Oracle GoldenGate is a comprehensive software package for real-time data integration and replication in heterogeneous IT environments. Among its many capabilities, the handling of Oracle decimal types when delivering data to destinations such as Apache Kafka is crucial for ensuring the accuracy and integrity of data during transfer. Handling decimal types effectively in GoldenGate when using the Kafka or Kafka Connect handler requires an understanding of Oracle data types, GoldenGate configuration, and Kafka data serialization.

Understanding Oracle Decimal Types

Oracle contains several numeric data types, including NUMBER, DECIMAL, NUMERIC, FLOAT, and DOUBLE PRECISION. However, NUMBER (or its synonyms DECIMAL and NUMERIC) are frequently used to store exact numeric data with optional scale and precision. Precision defines the total number of digits allowed, and scale defines the number of digits to the right of the decimal point. For example, NUMBER(5,2) can store a maximum of five digits, with two of them after the decimal point.

GoldenGate Configuration for Decimal Types

When configuring GoldenGate for use with the Kafka handler, several properties directly influence how decimal types are handled:

1. Data Types Conversion: Set with SOURCEDEFS or TARGETDEFS files. These files define the data structure of source and target systems to ensure that the data is interpreted correctly.
2. Handler Properties: The Kafka handler has specific settings in the properties file (e.g., gg.handler.kafka.propertyFile) controlling how data types are mapped and serialized. The critical property relating to decimals is how they are converted or cast during the transfer process.

Using Kafka and Kafka Connect Handlers

Kafka and Kafka Connect handlers can process GoldenGate trail files and publish changes into Kafka topics. Handling of precision and scale in decimal types is pivotal since Kafka's native types differ somewhat from Oracle's.

Kafka Configuration

• Kafka Connect Decimal Conversion: Kafka Connect can serialize and deserialize data into various formats, including Avro, JSON, and Protobuf. For decimals, Avro format is preferable because it supports logical types like decimal, which can precisely handle these values using bytes and fixed types. The Connect configuration would include specifying the decimal.handling.mode to ensure that decimal types are appropriately handled.
• Schema Registry: Avro schemas, including decimal types, can be managed using a schema registry, which provides centralized schema management and validation. This is crucial for ensuring that all Kafka messages conform to expected formats and types, particularly for precision-sensitive data.

Practical Example

Consider an Oracle table with a NUMBER(10,4) column. The GoldenGate Kafka handler configuration might look like the following:

1gg.handler.kafka.type=kafkaconnect
2gg.handler.kafka.Name=kafkaHandler
3gg.handler.kafka.KafkaProducerConfigFile=kafka_producer.properties
4gg.handler.kafka.topicMappingTemplate=${schemaName}.${tableName}
5gg.handler.kafka.format=avro
6gg.handler.kafka.avroSchemaNamespace=com.example
7gg.handler.kafka.includeTokens=true
8gg.handler.kafka.keyColumns=id
9gg.handler.kafka.SchemaRegistryURL=http://schema-registry-host:8081
10gg.handler.kafka.avroDecimalHandlingMode=PRECISE

Key Points Summary

Additional Considerations

• Performance Impact: Handling high-precision decimals can impact performance. Testing and optimization may be required depending on the volume of data and frequency of updates.
• Data Consistency: Ensure consistency during data type transformations between Oracle and Kafka. Thorough testing and validation strategies are essential.

The integration of Oracle GoldenGate with Kafka using the Kafka or Kafka Connect handler enables real-time data streaming capabilities, but handling data types like Oracle's decimal requires careful consideration and setup. Using the correct configurations and understanding the nuances of data serialization are key to a successful implementation.