chore: fix ops.ToTimedeltaOp and ops.IsInOp sqlglot compiler

Author: chelsea-lin

bigframes/core/compile/sqlglot/expressions/unary_compiler.py

@@ -420,6 +420,8 @@ def _(op: ops.base_ops.UnaryOp, expr: TypedExpr) -> sge.Expression:
 
 @UNARY_OP_REGISTRATION.register(ops.IsInOp)
 def _(op: ops.IsInOp, expr: TypedExpr) -> sge.Expression:
+    if op.values is None or len(op.values) == 0:
+        return sge.convert(False)
     return sge.In(this=expr.expr, expressions=[sge.convert(v) for v in op.values])
 
 
@@ -767,7 +769,7 @@ def _(op: ops.ToTimedeltaOp, expr: TypedExpr) -> sge.Expression:
     factor = UNIT_TO_US_CONVERSION_FACTORS[op.unit]
     if factor != 1:
         value = sge.Mul(this=value, expression=sge.convert(factor))
-    return sge.Interval(this=value, unit=sge.Identifier(this="MICROSECOND"))
+    return value
 
 
 @UNARY_OP_REGISTRATION.register(ops.UnixMicros)

tests/system/small/engines/test_generic_ops.py

@@ -392,7 +392,7 @@ def test_engines_invert_op(scalars_array_value: array_value.ArrayValue, engine):
     assert_equivalence_execution(arr.node, REFERENCE_ENGINE, engine)
 
 
-@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+@pytest.mark.parametrize("engine", ["polars", "bq", "bq-sqlglot"], indirect=True)
 def test_engines_isin_op(scalars_array_value: array_value.ArrayValue, engine):
     arr, col_ids = scalars_array_value.compute_values(
         [

tests/unit/core/compile/sqlglot/expressions/snapshots/test_unary_compiler/test_is_in/empty.sql

@@ -0,0 +1,13 @@
+WITH `bfcte_0` AS (
+  SELECT
+    `int64_col` AS `bfcol_0`
+  FROM `bigframes-dev`.`sqlglot_test`.`scalar_types`
+), `bfcte_1` AS (
+  SELECT
+    *,
+    FALSE AS `bfcol_1`
+  FROM `bfcte_0`
+)
+SELECT
+  `bfcol_1` AS `int64_col`
+FROM `bfcte_1`

tests/unit/core/compile/sqlglot/expressions/snapshots/test_unary_compiler/test_to_timedelta/out.sql

@@ -8,15 +8,15 @@ WITH `bfcte_0` AS (
     *,
     `bfcol_1` AS `bfcol_4`,
     `bfcol_0` AS `bfcol_5`,
-    INTERVAL `bfcol_0` MICROSECOND AS `bfcol_6`
+    `bfcol_0` AS `bfcol_6`
   FROM `bfcte_0`
 ), `bfcte_2` AS (
   SELECT
     *,
     `bfcol_4` AS `bfcol_10`,
     `bfcol_5` AS `bfcol_11`,
     `bfcol_6` AS `bfcol_12`,
-    INTERVAL (`bfcol_5` * 1000000) MICROSECOND AS `bfcol_13`
+    `bfcol_5` * 1000000 AS `bfcol_13`
   FROM `bfcte_1`
 ), `bfcte_3` AS (
   SELECT
@@ -25,7 +25,7 @@ WITH `bfcte_0` AS (
     `bfcol_11` AS `bfcol_19`,
     `bfcol_12` AS `bfcol_20`,
     `bfcol_13` AS `bfcol_21`,
-    INTERVAL (`bfcol_11` * 604800000000) MICROSECOND AS `bfcol_22`
+    `bfcol_11` * 604800000000 AS `bfcol_22`
   FROM `bfcte_2`
 )
 SELECT

tests/unit/core/compile/sqlglot/expressions/test_unary_compiler.py

@@ -307,10 +307,13 @@ def test_invert(scalar_types_df: bpd.DataFrame, snapshot):
 
 def test_is_in(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["int64_col"]]
-    sql = _apply_unary_op(bf_df, ops.IsInOp(values=(1, 2, 3)), "int64_col")
 
+    sql = _apply_unary_op(bf_df, ops.IsInOp(values=(1, 2, 3)), "int64_col")
     snapshot.assert_match(sql, "out.sql")
 
+    sql = _apply_unary_op(bf_df, ops.IsInOp(values=()), "int64_col")
+    snapshot.assert_match(sql, "empty.sql")
+
 
 def test_isalnum(scalar_types_df: bpd.DataFrame, snapshot):
     bf_df = scalar_types_df[["string_col"]]