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Overview for flink-sql

AthenaX - Unified Stream & Batch Processing using SQL at Uber,

Learn how AthenaX, Uber's streaming analytics platform enables users to run production-quality, large scale streaming analytics using SQL. This discussion highlights the design and architecture of AthenaX, and also Uber's production experience.


Streaming SQL to unify batch and stream processing: Theory and practice with Apache Flink at Uber

Fabian Hueske and Shuyi Chen share their experience using Flink SQL in production at Uber, explaining how Uber leverages Flink SQL to solve its unique business challenges and how the unified stream and batch processing platform enables both technical or nontechnical users to process real-time and batch data reliably using the same SQL at Uber scale.


Blink’s Improvements to Flink SQL & TableAPI

Search and recommendation system for Alibaba’s e-commerce platform use batch and streaming processing heavily. Flink SQL and Table API (which is a SQL-like DSL) provide simple, flexible, and powerful language to express the data processing logic. More importantly, it opens the door to unify the semantics of batch and streaming jobs. In this talk, Shaoxuan Wang and   Xiaowei Jiang both from Alibaba share their experience of running large scale Flink SQL and TableAPI jobs in Alibaba Search.