dtenedor opened a new pull request, #37501:
URL: https://github.com/apache/spark/pull/37501

   ### What changes were proposed in this pull request?
   
   Fix a bug in column DEFAULT support for non-vectorized Parquet scans, where 
inserting explicit NULL values to a column with a DEFAULT and then selecting 
the column back would sometimes erroneously return the default value. 
   
   To exercise the behavior:
   
   ```
   set spark.sql.parquet.enableVectorizedReader=false;
   create table t(a int) using parquet;
   insert into t values (42);
   alter table t add column b int default 42;
   insert into t values (43, null);
   select * from t;
   ```
   
   This should return two rows:
   
   `(42, 42) and (43, NULL)`
   
   But instead the scan missed the inserted NULL value, and returned the 
existence DEFAULT value of "42" instead:
   
   `(42, 42) and (43, 42)`.
   
   After this bug fix, Spark now returns the former correct result.
   
   ### Why are the changes needed?
   
   This fixes the correctness of SQL queries using Spark.
   
   ### Does this PR introduce _any_ user-facing change?
   
   No
   
   ### How was this patch tested?
   
   The PR includes unit test coverage.


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