feat(core): add per-mapper max_fan_out override for partition fan-out cap by Lee-W · Pull Request #67184 · apache/airflow

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W · 2026-05-19T13:48:33Z

Why

a per-mapper cap so each PartitionMapper instance can override the global [scheduler] partition_fanout_max_keys (implemented in #66030)
Lives on the mapper rather than the Dag because one Dag can bind several mappers
with very different fan-out profiles.

closes: #65760

What

Add max_fan_out: int | None = None to PartitionMapper base (SDK + core). Validator rejects 0, negatives, non-int, and bool. None → global; positive int → override.
Thread the kwarg through every subclass that overrides __init__, and through both serialization paths (per-class .serialize() and the encoders.py singledispatch overrides). Field emitted only when non-None — pre-change payloads round-trip byte-identical.
assets/manager.py: read the cap per target Dag, swap a cap_source fragment into the audit-log extra (max_fan_out=N vs. existing [scheduler] partition_fanout_max_keys=N).

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

… fan-out cap Add a `max_downstream_keys: int | None = None` parameter to both the SDK and core `PartitionMapper` base classes, threaded through every subclass constructor that defines its own `__init__`. The validator rejects 0, negatives, floats, and strings. Serialization is updated in two parallel paths: - Per-class `serialize()` / `deserialize()` methods (custom-mapper path). - `encoders.py` singledispatch overrides (built-in-mapper path). Both paths write `max_downstream_keys` only when non-None, following the existing convention of omitting default-valued fields from the serialized form. In `manager.py`, the single-shot `max_downstream_keys` read is deleted; the mapper object is retained after the `to_downstream` call so its `max_downstream_keys` attribute is readable at the boundary check. The effective cap is computed per target-Dag as either the mapper's own cap or the global `[scheduler] partition_mapper_max_downstream_keys`. The `Log.extra` string uses `max_downstream_keys=N` when the per-mapper cap trips, and keeps the existing `[scheduler] partition_mapper_max_downstream_keys=N` wording when the global trips.

The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

…validator Convert the SDK PartitionMapper base into an attrs class so the max_downstream_keys bound is enforced through a field validator instead of a hand-written __init__ check, matching the attrs convention used across the rest of airflow.sdk.definitions. Behavior is unchanged. Also add the SDK-side validator tests that previously only existed on the core mapper hierarchy.

Make the whole SDK partition-mapper hierarchy use one mechanism so the attrs base no longer needs a slots exception. RollupMapper, AllowedKeyMapper, the temporal mappers, and FanOutMapper become attrs classes; ChainMapper and ProductMapper keep their variadic __init__ via init=False. Public constructor signatures and behavior are unchanged.

… cap (apache#67184)

Lee-W changed the title ~~feat(AIP-76): window~~feat(core): add per-mapper max_fan_out override for partition fan-out capMay 19, 2026

vatsrahul1001 mentioned this pull request May 19, 2026
Refresh uv.lock and Edge OpenAPI spec after #67093 env upgrade #67188
Merged

jscheffl mentioned this pull request May 19, 2026
Status of testing Providers that were prepared on May 19, 2026 #67213
Closed

Lee-W force-pushed the partition-fanout-max-keys branch 14 times, most recently from d5d2ced to af057aeCompare May 28, 2026 10:11

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Comment threadairflow-core/src/airflow/assets/manager.py

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Lee-W removed the area:db-migrations PRs with DB migration label Jun 10, 2026

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bugraoz93 removed the backport-to-v3-2-test label Jun 10, 2026

Lee-W added 4 commits June 11, 2026 08:53

feat(core): log which cap was exceeded on partition fan-out overflow
5ff0fed
The scheduler error log for a partition fan-out overflow now carries a cap_source kwarg, so operators can tell whether the per-mapper max_downstream_keys override or the global scheduler cap was the limit that was hit.

Lee-W force-pushed the partition-fanout-max-keys branch from 9d28124 to 5f26df1Compare June 11, 2026 00:53

Lee-W merged commit b7247b1 into apache:mainJun 11, 2026
195 of 196 checks passed

Lee-W deleted the partition-fanout-max-keys branch June 11, 2026 02:26

github-project-automationBot moved this from In Review to Done in AIP-76 Asset Partitioning Jun 11, 2026

imrichardwu pushed a commit to imrichardwu/airflow that referenced this pull request Jun 16, 2026
feat(core): add per-mapper max_fan_out override for partition fan-out…
4e01472
… cap (apache#67184)

dingo4dev pushed a commit to dingo4dev/airflow that referenced this pull request Jun 16, 2026
feat(core): add per-mapper max_fan_out override for partition fan-out…
49ad9db
… cap (apache#67184)