What is the custom stage in GoldenGate Stream Analytics (OSA), and how does it work?

November 10, 2023 | 3 minute read
Nisharahmed Soneji
Distinguished Data Management Specialist
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As part of my 3-part blog series, I am writing about the GoldenGate Stream Analytics custom stage functionality, how it has been used in one of the customer scenarios with examples, what the architecture was, how the pipeline was built, and the Java program that creates the Kafka Avro Nested messages.

Let's talk about how GoldenGate Stream Analytics works. Real-time data is processed and analyzed in Streaming Pipelines like the one you see on the screen. You process incoming real-time data from several possible sources, such as GoldenGate Extracts from transactional sources, event hubs such as OCI Streaming, Kafka, or JMS, or file sources. The pipeline can be built using an interactive editor, and you can enrich, filter, and aggregate the data and analyze it through predefined patterns, machine learning models, or rules. Finally, you can visualize the data or write it to several targets, such as streaming hubs, relational or no-SQL databases, big data targets, or object stores, and this from different clouds or on-premises.

GoldenGate Stream Analytics is built on the Spark Streaming architecture to provide unlimited horizontal scaling, but at the same time, combines this with our own CQL query engine to provide rich and flexible stream processing semantics. 

GoldenGate Stream Analytics

To summarize the key capabilities, GoldenGate Stream Analytics provides an interactive, self-service interface to create low-code ETL pipelines. You can do Time-Series Analytics through in-built patterns to detect trends, outliers, and other relevant occurrences in your data. You can visualize your data in real-time dashboards in the tool and outside using Oracle Analytics Cloud or third-party environments such as Grafana. We provide a rich library of patterns to make rule-based decisions, and you can interactively define geospatial analysis, such as geo-fences, to detect the location or proximity of objects on a map. Finally, a central point is the ability to perform predictive analytics based on machine learning models such as PMML, ONNX, or our own OML Oracle Machine Learning in autonomous databases.

However, suppose the abovementioned functionalities are insufficient, and you want to build your own custom logic while processing the data in the GoldenGate Stream Analytics. In that case, it is very much possible with the "Custom Stage" functionality. The custom stage types or functions allow you to develop business logic unavailable in common stages and functions. For example, uncommon calculations, conversions, or algorithms.

For example, calculate a message digest using the MD5 algorithm. This algorithm is not part of the in-built function library, and it is not practical to implement it as an expression. Or you want to convert the data into another format (AVRO Kafka Nested messages), which is not supported out of the box. There are such scenarios where you need to use a custom stage. 

The custom stage types and functions are implemented in Java programming using interfaces, classes, and annotations provided in the osa.spark-cql.extensibility.api.jar library. You can download this jar file from the installation folder: osa-base/extensibility-api/osa.spark-cql.extensibility.api.jar. For more information, see Spark Extensibility for CQL in Oracle Stream Analytics.

For a custom stage type, you must implement the EventProcessor interface and apply the @OsaStage annotation to your class declaration. You must implement the processEvent() method that takes an input Event and returns an Output Event, which must be defined using the input and output spec, respectively.

As part of my future blogs, I will show you the example of custom stage programming and how it has been used in one of the use-cases and respective use-cases & architecture. Until then, stay tuned. For more information about the custom stage, the detailed documentation can be found at Developing Custom Stages and Custom Functions (oracle.com)

Nisharahmed Soneji

Distinguished Data Management Specialist

Nishar is the "Distinguished Data Management Specialist", leading the sales opportunity for Data Integration products, OCI GoldenGate & GoldenGate On-premises in the EMEA region. The GoldenGate is the best database replication technology available in the market. He has been advocating for the customers on new-age technology and best practices and helping them achieve strategic goals using Oracle solutions and Products. He has been evangelizing GoldenGate Products, Solutions, and new-age architects(Data Mesh, Data Fabric) in Conferences, enabling and coaching the Tech hub engineers on the Products' functionality & insights. The family of GoldenGate products includes OCI GoldenGate, GoldenGate for Oracle, GoldenGate for Non-Oracle, GoldenGate for Big Data, GoldenGate Stream Analytics, GoldenGate Foundation Suite(Veridata, GoldenGate OEM PlugIn), and OCI Data Integration.

Before joining the sales team, he was a Senior Principal Product Manager at Oracle. He led the OCI GoldenGate Cloud Service, GoldenGate Foundation Suite Products, and GoldenGate core products globally.

Nishar has been a key leadership team member who created new cloud services from inception to growing Oracle Data Integration business services. He has also spearheaded multiple Oracle internal innovations, resulting in top-line and bottom-line growth in Database Replication.

Nishar has over 22+ years of experience in technology, specializing in enterprise data replication and integration products, with a demonstrated track record of creating and scaling world-class businesses. For the last 10+ years, He has been focused on driving revenue through sales and product management, making the business strategy, executing the product execution, and leading the cross-functional teams and products.

Before joining the Sales and Product Management role, he was the software development architect; he led various complex technology projects for several companies, including Endress+Hauser, Cummins Inc, and GoldenGate Inc.


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