remove debug logging

Signed-off-by: Weichen Xu <weichen.xu@databricks.com>

python-package/xgboost/spark/core.py

@@ -684,16 +684,6 @@ def _fit(self, dataset):
                 num_workers,
             )
 
-        def log_partition_rows(df, msg):
-            def count_partition_rows(iter):
-                yield len(list(iter))
-
-            result = df.rdd.mapPartitions(count_partition_rows).collect()
-            get_logger(self.__class__.__name__).warning(
-                f"debug-repartition: {msg}: {str(list(result))}\n"
-            )
-
-        log_partition_rows(dataset, "before-repartition")
         if self._repartition_needed(dataset) or (
             self.isDefined(self.validationIndicatorCol)
             and self.getOrDefault(self.validationIndicatorCol)
@@ -706,7 +696,7 @@ def count_partition_rows(iter):
             # result unbalance. Directly using `.repartition(N)` might result in some
             # empty partitions.
             dataset = dataset.repartition(num_workers, rand(1))
-            log_partition_rows(dataset, "after-repartition")
+
         train_params = self._get_distributed_train_params(dataset)
         booster_params, train_call_kwargs_params = self._get_xgb_train_call_args(
             train_params