1. Connectors
2. Table & SQL Connectors
3. Formats
4. JSON

JSON Format

Format: Serialization Schema Format: Deserialization Schema

• Dependencies
• How to create a table with JSON format
• Format Options
• Data Type Mapping

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

Dependencies

In order to setup the JSON 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.

How to create a table with JSON format

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

• SQL

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' = 'json',
 'json.fail-on-missing-field' = 'false',
 'json.ignore-parse-errors' = 'true'
)

Format Options

Data Type Mapping

Currently, the JSON schema is always derived from table schema. Explicitly defining an JSON schema is not supported yet.

Flink JSON format uses jackson databind API to parse and generate JSON string.

The following table lists the type mapping from Flink type to JSON type.