[Feature Request]: [Kafka/YAML] Turnkey Confluent Schema Registry Wire Format deserializer in ReadFromKafka

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Issue 类型
功能
描述清晰度
基本清楚
活跃度
活跃
技术栈
java, kafka, python, yaml
领域
data-engineering, stream-processing

调研方向

Start by reading the Python ReadFromKafka wrapper and the Java cross-language provider in standard_io.yaml, which the issue names as integration points. Check how those paths handle the existing raw bytes and JSON formats, then trace the Confluent wire format and Schema Registry requirements. Done means Avro and Protobuf records can be decoded from the schema ID header and exposed as Beam Schema Rows through the proposed YAML configuration.

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描述

Description

Consuming from Kafka topics serialized with Confluent Schema Registry (magic byte 0x00 + 4-byte schema ID) is a ubiquitous industry pattern.
Currently in Beam, consuming from Schema Registry requires writing custom Java deserializers or complex manual Python Avro decode steps. In Beam YAML, ReadFromKafka only natively supports raw bytes or JSON.

Proposed Architecture

Add first-class Schema Registry support directly in ReadFromKafka (both Python wrapper and Java cross-language provider in standard_io.yaml):

pipeline:
  transforms:
    - type: ReadFromKafka
      config:
        topic: orders
        bootstrap_servers: "kafka:9092"
        schema_registry: "http://schema-registry:8081"
        format: avro  # automatically resolves schema ID from wire format
Key Capabilities
  1. Wire Format Parsing: Parses Confluent wire format header (magic byte 0 + 4-byte Big-Endian schema ID).
  2. Schema Cache: Fetches and caches Avro/Protobuf schema definitions from Schema Registry by ID.
  3. Beam Schema Mapping: Automatically converts deserialized records to strongly-typed Beam Schema Row objects.
主要语言
Java
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  3. Fork 仓库，在一个分支上完成修改。
  4. 提交 Pull Request，并在描述里引用这个 Issue 编号。

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