Opening Remarks: We expect more developers will become part of the Flink community
By Wang Shaoxuan, Senior Staff Engineer from Alibaba’s Computing Platform
Apache Flink, formerly known as Stratosphere, is a project initiated by several doctoral and postgraduate students at the Berlin Institute of Technology in Germany, where in 2014 they opened the source of the project and named it Flink. I became aware of Apache Flink in 2015 before witnessing and helping to complete its implementation as a stream computing engine at Alibaba Group. For many years now, it has helped Alibaba to pull off one successful 11.11 Shopping Festival after another. For the most recent 11.11 of 2018, the Flink engine smoothly supported real-time traffic peaking at 1.7 billion transactions per second.
Apache Flink has earned industry-wide recognition as the best available stream computing engine. However, Flink is in fact more than a stream processing engine. The positioning of Apache Flink is as a set of big data engines with multiple computing capabilities, including streaming, batch, and machine learning.
Lately, Flink has made great breakthroughs in many big data scenarios such as batch processing and machine learning. On the one hand, Flink’s batch computing has shown exponential improvement with Alibaba’s optimization work. On the other hand, the Flink community is gradually expanding its work into many areas including tableAPI, Python, and ML libraries, thus leading to a significant improvement on user experience for data science and AI computing. In addition, Flink is gradually upgrading its integration with other open source projects, including Hive, Notebook (Zeppelin, Jupyter), and so on.
Apache Flink has only been open sourced for four years, and we expect more companies and developers will join the community and ecosystem of Apache Flink and together build it as the world’s best open source big data computing engine.
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