Enable SQL compilation caching for the ignore-nulls window functions

[rebkwok]

Description

FirstValue, LastValue, NthValue, Lead, and Lag (the IGNORE NULLS-capable window functions registered on TrinoSQLCompiler), don't declare _traverse_internals or inherit_cache, which means SQLAlchemy's SQL compilation cache (added in 1.4) can't produce a cache key, falls back to recompiling from scratch every time, and emits a warning ("Class X will not make use of SQL compilation caching...").

Each class now gets its own _traverse_internals, extending Function's (the nearest ancestor in their hierarchy that defines one) with an extra traversal instruction for ignore_nulls.

For backwards compatibility, there's a hasattr check for Function._traverse_internals (doesn't exist pre-1.4)

Added two parametrized tests (across all five functions) confirming a cache key is actually produced with no warning, and that cache keys correctly distinguish both different arguments and different ignore_nulls values. Confirmed both new tests fail without the code fix.

Reproduce with (sqlalchemy >= 1.4):

import warnings
from sqlalchemy import func, table, column
import trino.sqlalchemy.dialect  # registers Lag etc. as SQLAlchemy GenericFunctions

t = table("t", column("x"))

with warnings.catch_warnings(record=True) as w:
    warnings.simplefilter("always")
    stmt = func.lag(t.c.x).over(order_by=t.c.x)
    print(stmt._generate_cache_key())  # None, before this fix
    print([str(x.message) for x in w])  # the SAWarning, before this fix

Non-technical explanation

Queries using these window functions (LAG, LEAD, FIRST_VALUE, LAST_VALUE, NTH_VALUE) couldn't benefit from SQLAlchemy's statement caching, so every execution recompiled the SQL from scratch and printed a performance-warning. This fix lets SQLAlchemy cache and reuse the compiled SQL for these statements, as it already does for most others.

Release notes

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* Fix SQLAlchemy's SQL compilation caching for `first_value`, `last_value`, `nth_value`, `lead`, and `lag`; these now cache by default and avoid emitting SQLAlchemy performance warnings.

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