This document discusses streamDM, an open source machine learning library for stream mining in Spark Streaming. It summarizes streamDM's capabilities for incremental learning on data streams using algorithms like SGD, Naive Bayes, clustering and decision trees. Examples of using streamDM in Huawei's network alarm analysis and fault localization systems are provided, demonstrating improvements in efficiency, accuracy and ability to handle large volumes of streaming data. The document encourages researchers to apply for Huawei's Innovation Research Program grants to further collaborative work on stream mining algorithms and applications.