revert log_batch

src/bentoml/_internal/monitoring/api.py

@@ -280,42 +280,13 @@ def log_batch(
         """
         Log a batch of data. The data will be logged as a single column.
         """
-        if name in self.PRESERVED_COLUMNS:
-            raise ValueError(
-                f"Column name {name} is preserved. Please use a different name."
-            )
-
-        assert role in BENTOML_MONITOR_ROLES, f"Invalid role {role}"
-        assert data_type in BENTOML_MONITOR_TYPES, f"Invalid data type {data_type}"
-
-        if self._is_first_record:
-            if name not in self._column_meta:
-                self._column_meta[name] = {
-                    "name": name,
-                    "role": role,
-                    "type": data_type,
-                }
-            else:
-                logger.warning(
-                    "Column %s already exists. Will use the existing column meta.",
-                    name,
-                )
-
         try:
             for data in data_batch:
-                if self._is_first_column:
-                    # universal columns
-                    self._columns[self.COLUMN_TIME].append(
-                        datetime.datetime.now().isoformat()
-                    )
-                    self._columns[self.COLUMN_RID].append(trace_context.request_id)
-                self._columns[name].append(data)
+                self.log(data, name, role, data_type)
         except TypeError:
             raise ValueError(
                 "data_batch is not iterable. Please use log() to log a single data."
             ) from None
-        if self._is_first_column:
-            self._is_first_column = False
 
     def log_table(
         self,