fix: optimize migration 0094 upgrade to use SQL instead of Python deserialization#63628
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YoannAbriel wants to merge 1 commit intoapache:mainfrom
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fix: optimize migration 0094 upgrade to use SQL instead of Python deserialization#63628YoannAbriel wants to merge 1 commit intoapache:mainfrom
YoannAbriel wants to merge 1 commit intoapache:mainfrom
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…erialization Replace row-by-row Python serde deserialization with pure SQL JSON manipulation for PostgreSQL (writable CTE with gen_random_uuid() and jsonb operations). For MySQL/SQLite, use batched approach with Python UUID generation but direct JSON dict access instead of importing and invoking serde.deserialize(). This eliminates the Python object instantiation bottleneck that caused ~33 minute migration times for 10M deadline rows. Also removes runtime module imports (airflow.serialization.serde, airflow.models.callback, airflow.models.deadline) from the upgrade path, hardcoding the constant values instead. This follows the migration best practice of avoiding ORM/runtime imports. Closes: apache#63532
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Migration 0094 (
replace_deadline_inline_callback_with_fkey) processes every deadline row through Python'sserde.deserialize()during upgrade, instantiating Python objects for each row. At scale (10M rows), this takes ~33 minutes.The callback JSON format prior to 3.2.0 is predictable (always
AsyncCallbackwith a fixed serde wrapper structure), so the transformation can be done entirely in SQL.PostgreSQL: single writable CTE with
gen_random_uuid()andjsonb_build_object()— handles INSERT intocallbackand UPDATE ofdeadlinein one statement. No Python loop, no batching.MySQL/SQLite: batched approach with Python UUID generation but direct JSON dict access instead of
serde.deserialize()round-trip.Also removes runtime module imports (
airflow.serialization.serde,airflow.models.callback,airflow.models.deadline) from the upgrade path, hardcoding constant values instead.Closes: #63532
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