Disable sqlglot optimization for dbt projects

Author: treysp

.circleci/continue_config.yml

@@ -300,8 +300,8 @@ workflows:
           name: cloud_engine_<< matrix.engine >>
           context:
             - sqlmesh_cloud_database_integration
-          requires:
-            - engine_tests_docker
+          # requires:
+          #   - engine_tests_docker
           matrix:
             parameters:
               engine:
@@ -313,10 +313,10 @@ workflows:
                 - athena
                 - fabric
                 - gcp-postgres
-          filters:
-            branches:
-              only:
-                - main
+          # filters:
+          #   branches:
+          #     only:
+          #       - main
       - ui_style
       - ui_test
       - vscode_test

sqlmesh/dbt/model.py

@@ -745,11 +745,10 @@ def to_sqlmesh(
                     )
                 else:
                     model_kwargs["start"] = begin
-            # If user explicitly disables concurrent batches then we want to set depends on past to true which we
-            # will do by including the model in the depends_on
+            # If user explicitly disables concurrent batches then force sequential execution by setting batch_concurrency to 1
             if self.concurrent_batches is not None and self.concurrent_batches is False:
-                depends_on = model_kwargs.get("depends_on", set())
-                depends_on.add(self.canonical_name(context))
+                if hasattr(kind, "batch_concurrency"):
+                    kind.batch_concurrency = 1
 
         model_kwargs["start"] = model_kwargs.get(
             "start", context.sqlmesh_config.model_defaults.start
@@ -768,6 +767,7 @@ def to_sqlmesh(
             allow_partials=allow_partials,
             virtual_environment_mode=virtual_environment_mode,
             dbt_node_info=self.node_info,
+            optimize_query=False,
             **optional_kwargs,
             **model_kwargs,
         )

tests/core/integration/test_dbt.py

@@ -2,7 +2,6 @@
 
 import typing as t
 import pytest
-from sqlmesh.core.model.common import ParsableSql
 import time_machine
 
 from sqlmesh.core.context import Context
@@ -11,7 +10,6 @@
 )
 from sqlmesh.core.snapshot import (
     DeployabilityIndex,
-    SnapshotChangeCategory,
 )
 
 if t.TYPE_CHECKING:
@@ -20,27 +18,6 @@
 pytestmark = pytest.mark.slow
 
 
-@time_machine.travel("2023-01-08 15:00:00 UTC")
-def test_dbt_select_star_is_directly_modified(sushi_test_dbt_context: Context):
-    context = sushi_test_dbt_context
-
-    model = context.get_model("sushi.simple_model_a")
-    context.upsert_model(
-        model,
-        query_=ParsableSql(sql="SELECT 1 AS a, 2 AS b"),
-    )
-
-    snapshot_a_id = context.get_snapshot("sushi.simple_model_a").snapshot_id  # type: ignore
-    snapshot_b_id = context.get_snapshot("sushi.simple_model_b").snapshot_id  # type: ignore
-
-    plan = context.plan_builder("dev", skip_tests=True).build()
-    assert plan.directly_modified == {snapshot_a_id, snapshot_b_id}
-    assert {i.snapshot_id for i in plan.missing_intervals} == {snapshot_a_id, snapshot_b_id}
-
-    assert plan.snapshots[snapshot_a_id].change_category == SnapshotChangeCategory.NON_BREAKING
-    assert plan.snapshots[snapshot_b_id].change_category == SnapshotChangeCategory.NON_BREAKING
-
-
 @time_machine.travel("2023-01-08 15:00:00 UTC")
 def test_dbt_is_incremental_table_is_missing(sushi_test_dbt_context: Context):
     context = sushi_test_dbt_context

tests/core/integration/test_multi_repo.py

@@ -413,7 +413,7 @@ def test_multi_hybrid(mocker):
     sqlmesh_rendered = (
         'SELECT "e"."col_a" AS "col_a", "e"."col_b" AS "col_b" FROM "memory"."dbt_repo"."e" AS "e"'
     )
-    dbt_rendered = 'SELECT DISTINCT ROUND(CAST(("b"."col_a" / NULLIF(100, 0)) AS DECIMAL(16, 2)), 2) AS "rounded_col_a" FROM "memory"."sqlmesh_repo"."b" AS "b"'
+    dbt_rendered = 'SELECT DISTINCT ROUND(CAST(("col_a" / NULLIF(100, 0)) AS DECIMAL(16, 2)), 2) AS "rounded_col_a" FROM "memory"."sqlmesh_repo"."b" AS "b"'
     assert sqlmesh_model_a.render_query().sql() == sqlmesh_rendered
     assert dbt_model_c.render_query().sql() == dbt_rendered
 

tests/dbt/test_model.py

@@ -373,7 +373,8 @@ def test_load_microbatch_all_defined_diff_values(
         column=exp.to_column("blah", quoted=True), format="%Y-%m-%d"
     )
     assert model.kind.batch_size == 1
-    assert model.depends_on_self is True
+    assert model.kind.batch_concurrency == 1
+    assert model.depends_on_self is False
 
 
 @pytest.mark.slow
@@ -630,7 +631,7 @@ def test_load_microbatch_with_ref(
     )
     assert (
         context.render(microbatch_two_snapshot_fqn, start="2025-01-01", end="2025-01-10").sql()
-        == 'SELECT "_q_0"."cola" AS "cola", "_q_0"."ds" AS "ds" FROM (SELECT "microbatch"."cola" AS "cola", "microbatch"."ds" AS "ds" FROM "local"."main"."microbatch" AS "microbatch" WHERE "microbatch"."ds" < \'2025-01-11 00:00:00+00:00\' AND "microbatch"."ds" >= \'2025-01-01 00:00:00+00:00\') AS "_q_0"'
+        == 'SELECT "cola" AS "cola", "ds" AS "ds" FROM (SELECT * FROM "local"."main"."microbatch" AS "microbatch" WHERE "ds" >= \'2025-01-01 00:00:00+00:00\' AND "ds" < \'2025-01-11 00:00:00+00:00\') AS "_q_0"'
     )
 
 
@@ -696,7 +697,7 @@ def test_load_microbatch_with_ref_no_filter(
     )
     assert (
         context.render(microbatch_two_snapshot_fqn, start="2025-01-01", end="2025-01-10").sql()
-        == 'SELECT "microbatch"."cola" AS "cola", "microbatch"."ds" AS "ds" FROM "local"."main"."microbatch" AS "microbatch"'
+        == 'SELECT "cola" AS "cola", "ds" AS "ds" FROM "local"."main"."microbatch" AS "microbatch"'
     )
 
 
@@ -1104,7 +1105,7 @@ def test_conditional_ref_in_unexecuted_branch(copy_to_temp_path: t.Callable):
     assert rendered is not None
     assert (
         rendered.sql()
-        == 'WITH "source" AS (SELECT "simple_model_a"."a" AS "a" FROM "memory"."sushi"."simple_model_a" AS "simple_model_a") SELECT "source"."a" AS "a" FROM "source" AS "source"'
+        == 'WITH "source" AS (SELECT * FROM "memory"."sushi"."simple_model_a" AS "simple_model_a") SELECT * FROM "source" AS "source"'
     )
 
     # And run plan with this conditional model for good measure