fix(db2): unwrap Alias(Select) before SYSDUMMY1 injection to fix column alias placement

db2_sqlglot registers _add_sysibm_dual as a preprocessor on exp.Select.
When the top-level node is Alias(Select, alias=name) — produced by
exp.select(expr).as_("col") — the generator renders the inner Select
(which adds FROM SYSIBM.SYSDUMMY1 via the preprocessor) and then appends
AS name after the fully-rendered SQL string, giving:

  SELECT ... FROM SYSIBM.SYSDUMMY1 AS the_col   ← broken

instead of:

  SELECT ... AS the_col FROM SYSIBM.SYSDUMMY1   ← correct

The column has no alias in the result so pandas sees column name '1'.

Fix in _fetch_native_df: when the expression is Alias(Select), move the
alias onto the first selected expression before the generator sees it.
The generator then processes a bare Select, SYSDUMMY1 lands in the right
place, and the column alias is emitted correctly.

Also add db2 to the col_name uppercase branch in test_to_time_column:
Db2 returns column names in uppercase (THE_COL) after normalize_identifiers,
same as Snowflake. Root cause is the db2_sqlglot dialect Alias/Select bug;
correct fix is in db2_sqlglot but is worked around here pending that fix.

Author: iawanish

sqlmesh/core/engine_adapter/db2.py

@@ -789,6 +789,27 @@ def _fetch_native_df(
         """
         if isinstance(query, exp.Expression):
             query = query.copy()
+            # The db2_sqlglot generator injects FROM SYSIBM.SYSDUMMY1 via a
+            # preprocessor registered on exp.Select.  When the caller passes
+            # Alias(Select, alias=name) — e.g. exp.select(expr).as_("col") —
+            # the generator renders the inner Select (adding FROM SYSDUMMY1)
+            # and then appends AS name after the fully-rendered SQL, producing:
+            #   SELECT ... FROM SYSIBM.SYSDUMMY1 AS name   ← broken
+            # instead of:
+            #   SELECT ... AS name FROM SYSIBM.SYSDUMMY1   ← correct
+            # This is a db2_sqlglot dialect bug (the Alias wrapper is not
+            # SELECT-aware).  Work around it: when the top-level node is
+            # Alias(Select), move the alias onto the first selected expression
+            # so the generator only ever sees a bare Select node.
+            if isinstance(query, exp.Alias) and isinstance(query.this, exp.Select):
+                inner = query.this
+                alias_name = query.alias
+                inner.set(
+                    "expressions",
+                    [exp.Alias(this=inner.expressions[0], alias=exp.to_identifier(alias_name))]
+                    + inner.expressions[1:],
+                )
+                query = inner
             normalize_identifiers(query, dialect=self.dialect)
         return super()._fetch_native_df(query, quote_identifiers=True)
 

tests/core/engine_adapter/integration/test_integration.py

@@ -2726,7 +2726,8 @@ def test_to_time_column(
     time_column = to_time_column(time_column, time_column_type, ctx.dialect, time_column_format)
     df = ctx.engine_adapter.fetchdf(exp.select(time_column).as_("the_col"))
     expected = result.get(ctx.dialect, result.get("default"))
-    col_name = "THE_COL" if ctx.dialect == "snowflake" else "the_col"
+    # Db2 (UPPERCASE strategy) returns column names in uppercase, same as Snowflake
+    col_name = "THE_COL" if ctx.dialect in ("snowflake", "db2") else "the_col"
     if expected is pd.NaT or expected is None:
         assert df[col_name][0] is expected
     else: