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Inferred schemas are materialized into the inferred_schemas table by our ops catalog. The table is keyed on the collection_name, which presents a problem when a collection is deleted and re-created. We can't tell whether the schema is from the prior version of the collection or the new one, and inferred schema updates from both versions will be merged into the same row.
The solution we'd like to implement is to thread through the "version id" of the collection as part of the inferred schemas, and make it part of the tables primary key. The version id is the build id at which the collection was created. It's a part of the collection journal names, like in the example acmeCo/foo/11223344aabbccdd/pivot=00. The desired outcome is for the inferred_schemas table to have collection_name = 'acmeCo/foo', version_id = '11223344aabbccdd'.
Publications will then only use the inferred schema matching the version_id for each collection in the draft.
The text was updated successfully, but these errors were encountered:
Inferred schemas are materialized into the
inferred_schemas
table by our ops catalog. The table is keyed on thecollection_name
, which presents a problem when a collection is deleted and re-created. We can't tell whether the schema is from the prior version of the collection or the new one, and inferred schema updates from both versions will be merged into the same row.The solution we'd like to implement is to thread through the "version id" of the collection as part of the inferred schemas, and make it part of the tables primary key. The version id is the build id at which the collection was created. It's a part of the collection journal names, like in the example
acmeCo/foo/11223344aabbccdd/pivot=00
. The desired outcome is for theinferred_schemas
table to havecollection_name = 'acmeCo/foo', version_id = '11223344aabbccdd'
.Publications will then only use the inferred schema matching the
version_id
for each collection in the draft.The text was updated successfully, but these errors were encountered: