Advises the kernel to not cache log files generated by Airflow (#18054)

* Advises the kernel to not cache log files generated by Airflow

Extends the standard python logging.FileHandler with advise to the
Kernel to not cache the file in PageCache when it is written. While
there is nothing wrong with such cache (it will be cleaned when memory
is needed), it causes ever-growing memory usage when scheduler is
running as it keeps on writing new log files and the files are not
rotated later on. This might lead to confusion for our users, who are
monitoring memory usage of Scheduler - without realising that it is
harmless and expected in this case.

Adding the advice to Kernel might help with not generating the cache
memory growth in the first place.

Closes: #14924

airflow/utils/cli.py

@@ -34,6 +34,7 @@
 from airflow import settings
 from airflow.exceptions import AirflowException
 from airflow.utils import cli_action_loggers
+from airflow.utils.log.non_caching_file_handler import NonCachingFileHandler
 from airflow.utils.platform import getuser, is_terminal_support_colors
 from airflow.utils.session import provide_session
 
@@ -244,7 +245,7 @@ def setup_locations(process, pid=None, stdout=None, stderr=None, log=None):
 def setup_logging(filename):
     """Creates log file handler for daemon process"""
     root = logging.getLogger()
-    handler = logging.FileHandler(filename)
+    handler = NonCachingFileHandler(filename)
     formatter = logging.Formatter(settings.SIMPLE_LOG_FORMAT)
     handler.setFormatter(formatter)
     root.addHandler(handler)

airflow/utils/log/file_processor_handler.py

@@ -23,6 +23,7 @@
 
 from airflow import settings
 from airflow.utils.helpers import parse_template_string
+from airflow.utils.log.non_caching_file_handler import NonCachingFileHandler
 
 
 class FileProcessorHandler(logging.Handler):
@@ -54,7 +55,7 @@ def set_context(self, filename):
         :param filename: filename in which the dag is located
         """
         local_loc = self._init_file(filename)
-        self.handler = logging.FileHandler(local_loc)
+        self.handler = NonCachingFileHandler(local_loc)
         self.handler.setFormatter(self.formatter)
         self.handler.setLevel(self.level)
 

airflow/utils/log/file_task_handler.py

@@ -26,6 +26,7 @@
 
 from airflow.configuration import AirflowConfigException, conf
 from airflow.utils.helpers import parse_template_string
+from airflow.utils.log.non_caching_file_handler import NonCachingFileHandler
 
 if TYPE_CHECKING:
     from airflow.models import TaskInstance
@@ -55,7 +56,7 @@ def set_context(self, ti: "TaskInstance"):
         :param ti: task instance object
         """
         local_loc = self._init_file(ti)
-        self.handler = logging.FileHandler(local_loc, encoding='utf-8')
+        self.handler = NonCachingFileHandler(local_loc, encoding='utf-8')
         if self.formatter:
             self.handler.setFormatter(self.formatter)
         self.handler.setLevel(self.level)

airflow/utils/log/non_caching_file_handler.py

@@ -0,0 +1,46 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import logging
+import os
+
+
+class NonCachingFileHandler(logging.FileHandler):
+    """
+    This is an extension of the python FileHandler that advises the Kernel to not cache the file
+    in PageCache when it is written. While there is nothing wrong with such cache (it will be cleaned
+    when memory is needed), it causes ever-growing memory usage when scheduler is running as it keeps
+    on writing new log files and the files are not rotated later on. This might lead to confusion
+    for our users, who are monitoring memory usage of Scheduler - without realising that it is
+    harmless and expected in this case.
+
+    See https://github.com/apache/airflow/issues/14924
+
+    Adding the advice to Kernel might help with not generating the cache memory growth in the first place.
+    """
+
+    def _open(self):
+        wrapper = super()._open()
+        try:
+            fd = wrapper.fileno()
+            os.posix_fadvise(fd, 0, 0, os.POSIX_FADV_DONTNEED)
+        except Exception:
+            # in case either file descriptor cannot be retrieved or fadvise is not available
+            # we should simply return the wrapper retrieved by FileHandler's open method
+            # the advise to the kernel is just an advise and if we cannot give it, we won't
+            pass
+        return wrapper