Ogg Format #

Changelog-Data-Capture Format Format: Serialization Schema Format: Deserialization Schema

Oracle GoldenGate (a.k.a ogg) is a managed service providing a real-time data mesh platform, which uses replication to keep data highly available, and enabling real-time analysis. Customers can design, execute, and monitor their data replication and stream data processing solutions without the need to allocate or manage compute environments. Ogg provides a format schema for changelog and supports to serialize messages using JSON.

Flink supports to interpret Ogg JSON as INSERT/UPDATE/DELETE messages into Flink SQL 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.

Flink also supports to encode the INSERT/UPDATE/DELETE messages in Flink SQL as Ogg JSON, and emit to external systems like Kafka. However, currently Flink can’t combine UPDATE_BEFORE and UPDATE_AFTER into a single UPDATE message. Therefore, Flink encodes UPDATE_BEFORE and UPDATE_AFTER as DELETE and INSERT Ogg messages.

Dependencies #

Ogg Json #

In order to use the Ogg 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.

<dependency>
  <groupId>org.apache.flink</groupId>
  <artifactId>flink-json</artifactId>
  <version>1.20.0</version>
</dependency>

Note: please refer to Ogg Kafka Handler documentation about how to set up an Ogg Kafka handler to synchronize changelog to Kafka topics.

How to use Ogg format #

Ogg provides a unified format for changelog, here is a simple example for an update operation captured from an Oracle PRODUCTS table in JSON format:

{
  "before": {
    "id": 111,
    "name": "scooter",
    "description": "Big 2-wheel scooter",
    "weight": 5.18
  },
  "after": {
    "id": 111,
    "name": "scooter",
    "description": "Big 2-wheel scooter",
    "weight": 5.15
  },
  "op_type": "U",
  "op_ts": "2020-05-13 15:40:06.000000",
  "current_ts": "2020-05-13 15:40:07.000000",
  "primary_keys": [
    "id"
  ],
  "pos": "00000000000000000000143",
  "table": "PRODUCTS"
}

Note: please refer to Debezium documentation about the meaning of each field.

The Oracle 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 this messages is synchronized to Kafka topic products_ogg, then we can use the following DDL to consume this topic and interpret the change events.

CREATE TABLE topic_products (
  -- schema is totally the same to the Oracle "products" table
  id BIGINT,
  name STRING,
  description STRING,
  weight DECIMAL(10, 2)
) WITH (
  'connector' = 'kafka',
  'topic' = 'products_ogg',
  'properties.bootstrap.servers' = 'localhost:9092',
  'properties.group.id' = 'testGroup',
  'format' = 'ogg-json'
)

After registering the topic as a Flink table, then you can consume the Ogg messages as a changelog source.

-- a real-time materialized view on the Oracle "PRODUCTS"
-- which calculate the latest average of weight for the same products
SELECT name, AVG(weight)
FROM topic_products
GROUP BY name;

-- synchronize all the data and incremental changes of Oracle "PRODUCTS" table to
-- Elasticsearch "products" index for future searching
INSERT INTO elasticsearch_products
SELECT *
FROM topic_products;

Available Metadata #

The following format metadata can be exposed as read-only (VIRTUAL) columns in a table definition.

Attention Format metadata fields are only available if the corresponding connector forwards format metadata. Currently, only the Kafka connector is able to expose metadata fields for its value format.

The following example shows how to access Ogg metadata fields in Kafka:

CREATE TABLE KafkaTable (
  origin_ts TIMESTAMP(3) METADATA FROM 'value.ingestion-timestamp' VIRTUAL,
  event_time TIMESTAMP(3) METADATA FROM 'value.event-timestamp' VIRTUAL,
  origin_table STRING METADATA FROM 'value.table' VIRTUAL,
  primary_keys ARRAY<STRING> METADATA FROM 'value.primary-keys' VIRTUAL,
  user_id BIGINT,
  item_id BIGINT,
  behavior STRING
) WITH (
  'connector' = 'kafka',
  'topic' = 'user_behavior',
  'properties.bootstrap.servers' = 'localhost:9092',
  'properties.group.id' = 'testGroup',
  'scan.startup.mode' = 'earliest-offset',
  'value.format' = 'ogg-json'
);

Format Options #

Data Type Mapping #

Currently, the Ogg format uses JSON format for serialization and deserialization. Please refer to JSON Format documentation for more details about the data type mapping.