diff --git a/airflow/models/taskinstance.py b/airflow/models/taskinstance.py
index c743d428ea8560..fec70cc3a501bf 100644
--- a/airflow/models/taskinstance.py
+++ b/airflow/models/taskinstance.py
@@ -24,6 +24,7 @@
 import pickle
 import signal
 import warnings
+from collections import defaultdict
 from datetime import datetime, timedelta
 from tempfile import NamedTemporaryFile
 from typing import IO, Any, Dict, Iterable, List, NamedTuple, Optional, Tuple, Union
@@ -146,6 +147,7 @@ def clear_task_instances(
     :param dag: DAG object
     """
     job_ids = []
+    task_id_by_key = defaultdict(lambda: defaultdict(lambda: defaultdict(set)))
     for ti in tis:
         if ti.state == State.RUNNING:
             if ti.job_id:
@@ -166,13 +168,36 @@ def clear_task_instances(
                 ti.max_tries = max(ti.max_tries, ti.prev_attempted_tries)
             ti.state = State.NONE
             session.merge(ti)
+
+        task_id_by_key[ti.dag_id][ti.execution_date][ti.try_number].add(ti.task_id)
+
+    if task_id_by_key:
         # Clear all reschedules related to the ti to clear
-        session.query(TR).filter(
-            TR.dag_id == ti.dag_id,
-            TR.task_id == ti.task_id,
-            TR.execution_date == ti.execution_date,
-            TR.try_number == ti.try_number,
-        ).delete()
+
+        # This is an optimization for the common case where all tis are for a small number
+        # of dag_id, execution_date and try_number. Use a nested dict of dag_id,
+        # execution_date, try_number and task_id to construct the where clause in a
+        # hierarchical manner. This speeds up the delete statement by more than 40x for
+        # large number of tis (50k+).
+        conditions = or_(
+            and_(
+                TR.dag_id == dag_id,
+                or_(
+                    and_(
+                        TR.execution_date == execution_date,
+                        or_(
+                            and_(TR.try_number == try_number, TR.task_id.in_(task_ids))
+                            for try_number, task_ids in task_tries.items()
+                        ),
+                    )
+                    for execution_date, task_tries in dates.items()
+                ),
+            )
+            for dag_id, dates in task_id_by_key.items()
+        )
+
+        delete_qry = TR.__table__.delete().where(conditions)
+        session.execute(delete_qry)
 
     if job_ids:
         from airflow.jobs.base_job import BaseJob
diff --git a/tests/models/test_cleartasks.py b/tests/models/test_cleartasks.py
index f54bacce339f47..1c5606e66acd84 100644
--- a/tests/models/test_cleartasks.py
+++ b/tests/models/test_cleartasks.py
@@ -20,8 +20,9 @@
 import unittest
 
 from airflow import settings
-from airflow.models import DAG, TaskInstance as TI, clear_task_instances
+from airflow.models import DAG, TaskInstance as TI, TaskReschedule, clear_task_instances
 from airflow.operators.dummy import DummyOperator
+from airflow.sensors.python import PythonSensor
 from airflow.utils.session import create_session
 from airflow.utils.state import State
 from airflow.utils.types import DagRunType
@@ -138,6 +139,50 @@ def test_clear_task_instances_without_dag(self):
         assert ti1.try_number == 2
         assert ti1.max_tries == 2
 
+    def test_clear_task_instances_with_task_reschedule(self):
+        """Test that TaskReschedules are deleted correctly when TaskInstances are cleared"""
+
+        with DAG(
+            'test_clear_task_instances_with_task_reschedule',
+            start_date=DEFAULT_DATE,
+            end_date=DEFAULT_DATE + datetime.timedelta(days=10),
+        ) as dag:
+            task0 = PythonSensor(task_id='0', python_callable=lambda: False, mode="reschedule")
+            task1 = PythonSensor(task_id='1', python_callable=lambda: False, mode="reschedule")
+
+        ti0 = TI(task=task0, execution_date=DEFAULT_DATE)
+        ti1 = TI(task=task1, execution_date=DEFAULT_DATE)
+
+        dag.create_dagrun(
+            execution_date=ti0.execution_date,
+            state=State.RUNNING,
+            run_type=DagRunType.SCHEDULED,
+        )
+
+        ti0.run()
+        ti1.run()
+
+        with create_session() as session:
+
+            def count_task_reschedule(task_id):
+                return (
+                    session.query(TaskReschedule)
+                    .filter(
+                        TaskReschedule.dag_id == dag.dag_id,
+                        TaskReschedule.task_id == task_id,
+                        TaskReschedule.execution_date == DEFAULT_DATE,
+                        TaskReschedule.try_number == 1,
+                    )
+                    .count()
+                )
+
+            assert count_task_reschedule(ti0.task_id) == 1
+            assert count_task_reschedule(ti1.task_id) == 1
+            qry = session.query(TI).filter(TI.dag_id == dag.dag_id, TI.task_id == ti0.task_id).all()
+            clear_task_instances(qry, session, dag=dag)
+            assert count_task_reschedule(ti0.task_id) == 0
+            assert count_task_reschedule(ti1.task_id) == 1
+
     def test_dag_clear(self):
         dag = DAG(
             'test_dag_clear', start_date=DEFAULT_DATE, end_date=DEFAULT_DATE + datetime.timedelta(days=10)