Streaming


Track Chairs : Yu Li, Xin Wang

Streaming data processing is a big deal in big data these days, businesses crave ever-more timely insights into their data, and what was once a ‘batch’ mindset is quickly being replaced with stream processing. More and more companies, small and large, are rethinking their architecture with real-time context at the forefront, and starting to build their streaming platforms with powerful open source engines such as Apache Flink, Apache Spark, Apache Kafka, Apache Pulsar, Apache Storm, Apache StreamPark (incubating), Apache Paimon (incubating) etc.

In this topic, you will not only learn about the practical experience of first-line users in applying these Apache projects to their in-production environment, but also the latest developments in the ecology of these Apache projects, and visions on where streaming technology is heading in the future.

2023-08-18

13:30 GMT+8 Apache Flink stream batch adaptive Shuffle Chinese Session 宋辛童,谭玉新

14:00 GMT+8 Build a stream graph processing system based on Apache Calcite/Gremlin Chinese Session 潘臻轩

14:30 GMT+8 China Unicom's large-scale real-time computing production practice based on Apache StreamPark Chinese Session 穆纯进

15:00 GMT+8 FlinkSQL's field parentage and data permission solution Chinese Session 白松

15:45 GMT+8 Streaming Apache Kudu within Apache Flink English Session Wei Chen

2023-08-19

13:30 GMT+8 Real-Time Data Integration Practice Based on Flink CDC at Alibaba Cloud Chinese Session Ruan Hang

14:00 GMT+8 In-depth analysis of Ziroom's large-scale On Kubernetes real-time computing production practice based on Apache StreamPark Chinese Session 陈卓宇

14:30 GMT+8 Flink K8S Operator AutoScaling Chinese Session Chen Zhengyu

15:00 GMT+8 RSQLDB Message queue-based flow database Chinese Session 倪泽

15:45 GMT+8 State of Scala API in Apache Flink English Session alexey

16:15 GMT+8 Construction practice of Xiaomi Flink real-time computing platform Chinese Session 陈子豪