What is the primary role of a Cloud Dataflow connector?

A Cloud Dataflow connector primarily serves the function of outputting the results of a pipeline to specific data sinks. In the context of Google Cloud Dataflow, which is a managed service for processing and analyzing large datasets in real time, connectors are integral components that facilitate the integration of various data sources and sinks.

When you create Dataflow pipelines, the main objective often includes transforming and processing data efficiently. Once the data has been processed, the results need to be stored or made available in a format that can be utilized by other systems or applications. This is where connectors come into play, as they allow developers to define how and where the processed data should be sent, whether it’s to Cloud Storage, BigQuery, Pub/Sub, or other services.

This functionality enables flexibility and scalability within data workflows, making it possible to send output data to the appropriate destination efficiently. Such connectors greatly enhance the utility of Dataflow in building robust data processing pipelines that can cater to varying needs for data movement and storage.