first pass: microbatch

dbt/include/spark/macros/materializations/incremental/strategies.sql

@@ -75,6 +75,9 @@
   {%- elif strategy == 'insert_overwrite' -%}
     {#-- insert statements don't like CTEs, so support them via a temp view #}
     {{ get_insert_overwrite_sql(source, target, existing) }}
+  {%- elif strategy == 'microbatch' -%}
+    {#-- insert statements don't like CTEs, so support them via a temp view #}
+    {{ get_insert_overwrite_sql(source, target, existing) }}
   {%- elif strategy == 'merge' -%}
   {#-- merge all columns for datasources which implement MERGE INTO (e.g. databricks, iceberg) - schema changes are handled for us #}
     {{ get_merge_sql(target, source, unique_key, dest_columns=none, incremental_predicates=incremental_predicates) }}

tests/functional/adapter/incremental_strategies/test_microbatch.py

@@ -0,0 +1,17 @@
+import pytest
+
+from dbt.tests.adapter.incremental.test_incremental_microbatch import (
+    BaseMicrobatch,
+)
+
+# No requirement for a unique_id for spark microbatch!
+_microbatch_model_no_unique_id_sql = """
+{{ config(materialized='incremental', incremental_strategy='microbatch', event_time='event_time', batch_size='day') }}
+select * from {{ ref('input_model') }}
+"""
+
+
+class TestMicrobatch(BaseMicrobatch):
+    @pytest.fixture(scope="class")
+    def microbatch_model_sql(self) -> str:
+        return _microbatch_model_no_unique_id_sql