The platform offers a wide range of algorithm libraries that support both batch and stream processing, which is critical for machine learning tasks such as online product recommendations and intelligent customer services.
Data analysts and software developers can access the codes on GitHub (https://github.com/alibaba/alink) to create their own software and facilitate tasks such as statistical analysis, machine learning, real-time prediction, personalized recommendations and anomaly detection.
"As a platform consisting of multiple algorithms that combine learning in different data processing patterns, Alink can be a valuable option for developers looking for robust large amounts of data and advanced machine learning tools," said Yangqing Jia, president and senior fellow of the data platform at Alibaba Cloud Intelligence. "As one of GitHub's top ten employees, we are committed to connecting with the open source community as early as possible in our software development cycles. Sharing Alink on GitHub underscores our long-standing commitment."
Alink was developed on the basis of Flink, a unified distributed computing engine. Based on Flink, Alink has seamlessly unified batch and stream processing and provides a more effective platform for developers to perform data analysis and machine learning. It supports not only Alibaba's proprietary data store, but also other open source data stores such as Kafka, HDFS and HBase.
Alink is already being used to support various companies within the Alibaba ecosystem. For example, it has helped increase the click rate of product recommendations on Alibaba's e-commerce platform Tmall by 4 percent this year during Alibaba's Global Shopping Festival.
In addition to GitHub, Alibaba has also been active in other open source communities such as the Cloud Native Computing Foundation, Alliance for Open Media, Cloud Foundry, Hyperledger, Open Container Initiative, Continuous Delivery Foundation, The Apache Software Foundation, MariaDB Foundation and The Linux Foundation.