Svend Vanderveken created FLINK-20999:
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Summary: Confluent Avro Format should document how to serialize
kafka keys
Key: FLINK-20999
URL: https://issues.apache.org/jira/browse/FLINK-20999
Project: Flink
Issue Type: Improvement
Components: Documentation
Affects Versions: 1.12.0
Reporter: Svend Vanderveken
The [Confluent Avro
Format|https://ci.apache.org/projects/flink/flink-docs-release-1.12/dev/table/connectors/formats/avro-confluent.html]
only shows example of how to serialize/deserialize Kafka values. Also,
parameter description is not always clear what is influencing the source and
the sink behaviour, IMHO.
This seems surprising especially in the context of a sink kafka connector since
keys are such an important concept in that case.
Adding examples of how to serialize/deserialize Kafka keys would add clarity.
While it can be argued that a connector format is independent from the
underlying storage, probably showing kafka-oriented examples in this case (i.e,
with a concept of "key" and "value") makes senses here since this connector is
very much thought with Kafka in mind.
I suggest to add this:
h3. writing to Kafka while keeping the keys in "raw" big endian format:
{code:java}
CREATE TABLE OUTPUT_TABLE (
user_id BIGINT,
item_id BIGINT,
category_id BIGINT,
behavior STRING
) WITH (
'connector' = 'kafka',
'topic' = 'user_behavior',
'properties.bootstrap.servers' = 'localhost:9092',
'key.format' = 'raw',
'key.raw.endianness' = 'big-endian',
'key.fields' = 'user_id',
'value.format' = 'avro-confluent',
'value.avro-confluent.schema-registry.url' = 'http://localhost:8081',
'value.avro-confluent.schema-registry.subject' = 'user_behavior'
)
{code}
h3. writing to Kafka while registering both the key and the value to the schema
registry
{code:java}
CREATE TABLE OUTPUT_TABLE (
user_id BIGINT,
item_id BIGINT,
category_id BIGINT,
behavior STRING
) WITH (
'connector' = 'kafka',
'topic' = 'user_behavior',
'properties.bootstrap.servers' = 'localhost:9092',
-- => this will register a {user_id: long} Avro type in the schema registry.
-- Watch out: schema evolution in the context of a Kafka key is almost never
backward nor
-- forward compatible in practice due to hash partitioning.
'key.avro-confluent.schema-registry.url' = 'http://localhost:8081',
'key.avro-confluent.schema-registry.subject' = 'user_behavior_key',
'key.format' = 'avro-confluent',
'key.fields' = 'user_id',
'value.format' = 'avro-confluent',
'value.avro-confluent.schema-registry.url' = 'http://localhost:8081',
'value.avro-confluent.schema-registry.subject' = 'user_behavior_value'
)
{code}
h3. reading form Kafka with both the key and value schema in the registry while
resolving field name clashes:
{code:java}
CREATE TABLE INPUT_TABLE (
-- user_id as read from the kafka key:
from_kafka_key_user_id BIGINT,
-- user_id, and other fields, as read from the kafka value-
user_id BIGINT,
item_id BIGINT,
category_id BIGINT,
behavior STRING
) WITH (
'connector' = 'kafka',
'topic' = 'user_behavior',
'properties.bootstrap.servers' = 'localhost:9092',
'key.format' = 'avro-confluent',
'key.avro-confluent.schema-registry.url' = 'http://localhost:8081',
'key.fields' = 'from_kafka_key_user_id',
-- Adds a column prefix when mapping the avro fields of the kafka key to
columns of this Table
-- to avoid clashes with avro fields of the value (both contain 'user_id' in
this example)
'key.fields-prefix' = 'from_kafka_key_',
'value.format' = 'avro-confluent',
-- cannot include key here since dealt with above
'value.fields-include' = 'EXCEPT_KEY',
'value.avro-confluent.schema-registry.url' = 'http://localhost:8081'
)
{code}
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