fix(spark): accept STRING and TIMESTAMP start dates in next_day

[harsh-ande]

Which issue does this PR close?

• Closes [Bug] next_day rejects STRING and TIMESTAMP start dates that Spark accepts #23889.

Rationale for this change

Spark's NextDay casts its first argument to DATE, so next_day('2015-07-23', 'Mon') and next_day(TIMESTAMP '2015-07-23 12:12:12', 'Mon') both work. datafusion-spark declared Exact(Date32, Utf8) and failed at planning for STRING and TIMESTAMP inputs.

What changes are included in this PR?

• next_day now uses a coercible signature: the first argument is implicitly cast to DATE from STRING or TIMESTAMP, and the day-of-week is any string type (numeric is still coerced to string).
• The kernel is unchanged.
• In next_day.slt, three existing query error expectations changed to the new planner messages (arity and non-date first argument), and the unparseable-string case now returns a cast error. They still fail at planning or execution as before.

What is the testing strategy for this PR?

New cases in spark/datetime/next_day.slt: string, string with a time part, timestamp literal, string column with NULL, timestamp column, and LargeUtf8/Utf8View day-of-week. I compared the expected results with pyspark==4.0.0, ANSI on and off.

Are there any user-facing changes?

next_day accepts more argument types. No API changes.

Known limitations / unknowns

• An unparseable date string always errors. Spark returns NULL with ANSI off and errors with ANSI on. This looks tied to the ANSI work in [Bug] next_day cross-version divergence: ANSI default flip and error class change between Spark 3.5 and 4.x #23890 and [EPIC] Support ANSI mode #23929.
• I did not verify timestamps with time zones near midnight against Spark's session-time-zone cast.
• fix: [spark] honor ANSI mode in next_day, and fix a panic and a missing argument shape #23892 touches the same files, so I expect a small rebase if it merges first.
• AI assistance was used to implement this. I reviewed and understand the change, and checked the results against Spark.