Remove reference to undead tasks from documentation (apache#43536)

---------

Co-authored-by: Ryan Hatter <25823361+RNHTTR@users.noreply.github.com>

Author: karenbraganz

airflow/jobs/scheduler_job_runner.py

@@ -2017,14 +2017,14 @@ def _purge_zombies(self, zombies: list[tuple[TI, str]], *, session: Session) ->
                         f"Task did not emit heartbeat within time limit ({self._zombie_threshold_secs} "
                         "seconds) and will be terminated. "
                         "See https://airflow.apache.org/docs/apache-airflow/"
-                        "stable/core-concepts/tasks.html#zombie-undead-tasks"
+                        "stable/core-concepts/tasks.html#zombie-tasks"
                     ),
                 )
             )
             self.log.error(
                 "Detected zombie job: %s "
                 "(See https://airflow.apache.org/docs/apache-airflow/"
-                "stable/core-concepts/tasks.html#zombie-undead-tasks)",
+                "stable/core-concepts/tasks.html#zombie-tasks)",
                 request,
             )
             self.job.executor.send_callback(request)

docs/apache-airflow/core-concepts/tasks.rst

@@ -167,55 +167,20 @@ These can be useful if your code has extra knowledge about its environment and w
 
 .. _concepts:zombies:
 
-Zombie/Undead Tasks
--------------------
+Zombie Tasks
+------------
 
-No system runs perfectly, and task instances are expected to die once in a while. Airflow detects two kinds of task/process mismatch:
+No system runs perfectly, and task instances are expected to die once in a while.
 
-* *Zombie tasks* are ``TaskInstances`` stuck in a ``running`` state despite their associated jobs being inactive
-  (e.g. their process did not send a recent heartbeat as it got killed, or the machine died). Airflow will find these
-  periodically, clean them up, and either fail or retry the task depending on its settings. Tasks can become zombies for
-  many reasons, including:
+*Zombie tasks* are ``TaskInstances`` stuck in a ``running`` state despite their associated jobs being inactive
+(e.g. their process did not send a recent heartbeat as it got killed, or the machine died). Airflow will find these
+periodically, clean them up, and either fail or retry the task depending on its settings. Tasks can become zombies for
+many reasons, including:
 
-    * The Airflow worker ran out of memory and was OOMKilled.
-    * The Airflow worker failed its liveness probe, so the system (for example, Kubernetes) restarted the worker.
-    * The system (for example, Kubernetes) scaled down and moved an Airflow worker from one node to another.
+* The Airflow worker ran out of memory and was OOMKilled.
+* The Airflow worker failed its liveness probe, so the system (for example, Kubernetes) restarted the worker.
+* The system (for example, Kubernetes) scaled down and moved an Airflow worker from one node to another.
 
-* *Undead tasks* are tasks that are *not* supposed to be running but are, often caused when you manually edit Task
-  Instances via the UI. Airflow will find them periodically and terminate them.
-
-
-Below is the code snippet from the Airflow scheduler that runs periodically to detect zombie/undead tasks.
-
-.. exampleinclude:: /../../airflow/jobs/scheduler_job_runner.py
-    :language: python
-    :start-after: [START find_and_purge_zombies]
-    :end-before: [END find_and_purge_zombies]
-
-
-The explanation of the criteria used in the above snippet to detect zombie tasks is as below:
-
-1. **Task Instance State**
-
-    Only task instances in the RUNNING state are considered potential zombies.
-
-2. **Job State and Heartbeat Check**
-
-    Zombie tasks are identified if the associated job is not in the RUNNING state or if the latest heartbeat of the job is
-    earlier than the calculated time threshold (limit_dttm). The heartbeat is a mechanism to indicate that a task or job is
-    still alive and running.
-
-3. **Job Type**
-
-    The job associated with the task must be of type ``LocalTaskJob``.
-
-4. **Queued by Job ID**
-
-    Only tasks queued by the same job that is currently being processed are considered.
-
-These conditions collectively help identify running tasks that may be zombies based on their state, associated job
-state, heartbeat status, job type, and the specific job that queued them. If a task meets these criteria, it is
-considered a potential zombie, and further actions, such as logging and sending a callback request, are taken.
 
 Reproducing zombie tasks locally
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

docs/apache-airflow/static/redirects.js

@@ -0,0 +1,28 @@
+/*!
+ * 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.
+ */
+
+document.addEventListener("DOMContentLoaded", function () {
+    const redirects = {
+        "zombie-undead-tasks": "zombie-tasks",
+    };
+    const fragment = window.location.hash.substring(1);
+    if (redirects[fragment]) {
+        window.location.hash = redirects[fragment];
+    }
+});

docs/conf.py

@@ -363,6 +363,7 @@ def _get_rst_filepath_from_path(filepath: pathlib.Path):
         "administration-and-deployment/logging-monitoring/advanced-logging-configuration.html",
         "howto/docker-compose/index.html",
     ]
+    html_js_files.append("redirects.js")
 if PACKAGE_NAME.startswith("apache-airflow-providers"):
     manual_substitutions_in_generated_html = ["example-dags.html", "operators.html", "index.html"]
 if PACKAGE_NAME == "docker-stack":