diff --git a/python-package/xgboost/dask.py b/python-package/xgboost/dask.py
index 8eb026283..fb0f7f0d9 100644
--- a/python-package/xgboost/dask.py
+++ b/python-package/xgboost/dask.py
@@ -347,12 +347,11 @@ class DaskDMatrix:
 def _get_worker_parts_ordered(meta_names, list_of_keys, list_of_parts, partition_order):
     # List of partitions like: [(x3, y3, w3, m3, ..), ..], order is not preserved.
     assert isinstance(list_of_parts, list)
-    list_of_parts_value = list_of_parts
 
     result = []
 
     for i, _ in enumerate(list_of_parts):
-        data = list_of_parts_value[i][0]
+        data = list_of_parts[i][0]
         labels = None
         weights = None
         base_margin = None
@@ -360,7 +359,7 @@ def _get_worker_parts_ordered(meta_names, list_of_keys, list_of_parts, partition
         label_upper_bound = None
         # Iterate through all possible meta info, brings small overhead as in xgboost
         # there are constant number of meta info available.
-        for j, blob in enumerate(list_of_parts_value[i][1:]):
+        for j, blob in enumerate(list_of_parts[i][1:]):
             if meta_names[j] == 'labels':
                 labels = blob
             elif meta_names[j] == 'weights':
@@ -701,7 +700,8 @@ async def _train_async(client,
                           dtrain.create_fn_args(workers[i]),
                           id(dtrain),
                           evals_per_worker,
-                          pure=False)
+                          pure=False,
+                          workers=[worker_addr])
         futures.append(f)
 
     results = await client.gather(futures)