Canal Format
Changelog-Data-Capture Format Format: Serialization Schema Format: Deserialization Schema
Canal is a CDC (Changelog Data Capture) tool that can stream changes in real-time from MySQL into other systems. Canal provides a unified format schema for changelog and supports to serialize messages using JSON and protobuf (protobuf is the default format for Canal).
SeaTunnel supports to interpret Canal JSON messages as INSERT/UPDATE/DELETE messages into seatunnel system. This is useful in many cases to leverage this feature, such as
synchronizing incremental data from databases to other systems
auditing logs
real-time materialized views on databases
temporal join changing history of a database table and so on.
SeaTunnel also supports to encode the INSERT/UPDATE/DELETE messages in SeaTunnel as Canal JSON messages, and emit to storage like Kafka. However, currently SeaTunnel can’t combine UPDATE_BEFORE and UPDATE_AFTER into a single UPDATE message. Therefore, SeaTunnel encodes UPDATE_BEFORE and UPDATE_AFTER as DELETE and INSERT Canal messages.
Format Options
option | default | required | Description |
---|---|---|---|
format | (none) | yes | Specify what format to use, here should be 'canal_json'. |
canal_json.ignore-parse-errors | false | no | Skip fields and rows with parse errors instead of failing. Fields are set to null in case of errors. |
canal_json.database.include | (none) | no | An optional regular expression to only read the specific databases changelog rows by regular matching the "database" meta field in the Canal record. The pattern string is compatible with Java's Pattern. |
canal_json.table.include | (none) | no | An optional regular expression to only read the specific tables changelog rows by regular matching the "table" meta field in the Canal record. The pattern string is compatible with Java's Pattern. |
How to use Canal format
Kafka uses example​
Canal provides a unified format for changelog, here is a simple example for an update operation captured from a MySQL products table:
{
"data": [
{
"id": "111",
"name": "scooter",
"description": "Big 2-wheel scooter",
"weight": "5.18"
}
],
"database": "inventory",
"es": 1589373560000,
"id": 9,
"isDdl": false,
"mysqlType": {
"id": "INTEGER",
"name": "VARCHAR(255)",
"description": "VARCHAR(512)",
"weight": "FLOAT"
},
"old": [
{
"weight": "5.15"
}
],
"pkNames": [
"id"
],
"sql": "",
"sqlType": {
"id": 4,
"name": 12,
"description": 12,
"weight": 7
},
"table": "products",
"ts": 1589373560798,
"type": "UPDATE"
}
Note: please refer to Canal documentation about the meaning of each fields.
The MySQL products table has 4 columns (id, name, description and weight). The above JSON message is an update change event on the products table where the weight value of the row with id = 111 is changed from 5.18 to 5.15. Assuming the messages have been synchronized to Kafka topic products_binlog, then we can use the following SeaTunnel to consume this topic and interpret the change events.
env {
execution.parallelism = 1
job.mode = "BATCH"
}
source {
Kafka {
bootstrap.servers = "kafkaCluster:9092"
topic = "products_binlog"
result_table_name = "kafka_name"
start_mode = earliest
schema = {
fields {
id = "int"
name = "string"
description = "string"
weight = "string"
}
},
format = canal_json
}
}
transform {
}
sink {
Kafka {
bootstrap.servers = "localhost:9092"
topic = "consume-binlog"
format = canal_json
}
}