Enable Delta Lake schema enforcement and safely perform schema evolution with mergeSchema

Steps

1. Delta Lake enforces schema by default; attempt to write a DataFrame with a mismatched column to observe the AnalysisException and understand the enforcement boundary.
2. To add new columns from an incoming DataFrame, enable schema evolution with df.write.format('delta').option('mergeSchema', 'true').mode('append').save('/path/to/table').
3. For DDL-driven evolution, use ALTER TABLE delta.`/path/to/table` ADD COLUMNS (new_col STRING) to add columns explicitly without a write operation.
4. Set the table-level property delta.columnMapping.mode=name if you need to rename or drop columns without rewriting data (requires Delta protocol version 2).
5. Validate the resulting schema with DESCRIBE delta.`/path/to/table` or spark.read.format('delta').load('/path/to/table').schema to confirm the evolution applied correctly.