steveahnahn opened a new pull request, #60352:
URL: https://github.com/apache/airflow/pull/60352
## Problem
The previous implementation fetched all task instances from the database and
then filtered by `map_index` in Python. For DAGs with mapped tasks containing
large map indices, this caused unnecessary database load and memory usage.
## Solution
Push the map_index filter to the SQL query, allowing the database to handle
filtering efficiently:
- Move `map_index` filtering from Python to SQL in
`get_task_instance_states` and `get_task_instance_count` endpoints
- Add `map_index` parameter to `_get_group_tasks` helper function to
filter at the database level
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