Apache Flink is a stream processing framework with two main interfaces: Flink SQL, which uses SQL for batch and streaming data, and the DataStream API...
This article is authored by the data pipeline team of Alibaba Cloud's open-source big data platforms.
Unified batch and stream processing of Flink is a well-established concept in the stream computing field.
Discover Flink SQL, the high-level API for executing SQL queries across streaming and batch data sets in Apache Flink.
This article is based on a keynote speech given by Jark Wu, head of Flink SQL and Flink CDC at Alibaba Cloud, during Flink Forward Asia 2023.
This article introduces SPL and its application in the Realtime Compute for Apache Flink SLS Connector.
This article describes how to use SLS SPL (Structured Programming Language) to configure the SLS Connector to structure data.
This article is compiled from Xiaolin He’s presentation at the 2022 Flink Forward Asia (FFA) Conference, discussing Flink SQL insight, best practices, and future works.
This article was compiled from a speech from the Apache Flink Meetup, discussing the release of Flink 1.16.
This article introduces the real-time data warehouse architecture built by Kwai based on Flink and offers solutions to some difficult problems.
This article focuses on the optimization measures of Jingdong in Flink SQL tasks, focusing on the aspects of shuffle, join mode selection, object reuse, and UDF reuse.
This article gives a detailed interpretation of Flink Connector from the four aspects: connectors, Source API, Sink API, and the future development of collectors.
This article explains the key functional changes in Flink 1.9 from the user perspective and describes the design and scenarios of the new TableEnvironment.
