diff --git a/python-package/xgboost/dask.py b/python-package/xgboost/dask.py
index 1de2e4773..8eb026283 100644
--- a/python-package/xgboost/dask.py
+++ b/python-package/xgboost/dask.py
@@ -627,7 +627,7 @@ def _get_workers_from_data(dtrain: DaskDMatrix, evals=()):
             assert len(e) == 2
             assert isinstance(e[0], DaskDMatrix) and isinstance(e[1], str)
             worker_map = set(e[0].worker_map.keys())
-            X_worker_map.union(worker_map)
+            X_worker_map = X_worker_map.union(worker_map)
     return X_worker_map
 
 
diff --git a/tests/python/test_with_dask.py b/tests/python/test_with_dask.py
index ca1da7042..ba697ab4d 100644
--- a/tests/python/test_with_dask.py
+++ b/tests/python/test_with_dask.py
@@ -776,6 +776,26 @@ class TestDaskCallbacks:
         dump = booster.get_dump(dump_format='json')
         assert len(dump) - booster.best_iteration == early_stopping_rounds + 1
 
+    def test_n_workers(self):
+        with LocalCluster(n_workers=2) as cluster:
+            with Client(cluster) as client:
+                workers = list(_get_client_workers(client).keys())
+                from sklearn.datasets import load_breast_cancer
+                X, y = load_breast_cancer(return_X_y=True)
+                dX = client.submit(da.from_array, X, workers=[workers[0]]).result()
+                dy = client.submit(da.from_array, y, workers=[workers[0]]).result()
+                train = xgb.dask.DaskDMatrix(client, dX, dy)
+
+                dX = dd.from_array(X)
+                dX = client.persist(dX, workers={dX: workers[1]})
+                dy = dd.from_array(y)
+                dy = client.persist(dy, workers={dy: workers[1]})
+                valid = xgb.dask.DaskDMatrix(client, dX, dy)
+
+                merged = xgb.dask._get_workers_from_data(train, evals=[(valid, 'Valid')])
+                assert len(merged) == 2
+
+
     def test_data_initialization(self):
         '''Assert each worker has the correct amount of data, and DMatrix initialization doesn't
         generate unnecessary copies of data.