As data processing becomes more real-time, stream processing is becoming more important. Apache Flink makes it easier to build and manage stream processing applications. Flink’s new SQL interface is not only a great way to get started with Flink, but also to build and maintain production applications.
This hands-on session introduces Flink via the SQL interface. You will receive an overview of stream processing, and a survey of Apache Flink with its various modes of use. Then we’ll use Flink to run SQL queries on data streams and contrast this with the Flink data stream API.
Talk: Survey of Apache Flink and its interfaces
Talk: Intro into SQL on Flink
Unified API for Batch and Streaming
Executing SQL queries on Flink
Walk through the documentation
Hands-On: Setting up the SQL CLI Client
Running the first queries
Talk: SQL on Data Streams
Tables, Streams, and Materialized Views
Event Time and Processing Time
Hands-On: Running queries on data streams
Event time queries
(considering cutting: Processing time queries
Considering cutting: Materializing Queries)
Talk: Flink APIs, Internals, Connectors & UDFs
Table API and SQL
Hands-on: Working with the datastream API
Fabian Hueske is a committer and PMC member of the Apache Flink project. He was one of the three original authors of the Stratosphere research system, from which Apache Flink was forked in 2014. Fabian is a co-founder of Ververica, a Berlin-based startup devoted to fostering Flink, where he works as a software engineer and contributes to Apache Flink. He holds a PhD in computer science from TU Berlin and is currently spending a lot of his time writing a book, Stream Processing with Apache Flink.
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