chore(examples): Use QuantileDMatrix for histogram tree method in XGBoost example (#3376)

Replace DMatrix with QuantileDMatrix in distributed XGBoost training
example when using histogram tree method. This reduces memory usage
and aligns with XGBoost best practices for distributed workloads.

Fixes #3300

Signed-off-by: Suyash Nalawade <sunalawa@redhat.com>

Author: sunalawa

examples/xgboost/distributed-training/xgboost-distributed.ipynb

@@ -102,14 +102,15 @@
     "            X, y, test_size=0.2, random_state=42,\n",
     "        )\n",
     "\n",
-    "        # NOTE: DMatrix construction MUST be inside the communicator context\n",
+    "        # NOTE: QuantileDMatrix construction MUST be inside the communicator context\n",
     "        # because it involves cross-worker synchronization for quantization.\n",
-    "        dtrain = xgb.DMatrix(X_train, label=y_train)\n",
-    "        dvalid = xgb.DMatrix(X_valid, label=y_valid)\n",
+    "        dtrain = xgb.QuantileDMatrix(X_train, label=y_train)\n",
+    "        dvalid = xgb.QuantileDMatrix(X_valid, label=y_valid, ref=dtrain)\n",
     "\n",
     "        # Training parameters (for GPU training, add device=\"cuda\").\n",
     "        params = {\n",
     "            \"objective\": \"binary:logistic\",\n",
+    "            \"tree_method\": \"hist\",\n",
     "            \"max_depth\": 6,\n",
     "            \"eta\": 0.1,\n",
     "            \"eval_metric\": \"logloss\",\n",