[SQL] Reject incompatible Parquet row reader conversions

[Jiayi-Wang-db]

What changes were proposed in this pull request?

Make the Parquet row-based reader reject two incompatible primitive type conversions that the
vectorized reader already rejects:

• Parquet FIXED_LEN_BYTE_ARRAY to Spark SQL STRING
• Parquet INT32 annotated as DATE to Spark SQL DECIMAL

The row converter now accepts INT32 and INT64 as decimals only when their logical annotation
is decimal, absent, or a signed integer annotation. Unsupported conversions raise
SchemaColumnConvertNotSupportedException, consistently with the vectorized reader.

This follows the conversion semantics established by SPARK-34212 and SPARK-40876. The earlier
SPARK-32317 / PR #29600 discussion proposed a broader configurable conversion matrix but was not
merged.

Closes #58495.

Why are the changes needed?

The row-based reader currently ignores incompatible logical and physical type combinations. It
interprets a DATE value as an unannotated integer-backed decimal and interprets arbitrary
fixed-length bytes as UTF-8. This can silently return incorrect data, while reading the same file
and requested schema with the vectorized reader fails with a Parquet column type mismatch.

Both readers should reject these unsupported conversions instead of producing reader-dependent
results.

Does this PR introduce any user-facing change?

Yes. When the vectorized Parquet reader is disabled, the two unsupported schema conversions above
now fail with FAILED_READ_FILE.PARQUET_COLUMN_DATA_TYPE_MISMATCH instead of returning incorrectly
interpreted values. Supported binary-to-string and integer-to-decimal conversions are unchanged.

How was this patch tested?

Added an end-to-end test in ParquetIOSuite that writes raw Parquet schemas for both incompatible
conversions and verifies that the row-based and vectorized readers return the same error condition.

The focused test command was attempted locally:

build/sbt 'sql/core/testOnly org.apache.spark.sql.execution.datasources.parquet.ParquetIOSuite -- -z "Parquet readers reject incompatible primitive type conversions consistently"'

Was this patch authored or co-authored using generative AI tooling?

Generated-by: OpenAI Codex (GPT-5)

[uros-b]

Thank you for the PR @Jiayi-Wang-db, could you please make a Spark Jira ticket for this change? Please see: https://issues.apache.org/jira/projects/SPARK/

Also, could you please enable GHA / GitHub Actions workflows (please see "Pull request" in https://spark.apache.org/contributing.html)