We want to index all words in the document, stopword handling is moved to the index where we change the semantics to elide inclusion checks in query construction for a very short list of words tentatively hard-coded in SearchTerms.
To help offer verbatim matches for external link texts, we assign these positions in the document a bit after the actual document ends. Integrating this information with the ranking is not performed here.
The first change, running index construction in parallel, was previously how it was done, but it was changed to run sequentially to see how it would affect performance. It got worse, so the change is reverted.
Though it's been noted that sorting in parallel is likely not a good idea as it leads to a lot of I/O thrashing, so this is changed to be done sequentially.
This lets the slop library be stand-alone without dependence on coded-sequence.
The change also gets rid of the vestigial seek() method in ColumnReader.
The most common error when dealing with Slop columns is that they can fall out of sync with each other if the programmer accidentally does a conditional read and forgets to skip.
The second most common error is forgetting to close one of the columns in a reader or writer.
To deal with both cases, a new class SlopTable is added that keeps track of the lifecycle of all slop columns and performs a check when closing them that they are in sync.
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.
Expected behavior changed since the ranking algorithm now takes into account the number of positions of the keyword, and the test loader was previously modified to generate positions based on prime factors of the document id.
