3. Append-only insert if no partitions

README.md

@@ -168,7 +168,8 @@ The following configurations can be supplied to models run with the dbt-spark pl
 **Incremental Models**
 
 To use incremental models, specify a `partition_by` clause in your model config. The default incremental strategy used is `insert_overwrite`, which will overwrite the partitions included in your query. Be sure to re-select _all_ of the relevant
-data for a partition when using the `insert_overwrite` strategy. If a `partition_by` config is not specified, dbt will overwrite the entire table as an atomic operation, replacing it with new data of the same schema. This is analogous to `truncate` + `insert`.
+data for a partition when using the `insert_overwrite` strategy. If a `partition_by` config is not specified, dbt will simply
+append new data to the model, without overwriting any existing data.
 
 ```
 {{ config(

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

@@ -1,8 +1,11 @@
 {% macro get_insert_overwrite_sql(source_relation, target_relation) %}
 
+    {%- set cols = config.get('partition_by', validator=validation.any[list, basestring]) -%}
+    {%- set insert = 'insert overwrite' if cols is not none else 'insert into' -%}
+
     {%- set dest_columns = adapter.get_columns_in_relation(target_relation) -%}
     {%- set dest_cols_csv = dest_columns | map(attribute='quoted') | join(', ') -%}
-    insert overwrite table {{ target_relation }}
+    {{ insert }} table {{ target_relation }}
     {{ partition_cols(label="partition") }}
     select {{dest_cols_csv}} from {{ source_relation.include(database=false, schema=false) }}