The priority index documents file can be trivially compressed to a large degree.
Compression schema:
```
00b -> diff docord (E gamma)
01b -> diff domainid (E delta) + (1 + docord) (E delta)
10b -> rank (E gamma) + domainid,docord (raw)
11b -> 30 bit size header, followed by 1 raw doc id (61 bits)
```
The implementation was incorrectly using 1 bit more than it should. The change also adds a put method for Elias delta; and cleans up the interface a bit.
This commit introduces a readme.md file to document the functionality and usage of the coded-sequence library. It covers the Elias Gamma code support, how sequences are encoded, and methods the library offers to query sequences, iterate over values, access data, and decode sequences.
It had been previously assumed that re-writing this function in the style of retain() would make it faster, but it had the opposite effect.
The reason why retain is so fast due to properties of the data that hold true when intersecting document lists, where long runs of adjacent documents are expected, but not when looking up the data associated with the already intersected documents, where the data is more sparse.
IntArray gets the YAGNI axe. The array library had two implementations, one for longs which was used, and one for ints, which only ever saw bit rot. Removing the latter, as all it ever did was clutter up the codebase and add technical debt. If we need int arrays, we fork LongArray again (or add int capabilities to it)
Also cleaning up the interfaces, removing layers of redundant abstractions and adding javadocs.
Finally adding sz=2 specializations to the quick- and insertion sort algorithms. It seems the JIT isn't optimizing these particularly well, this is an attempt to help it out a bit.
Retire search functions that weren't used, including the native implementations. Drop confusing suffixes on search function names. Search functions no longer encode search misses as negative values.
Replaced binary search function with a branchless version that is much faster.
Cleaned up benchmark code.
Retire search functions that weren't used, including the native implementations. Drop confusing suffixes on search function names. Search functions no longer encode search misses as negative values.
Replaced binary search function with a branchless version that is much faster.
Cleaned up benchmark code.
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.
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.
The sign of the counter is used to indicate whether a term has appeared as title. Until it's seen in the title, it's provisionally saved as a negative count.
The code would always re-initialize the static ngramLexicon and rdrposTagger fields with new instances even if they were already instantiated, leading to a ton of unnecessary RAM allocation.
The modified behavior checks for nullity before creating a new instance.
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.
Look, this will make the git history look funny, but trimming unnecessary depth from the source tree is a very necessary sanity-preserving measure when dealing with a super-modularized codebase like this one.
While it makes the project configuration a bit less conventional, it will save you several clicks every time you jump between modules. Which you'll do a lot, because it's *modul*ar. The src/main/java convention makes a lot of sense for a non-modular project though. This ain't that.
Cleaning out a lot of old junk from the code, and one thing lead to another...
* Build is improved, now constructing docker images with 'jib'. Clean build went from 3 minutes to 50 seconds.
* The ProcessService's spawning is smarter. Will now just spawn a java process instead of relying on the application plugin's generated outputs.
* Project is migrated to GraalVM
* gRPC clients are re-written with a neat fluent/functional style. e.g.
```channelPool.call(grpcStub::method)
.async(executor) // <-- optional
.run(argument);
```
This change is primarily to allow handling ManagedChannel errors, but it turned out to be a pretty clean API overall.
* For now the project is all in on zookeeper
* Service discovery is now based on APIs and not services. Theoretically means we could ship the same code either a monolith or a service mesh.
* To this end, began modularizing a few of the APIs so that they aren't strongly "living" in a service. WIP!
Missing is documentation and testing, and some more breaking apart of code.
