[jira] [Created] (FLINK-20999) Confluent Avro Format should document how to serialize kafka keys

["Svend Vanderveken (Jira)" <ji...@apache.org>]

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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