Blink’s Improvements to Flink SQL & TableAPI

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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. To support our products, we made lots of improvements to Flink SQL & TableAPI. We added the support for User-Defined Table function (UDTF), User-Defined Aggregates (UDAGG), window aggregate, and streaming retraction, etc. We have contributed these improvements back to the Flink community in the last few months. In this talk, we present the design and implementation of these improvement. We will also share the experience of running large scale Flink SQL and TableAPI jobs in Alibaba Search.