diff --git a/datapipe/step/batch_transform.py b/datapipe/step/batch_transform.py
index 1db7d3e6..88b3e82b 100644
--- a/datapipe/step/batch_transform.py
+++ b/datapipe/step/batch_transform.py
@@ -207,8 +207,6 @@ def _get_filters(
         keys = set([key for keys in filters for key in keys])
         if not all(len(filter) == len(keys) for filter in filters):
             raise ValueError("Size of keys from filters must have same length")
-        if not all([key in self.transform_keys for key in keys]):
-            raise ValueError(f"Keys from filters must be in transform_keys={self.transform_keys}.")
         return filters
 
     def get_status(self, ds: DataStore) -> StepStatus:
diff --git a/tests/test_complex_pipeline.py b/tests/test_complex_pipeline.py
index 7e3321c2..f9dc079b 100644
--- a/tests/test_complex_pipeline.py
+++ b/tests/test_complex_pipeline.py
@@ -458,11 +458,10 @@ def gen_tbl(df):
     test_df__model = pd.DataFrame({
         "model_id": [0, 1, 2, 3, 4]
     })
-    
+
     def filters_images():
         return [{"image_id": i} for i in range(N // 2)]
 
-
     def make_prediction(
         df__image: pd.DataFrame,
         df__model: pd.DataFrame,
diff --git a/tests/test_core_steps2.py b/tests/test_core_steps2.py
index 604d8145..90237339 100644
--- a/tests/test_core_steps2.py
+++ b/tests/test_core_steps2.py
@@ -147,7 +147,7 @@ def test_batch_transform_with_filter_in_run_config(dbconn):
     assert_datatable_equal(tbl2, TEST_DF1_1.query("pipeline_id == 0"))
 
 
-def test_batch_transform_with_filter_not_in_transform_index(dbconn):
+def test_batch_transform_with_filter_in_run_config_not_in_transform_index(dbconn):
     ds = DataStore(dbconn, create_meta_table=True)
 
     tbl1 = ds.create_table(
@@ -176,6 +176,35 @@ def test_batch_transform_with_filter_not_in_transform_index(dbconn):
     assert_datatable_equal(tbl2, TEST_DF1_2.query("pipeline_id == 0")[["item_id", "a"]])
 
 
+def test_batch_transform_with_filter_not_in_transform_index(dbconn):
+    ds = DataStore(dbconn, create_meta_table=True)
+
+    tbl1 = ds.create_table(
+        "tbl1", table_store=TableStoreDB(dbconn, "tbl1_data", TEST_SCHEMA1, True)
+    )
+
+    tbl2 = ds.create_table(
+        "tbl2", table_store=TableStoreDB(dbconn, "tbl2_data", TEST_SCHEMA2, True)
+    )
+
+    tbl1.store_chunk(TEST_DF1_2, now=0)
+
+    step = BatchTransformStep(
+        ds=ds,
+        name="test",
+        func=lambda df: df[["item_id", "a"]],
+        input_dts=[ComputeInput(dt=tbl1, join_type="full")],
+        output_dts=[tbl2],
+        filters=[{"pipeline_id": 0}]
+    )
+
+    step.run_full(
+        ds,
+    )
+
+    assert_datatable_equal(tbl2, TEST_DF1_2.query("pipeline_id == 0")[["item_id", "a"]])
+
+
 def test_batch_transform_with_dt_on_input_and_output(dbconn):
     ds = DataStore(dbconn, create_meta_table=True)