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Don't see much recent discussion about FlinkML - is it dying or dead?
What are some examples of some interesting recent live usages?
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Flink's low latency outperforms Spark consistently, even at higher throughput. Spark can achieve low latency with lower throughput, but increasing the throughput will also increase the latency.
Flink ML is a library which provides machine learning (ML) APIs and infrastructures that simplify the building of ML pipelines. Users can implement ML algorithms with the standard ML APIs and further use these infrastructures to build ML pipelines for both training and inference jobs.
PyFlink is a Python API for Apache Flink that allows you to build scalable batch and streaming workloads, such as real-time data processing pipelines, large-scale exploratory data analysis, Machine Learning (ML) pipelines and ETL processes.
The community decided to drop the old flink-ml library from the 1.9 release. Meanwhile a new machine learning library has been developed under the umbrella of FLIP-39, and is being extended under FLINK-12470.
Alink may also be of interest.
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