Exercise 2: must vs. filter, "Contributes to Relevance Scoring," and the Missing SQL Equivalent — Possible Solution
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THE DIFFERENCE BETWEEN must AND filter
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Per this chapter, "must clauses contribute to relevance scoring
(search1-6's own material); filter clauses express yes/no criteria
that don't affect scoring at all — and, as a result, are more
cacheable and efficient."

WHAT "CONTRIBUTES TO RELEVANCE SCORING" ACTUALLY MEANS
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A must clause doesn't just decide whether a document is included in
the results at all — it also feeds into a numeric SCORE that
determines how each matching document is RANKED relative to the
others (the actual mechanism is covered fully in search1-6's own
TF-IDF/BM25 material). A document that matches a must clause more
strongly (a better full-text match, per search1-4's own term-frequency
material) gets a HIGHER score and ranks higher in the results than a
document that matches only weakly. A filter clause, by contrast,
answers only a binary yes/no question — does this document satisfy the
condition or not — with no notion of "how well" it satisfies it, and
has zero influence on where a matching document ranks among the other
results; it only decides inclusion or exclusion.

WHY SQL'S OWN WHERE CLAUSE HAS NO DIRECT EQUIVALENT
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Per this chapter, "ordinary SQL's own WHERE clause has no built-in
concept of 'this condition should also feed a relevance score' at
all." SQL's WHERE clause is purely a filtering mechanism — every
condition in a WHERE clause either includes or excludes a row, with no
native concept of one condition contributing MORE to some kind of
match quality than another condition does. SQL has no built-in notion
of ranking rows by how WELL they satisfy a condition, only whether
they satisfy it at all (ORDER BY can sort by an explicit column value
afterward, but that's a separate, later step operating on already-
filtered rows, not a scoring mechanism baked into the filtering
condition itself). This is exactly why the must-vs-filter distinction
is genuinely new territory rather than simply "Elasticsearch's version
of AND" — SQL was never built with the concept of a condition that
BOTH filters AND contributes to a relevance ranking simultaneously,
because relevance ranking isn't something SQL's own WHERE clause was
ever designed to express at all.

WHY THIS WORKS AS AN ANSWER
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It explains precisely what "contributes to scoring" means in terms of
ranking (not just inclusion/exclusion), and explains specifically why
SQL's WHERE clause structurally has no equivalent concept, rather than
treating the missing equivalence as an unexplained fact.