Indeed this is code is ASL2 pre-7.10, but I wouldn't have expected any
concerns regardless. Jack volunteered to bring this code to Lucene by
removing the Elasticsearch-specific bits.

On Mon, May 10, 2021 at 4:55 PM Michael McCandless <
[email protected]> wrote:

> +1 to start from the Elasticsearch implementation for low-level query
> execution tracing, which I think is from (pre-7.10) ASL2 licensed code?
>
> That sounds helpful, even with the Heisenberg caveats.
>
> Mike McCandless
>
> http://blog.mikemccandless.com
>
> On Thu, May 6, 2021 at 4:24 PM Adrien Grand <[email protected]> wrote:
>
>> We have something like that in Elasticsearch that wraps queries in order
>> to be able to report cost, matchCost and the number of calls to
>> nextDoc/advance/matches/score/advanceShallow/getMaxScore for every node in
>> the query tree.
>>
>> It's not perfect as it needs to disable some optimizations in order to
>> work properly. For instance bulk scorers are disabled and conjunctions are
>> not inlined, which means that clauses may run in a different order. So
>> results need to be interpreted carefully as the way the query gets executed
>> when observed may differ a bit from how it gets executed normally. That
>> said it has still been useful in a number of cases. I don't think our
>> implementation works when IndexSearcher is configured with an executor but
>> we could maybe put it in sandbox and iterate from there?
>>
>> For your case, do you think it could be attributed to deleted docs?
>> Deleted docs are checked before two-phase confirmation and collectors but
>> after disjunctions/conjunctions of postings.
>>
>> Le jeu. 6 mai 2021 à 20:20, Michael Sokolov <[email protected]> a
>> écrit :
>>
>>> Do we have a way to understand how BooleanQuery (and other composite
>>> queries) are advancing their child queries? For example, a simple
>>> conjunction of two queries advances the more restrictive (lower
>>> cost()) query first, enabling the more costly query to skip over more
>>> documents. But we may not be making the best choice in every case, and
>>> I would like to know, for some query, how we are doing. For example,
>>> we could execute in a debugging mode, interposing something that wraps
>>> or observes the Scorers in some way, gathering statistics about how
>>> many documents are visited by each Scorer, which can be aggregated for
>>> later analysis.
>>>
>>> This is motivated by a use case we have in which we currently
>>> post-filter our query results in a custom collector using some filters
>>> that we know to be expensive (they must be evaluated on every
>>> document), but we would rather express these post-filters as Queries
>>> and have them advanced during the main Query execution. However when
>>> we tried to do that, we saw some slowdowns (in spite of marking these
>>> Queries as high-cost) and I suspect it is due to the iteration order,
>>> but I'm not sure how to debug.
>>>
>>> Suggestions welcome!
>>>
>>> -Mike
>>>
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-- 
Adrien

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