Schema Deletion Guidelines¶
The Schema Registry API supports deleting a specific schema version or all versions of a subject. On a soft delete, the API only deletes the version and the underlying schema ID would still be available for any lookup.
Soft delete a schema¶
You can perform a soft delete on all schema versions registered under a subject or on a specific version of a subject.
A soft delete removes the specified schema versions but does not free up space in the registry because the schema metadata, including schema IDs, is retained and schema IDs are not reusable.
# Deletes all schema versions registered under the subject "Kafka-value" curl -X DELETE http://localhost:8081/subjects/Kafka-value  # Deletes version 1 of the schema registered under subject "Kafka-value" curl -X DELETE http://localhost:8081/subjects/Kafka-value/versions/1 1 # Deletes the most recently registered schema under subject "Kafka-value" curl -X DELETE http://localhost:8081/subjects/Kafka-value/versions/latest 1
Hard delete a schema¶
Both Confluent Platform and Confluent Cloud Schema Registry support hard delete of a schema with the use of the query string,
?permanent=true. A hard delete removes all metadata, including schema IDs.
You can perform a hard delete on all schema versions registered under a subject or on a specific version of a subject.
To accomplish a hard delete of a schema (all versions or a specific version), use this two-step process. You must first soft delete the schema, then hard-delete it.
Perform a soft delete of all versions of the schema.
curl -X DELETE -u <schema-registry-api-key>:<schema-registry-api-secret> <schema-registry-url>/subjects/my-existing-subject
Perform a hard delete of all versions of the schema by appending
?permanent=trueto the command.
curl -X DELETE -u <schema-registry-api-key>:<schema-registry-api-secret> <schema-registry-url>/subjects/<my-existing-subject>?permanent=true
The following commands hard-delete all versions of the schema registered under the subject “Kafka-value”:
curl -X DELETE -u <schema-registry-api-key>:<schema-registry-api-secret> <schema-registry-url>/subjects/Kafka-value curl -X DELETE -u <schema-registry-api-key>:<schema-registry-api-secret> <schema-registry-url>/subjects/Kafka-value?permanent=true
To hard-delete version 1 of the schema registered under the subject Kafka-value:
curl -X DELETE -u <schema-registry-api-key>:<schema-registry-api-secret> <schema-registry-url>/subjects/Kafka-value/versions/1 curl -X DELETE -u <schema-registry-api-key>:<schema-registry-api-secret> <schema-registry-url>/subjects/Kafka-value/versions/1?permanent=true
For the version-specific delete, a hard delete requires a version number as input; not just
version:latest, which results in a soft delete only.
Recovering a soft-deleted schema¶
You can recover a soft-deleted schema using the Schema Registry
GET /subjects and
POST /subjects APIs as follows:
- Retrieve the schema with
GET /subjects?deleted=true, as described in GET /subjects API description. (A usage example is shown in List all subjects.)
- Use POST/subjects/(string: subject)/versions to re-register the schema.
Workaround to virtually recover a hard-deleted schema¶
In some cases, a schema is hard deleted but later found to still be required to read messages. If the you have the schema definition, you can re-register it at its previous offset to allow the consumers to keep functioning.
If this is the case, you can essentially “restore” the schema by recreating it with the same definition, putting the schema into IMPORT mode, and manually registering it at a specified ID on a Schema Registry. This assumes that the schema ID is not already taken, and is useful in recovery operations when a schema was deleted but is backed up on another cluster.
To learn how to “restore” a hard-deleted schema using this method, see Migrate an Individual Schema to an Already Populated Schema Registry (subject-level migration).
Guidelines for using these APIs¶
The above APIs are primarily intended to be used be in a development environment where it’s common to go through iterations before finalizing a schema. While it’s not recommended to be used in a production environment, there are few scenarios where these APIs can be used in production, but with utmost care.
- A new schema to be registered has compatibility issues with one of the existing schema versions.
- An old version of the schema needs to be registered again for the same subject.
- The schemas are used only in real-time streaming systems and the older version(s) are absolutely no longer required.
- A topic needs to be recycled.
It is also important to note that any registered compatibility settings for the subject would also be deleted while using Delete Subject or when you delete the only available schema version.
Looking under the hood at schema deletion, versioning, and compatibility¶
In reality, deleting a schema removes only the versioned instance(s) of the schema. The actual schema (with the hashed ID) does not go away. The canonical MD5 hash of the schema still exists in the system. This is why you can perform a lookup on a deleted schema in the rest API.
If, on a subject that has three versions, you delete the third one but register again the same schema it will be registered under version 3 and the associated schema will have the same ID as before, because the hash matched the existing one.
When the Avro serializer serializes Avro data, it stores the ID (not the version, which is specific to the subject). If the version (in a subject) is deleted, the schema and its ID remain in Schema Registry so that the data and can still be deserialized using Schema Registry
This has implications for versioning and compatibility. Suppose, for a given subject, you have two schemas:
- Schema ID: 23, version 1 with fields (a,b)
- Schema ID: 45, version 2 with fields (a,b,c)
If you delete version 2, version 1 becomes the latest version.
If the compatibility level is BACKWARD, the next schema that is registered to the subject need only be backward compatible with version 1, not version 2.