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Make the scheduler Dag cache size and TTL configurable - #71816
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A fixed 512-entry cache cannot fit every deployment: larger active working sets churn while memory-constrained schedulers may need a lower cap. Exposing size and TTL controls lets operators trade memory for refetch and deserialization cost while preserving the current defaults.
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Backport successfully created: v3-4-testNote: As of Merging PRs targeted for Airflow 3.X In matter of doubt please ask in #release-management Slack channel.
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…71816) (#75087) * Make the scheduler Dag cache size and TTL configurable A fixed 512-entry cache cannot fit every deployment: larger active working sets churn while memory-constrained schedulers may need a lower cap. Exposing size and TTL controls lets operators trade memory for refetch and deserialization cost while preserving the current defaults. * Remove redundant scheduler Dag cache config fallbacks (cherry picked from commit d01d351) Co-authored-by: Jason(Zhe-You) Liu <68415893+jason810496@users.noreply.github.com>
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…71816) (#75087) * Make the scheduler Dag cache size and TTL configurable A fixed 512-entry cache cannot fit every deployment: larger active working sets churn while memory-constrained schedulers may need a lower cap. Exposing size and TTL controls lets operators trade memory for refetch and deserialization cost while preserving the current defaults. * Remove redundant scheduler Dag cache config fallbacks (cherry picked from commit d01d351) Co-authored-by: Jason(Zhe-You) Liu <68415893+jason810496@users.noreply.github.com>
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feat/dagbag-cache-metric-namespace...feat/scheduler-dag-cache-configWhy
The scheduler's cache bound landed in #71704 as a fixed constant. Deployments whose active Dag-version working set exceeds that limit cannot raise it, while memory-constrained deployments cannot lower it or choose time-based eviction.
How
The API server and scheduler read and validate their size and TTL pairs through component-specific helpers. Each component constructs
CachedDBDagBagfor every configuration. When both values are 0, the configured cache uses a plain unbounded dict and performs no eviction.What
[scheduler] dag_cache_size, defaulting to the existing LRU limit of 512 versions.[scheduler] dag_cache_ttl, defaulting to 0 with no time-based eviction.Was generative AI tooling used to co-author this PR?