index, as this results in no search results being found.
Roll back to JDK 21 for now, and make Java version configurable in the root build.gradle
The project has run into no less than three distinct show-stopping bugs in JDK22, across multiple vendors, and gradle still doesn't fully support it, meaning you need multiple JDK versions installed.
This functionality fell into disrepair some while ago. It's supposed to allow non-mandatory search terms that boost the ranking if they are present in the document.
The change set cleans up the data model for the term-level data. This used to contain a bunch of fields with document-level metadata. This data-duplication means a larger memory footprint and worse memory locality.
The ranking code is also modified to not accept SearchResultKeywordScores, but rather CompiledQueryLong and CqDataInts containing only the term metadata and the frequency information needed for ranking. This is again an effort to improve memory locality.
We no longer break the query into "sets" of search terms and need to adapt the code to not use this assumption.
For the API service, we'll simulate the old behavior to keep the API stable.
For the search service, we'll introduce a new way of calculating positions through tree aggregation.
Seems to work, tests are green and initial testing finds no errors. Still a bit untested, committing WIP as-is because it would suck to lose weeks of work due to a drive failure or something.
This addresses the relatively common case where the graph consists of two segments, such as x y, z w; in this case we want an output like (x_y) (z w | z_w) | x y (z_w). The generated output does somewhat pessimize a few other cases, but this one is arguably more important.
