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# How-to Guides for Confluent Cloud for Apache Flink

These how-to guides provide task-focused, step-by-step instructions for
common Flink SQL processing patterns on Confluent Cloud for Apache Flink®, including joins,
aggregations, windowed queries, and user-defined functions (UDFs).

- [Aggregate a Stream in a Tumbling Window](aggregate-tumbling-window.md#flink-sql-aggregate-tumbling-window)
- [Combine Streams and Track Most Recent Records](combine-and-track-most-recent-records.md#flink-sql-combine-streams)
- [Compare Current and Previous Values in a Data Stream](compare-current-and-previous-values.md#flink-sql-compare-current-and-previous-values)
- [Convert the Serialization Format of a Topic](convert-serialization-format.md#flink-sql-convert-format)
- [Create a User Defined Function](create-udf.md#flink-sql-create-udf)
- [Handle Multiple Event Types](multiple-event-types.md#flink-sql-multiple-event-types)
- [Read Records without a Schema ID Prefix](read-records-without-schema-id-prefix.md#flink-sql-read-records-without-schema-id-prefix)
- [Resolve Statement Issues](resolve-common-query-problems.md#flink-sql-statement-problems)
- [Run a Snapshot Query](run-snapshot-query.md#flink-sql-run-snapshot-query)
- [Scan and Summarize Tables](scan-and-summarize-tables.md#flink-sql-scan-and-summarize)
- [Set a Baseline CFU for a Statement](manage-baseline-cfu.md#flink-sql-manage-baseline-cfu)
- [View Time Series Data](view-time-series-data.md#flink-sql-view-time-series)

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## 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
simplify common workloads with a user-friendly interface that lets you
configure and execute them.

- [Create an Embedding](../../ai/embeddings/embedding-action.md#flink-sql-embedding-action): Convert data in a
  topic’s column into a vector embedding for AI model inference.
- [Deduplicate Rows in a Table](deduplicate-rows.md#flink-sql-deduplicate-topic-action):
  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-fields.md#flink-sql-mask-fields-action): Mask sensitive
  data in specified fields of a topic by replacing the original data with a
  static value.
- [Transform a Topic](transform-topic.md#flink-sql-transform-topic-action): Change a
  topic’s properties by applying custom Flink SQL transformations.

## Related content

- Video: [How to Set Idle Timeouts](https://www.youtube.com/watch?v=YSIhM5-Sykw)
- Video: [How to Analyze Data from a REST API with Flink SQL](https://www.youtube.com/watch?v=HB_TbqCKny4)
- Video: [How To Use Streaming Joins with Apache Flink](https://www.youtube.com/watch?v=ChiAXgTuzaA)
- Video: [How to Visualize Real-Time Data from Apache Kafka using Apache Flink SQL and Streamlit](https://www.youtube.com/watch?v=dRkyf1eyYvQ)
- [Use Flink SQL with Kafka, Streamlit, and the Alpaca API](https://github.com/confluentinc/demo-scene/tree/master/flink-streamlit)

#### NOTE
This website includes content developed at the [Apache Software Foundation](https://www.apache.org/)
under the terms of the [Apache License v2](https://www.apache.org/licenses/LICENSE-2.0.html).