Avro Format

Format: Serialization Schema Format: Deserialization Schema

The Apache Avro format allows to read and write Avro data based on an Avro schema. Currently, the Avro schema is derived from table schema.

Dependencies

In order to setup the Avro format, the following table provides dependency information for both projects using a build automation tool (such as Maven or SBT) and SQL Client with SQL JAR bundles.

You can download flink-avro from Download, and requires additional Hadoop dependency for cluster execution.

<dependency>
  <groupId>org.apache.flink</groupId>
  <artifactId>flink-avro</artifactId>
  <version>1.11.0</version>
</dependency>

How to create a table with Avro format

Here is an example to create a table using Kafka connector and Avro format.

CREATE TABLE user_behavior (
  user_id BIGINT,
  item_id BIGINT,
  category_id BIGINT,
  behavior STRING,
  ts TIMESTAMP(3)
) WITH (
 'connector' = 'kafka',
 'topic' = 'user_behavior',
 'properties.bootstrap.servers' = 'localhost:9092',
 'properties.group.id' = 'testGroup',
 'format' = 'avro'
)

Format Options

Data Type Mapping

Currently, the Avro schema is always derived from table schema. Explicitly defining an Avro schema is not supported yet. So the following table lists the type mapping from Flink type to Avro type.

In addition to the types listed above, Flink supports reading/writing nullable types. Flink maps nullable types to Avro union(something, null), where something is the Avro type converted from Flink type.

You can refer to Avro Specification for more information about Avro types.