JSON

JSON Format #

Format: Serialization Schema Format: Deserialization Schema

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

The JSON format supports append-only streams, unless you’re using a connector that explicitly support retract streams and/or upsert streams like the Upsert Kafka connector. If you need to write retract streams and/or upsert streams, we suggest you to look at CDC JSON formats like Debezium JSON and Canal JSON.

Dependencies #

In order to use the Json format the following dependencies are required for both projects using a build automation tool (such as Maven or SBT) and SQL Client with SQL JAR bundles.

Maven dependency SQL Client
Built-in

How to create a table with JSON format #

Here is an example to create a table using Kafka connector and JSON 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' = 'json',
 'json.fail-on-missing-field' = 'false',
 'json.ignore-parse-errors' = 'true'
)

Format Options #

Option Required Forwarded Default Type Description
format
 required no (none) String Specify what format to use, here should be 'json'.
json.fail-on-missing-field
 optional no false Boolean Whether to fail if a field is missing or not.
json.ignore-parse-errors
 optional no false Boolean Skip fields and rows with parse errors instead of failing. Fields are set to null in case of errors.
json.timestamp-format.standard
 optional yes 'SQL' String Specify the input and output timestamp format for TIMESTAMP and TIMESTAMP_LTZ type. Currently supported values are 'SQL' and 'ISO-8601':
  • Option 'SQL' will parse input TIMESTAMP values in "yyyy-MM-dd HH:mm:ss.s{precision}" format, e.g "2020-12-30 12:13:14.123", parse input TIMESTAMP_LTZ values in "yyyy-MM-dd HH:mm:ss.s{precision}'Z'" format, e.g "2020-12-30 12:13:14.123Z" and output timestamp in the same format.
  • Option 'ISO-8601'will parse input TIMESTAMP in "yyyy-MM-ddTHH:mm:ss.s{precision}" format, e.g "2020-12-30T12:13:14.123" parse input TIMESTAMP_LTZ in "yyyy-MM-ddTHH:mm:ss.s{precision}'Z'" format, e.g "2020-12-30T12:13:14.123Z" and output timestamp in the same format.
json.map-null-key.mode
 optional yes 'FAIL' String Specify the handling mode when serializing null keys for map data. Currently supported values are 'FAIL', 'DROP' and 'LITERAL':
  • Option 'FAIL' will throw exception when encountering map with null key.
  • Option 'DROP' will drop null key entries for map data.
  • Option 'LITERAL' will replace null key with string literal. The string literal is defined by json.map-null-key.literal option.
json.map-null-key.literal
 optional yes 'null' String Specify string literal to replace null key when 'json.map-null-key.mode' is LITERAL.
json.encode.decimal-as-plain-number
 optional yes false Boolean Encode all decimals as plain numbers instead of possible scientific notations. By default, decimals may be written using scientific notation. For example, 0.000000027 is encoded as 2.7E-8 by default, and will be written as 0.000000027 if set this option to true.

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.

Flink SQL type JSON type
CHAR / VARCHAR / STRING string
BOOLEAN boolean
BINARY / VARBINARY string with encoding: base64
DECIMAL number
TINYINT number
SMALLINT number
INT number
BIGINT number
FLOAT number
DOUBLE number
DATE string with format: date
TIME string with format: time
TIMESTAMP string with format: date-time
TIMESTAMP_WITH_LOCAL_TIME_ZONE string with format: date-time (with UTC time zone)
INTERVAL number
ARRAY array
MAP / MULTISET object
ROW object