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https://issues.apache.org/jira/browse/JENA-473?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13689768#comment-13689768
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Rob Vesse commented on JENA-473:
--------------------------------
So the issue with the implicit left join case blocking is down to how VarFinder
classifiers the variables and what LeftJoinClassifer does with that information
The problem is that with the assign introduced the variable being assigned from
ends up in the filterMentions list and one of the checks in the Left Join
classifier explicitly disallows linearization if the LHS variables have any
intersection with mentioned filter variables on the RHS.
I'm wondering if it is actually sensible to define a separate category for
assign and extend mentioned vars and track those separately?
Andy - Are there examples you can think of where linearizing a left join with
the relaxed restriction changes the query semantics?
> ARQ should be able to optimize implicit joins and implicit left joins
> ---------------------------------------------------------------------
>
> Key: JENA-473
> URL: https://issues.apache.org/jira/browse/JENA-473
> Project: Apache Jena
> Issue Type: Improvement
> Components: ARQ
> Reporter: Rob Vesse
> Assignee: Rob Vesse
> Labels: optimization, sparql
> Fix For: Jena 2.10.2
>
> Attachments: impl-join.csv, impl-join-opt.csv
>
>
> There is a class of useful optimizations that currently ARQ does not even
> attempt to apply which are usually referred to as implicit joins.
> A trivial example is as follows:
> SELECT *
> WHERE
> {
> ?x ?p1 ?o1 .
> ?y ?p2 ?o2 .
> FILTER(?x = ?y)
> }
> Currently this requires us to compute a cross product and then apply the
> filter, even with streaming evaluation this can be extremely costly. The aim
> of this optimization is to produce a query like the following:
> SELECT *
> WHERE
> {
> ?x ?p1 ?o1 .
> ?x ?p2 ?o2 .
> BIND(?x AS ?y)
> }
> This optimization can also be applied to some left joins where the implicit
> join applies across the join e.g.
> SELECT *
> WHERE
> {
> ?x ?p1 ?o1 .
> OPTIONAL
> {
> ?y ?p2 ?o2 .
> FILTER(?x = ?y)
> }
> }
> This can be thought of as a generalization of TransformFilterEquality except
> covering the case where both items are variables. Since both things are
> variables we need to be careful about when we apply this optimization since
> when = is used we need to guarantee that substituting one variable for the
> other does not alter the semantics of the query.
> I believe the optimization is safe to apply providing that we can guarantee
> (as far as possible) that one variable is non-literal. This can be done by
> inspecting the positions in which the mentioned variables are used and
> ensuring that at least one of the variables occurs in the graph, subject or
> predicate position.
> Safety for left joins is a little more complex since we must ensure that at
> least one of the variables occurs in the RHS and we can only make the
> substitution in the RHS as otherwise we change the join semantics.
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