How-to Guides for Confluent Cloud for Apache Flink¶
Discover how Confluent Cloud for Apache Flink® can help you accomplish common processing tasks such as joins and aggregations. This section provides step-by-step guidance on how to use Flink to process your data efficiently and effectively.
- Aggregate a Stream in a Tumbling Window
- Combine Streams and Track Most Recent Records
- Compare Current and Previous Values in a Data Stream
- Convert the Serialization Format of a Topic
- Create a User Defined Function
- Handle Multiple Event Types
- Process Schemaless Events
- Scan and Summarize Tables
- View Time Series Data
Flink actions¶
Confluent Cloud for Apache Flink provides Flink Actions that enable you to perform specific data-processing tasks on topics with minimal configuration. These actions are designed to simplify common workloads by providing a user-friendly interface to configure and execute them.
- Create an Embedding: Convert data in a topic’s column into a vector embedding for AI model inference.
- Deduplicate Rows in a Table: Remove duplicate records from a topic based on specified fields, ensuring that only unique records are retained in the output topic.
- Mask Fields in a Table: Mask sensitive data in specified fields of a topic by replacing the original data with a static value.
- Transform a Topic: Change a topic’s properties by applying custom Flink SQL transformations.