Taxonomy: Improve AND term query performance

[Sukhendu2002]

This PR improves the performance of taxonomy queries using the AND operator, including category__and.

Small term intersections now use one indexed wp_term_relationships join per term instead of executing a correlated subquery for every candidate object. The optimization is limited to three total taxonomy joins. Larger intersections retain the existing correlated subquery because benchmarks showed that additional joins can regress queries where all terms are common.

Trac ticket: https://core.trac.wordpress.org/ticket/16706

Benchmark results

Benchmarks used 50,000 synthetic published posts on MySQL 8.4.10 and MariaDB 10.11.18. Values are medians from five warmed runs after analyzing the tables. Both query forms returned identical post IDs.

Database	Scenario	Terms	JOIN	Subquery	Improvement
MySQL 8.4	Selective	3	0.725 ms	140.919 ms	194.36×
MySQL 8.4	Common	3	108.164 ms	142.594 ms	1.32×
MySQL 8.4	No match	3	49.135 ms	139.557 ms	2.84×
MariaDB 10.11	Selective	3	0.562 ms	127.070 ms	226.03×
MariaDB 10.11	Common	3	108.215 ms	130.360 ms	1.20×
MariaDB 10.11	No match	3	50.801 ms	127.312 ms	2.51×

Four joins were approximately neutral for common terms, while five or more regressed. This is why the automatic optimization stops at three total taxonomy joins.

Absolute timings are environment-specific, but the trend was consistent across both database engines.

Use of AI Tools

AI assistance: Yes
Tool(s): Pi coding agent
Model(s): GPT-5.6
Used for: Ticket validation, initial implementation, benchmark design, code review, and drafting this PR description. The final changes and test results were reviewed by me.

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