MaxWell Format
Last updated
Last updated
is a CDC (Changelog Data Capture) tool that can stream changes in real-time from MySQL into Kafka, Kinesis and other streaming connectors. Maxwell provides a unified format schema for changelog and supports to serialize messages using JSON.
Nexus supports to interpret MaxWell JSON messages as INSERT/UPDATE/DELETE messages into Nexus system. This is useful in many cases to leverage this feature, such as
Nexus also supports to encode the INSERT/UPDATE/DELETE messages in Nexus as MaxWell JSON messages, and emit to storage like Kafka. However, currently Nexus can’t combine UPDATE_BEFORE and UPDATE_AFTER into a single UPDATE message. Therefore, Nexus encodes UPDATE_BEFORE and UPDATE_AFTER as DELETE and INSERT MaxWell messages.
format
(none)
yes
Specify what format to use, here should be 'maxwell_json'.
maxwell_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.
maxwell_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 MaxWell record. The pattern string is compatible with Java's Pattern.
maxwell_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 MaxWell record. The pattern string is compatible with Java's Pattern.
MaxWell provides a unified format for changelog, here is a simple example for an update operation captured from a MySQL products table:
Note: please refer to MaxWell 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 Nexus to consume this topic and interpret the change events.