#bbuzz: Querying Data Streams with Flink SQL – Part 2
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| Title | #bbuzz: Querying Data Streams with Flink SQL – Part 2 |
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| Number of Parts | 48 |
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| License | You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor. |
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| Abstract | Apache Flink supports SQL as a unified API for stream and batch processing. SQL is easier to use than Flink’s lower-level APIs and covers a wide variety of use cases. In this hands-on tutorial you will learn how to run SQL queries on data streams with Apache Flink. We will look at the concepts behind continuous queries and dynamic tables and will show you how to solve different use cases with streaming SQL, including enriching and joining streaming data, computing windowed aggregations, and maintaining materialized views in external storage systems.
Prerequisites:
- No prior knowledge of Apache Flink is required. We assume basic knowledge of SQL
- You will need a computer with at least 8 GB RAM and Docker installed. |
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