Github Flink Extended Ai Flow Ai Flow Is An Open Source Framework Aiflow is an event based workflow orchestration platform that allows users to programmatically author and schedule workflows with a mixture of streaming and batch tasks. most existing workflow orchestration platforms (e.g. apache airflow, kubeflow) schedule task executions based on the status changes of upstream task executions. Aiflow is proposed to facilitate the orchestration of workflows involving streaming tasks. for example, users might want to run a flink streaming job continuously to assemable training data, and start a machine learning training job everytime the flink job has processed all upstream data for the past hour.

Flow Framework Github Flink ai flow's current components are: sdk: it defines how to build a machine learning workflow and includes the api of the flink ai flow. notification service: it provides event listening and notification functions. meta service: it saves the meta data of the machine learning workflow. Aiflow is an event based workflow orchestration platform that allows users to programmatically author and schedule workflows with a mixture of streaming and batch tasks. most existing workflow orchestration platforms (e.g. apache airflow, kubeflow) schedule task executions based on the status changes of upstream task executions. Ai flow seamlessly integrates with apache flink, a powerful stream processing framework. by using a specific implementation called linking airflow, users can leverage flink's capabilities within their ai workflows. Deep learning on flink aims to integrate flink and deep learning frameworks (e.g. tensorflow, pytorch, etc) to enable distributed deep learning training and inference on a flink cluster. ai flow is an open source framework that bridges big data and artificial intelligence.

Github Liukingjia Flink Ai Extended Ai flow seamlessly integrates with apache flink, a powerful stream processing framework. by using a specific implementation called linking airflow, users can leverage flink's capabilities within their ai workflows. Deep learning on flink aims to integrate flink and deep learning frameworks (e.g. tensorflow, pytorch, etc) to enable distributed deep learning training and inference on a flink cluster. ai flow is an open source framework that bridges big data and artificial intelligence. Flink ai flow is an open source framework that bridges big data and ai. it manages the entire machine learning project lifecycle as a unified workflow, including feature engineering,. Aiflow is an event based workflow orchestration platform that allows users to programmatically author and schedule workflows with a mixture of streaming and batch tasks. most existing workflow orchestration platforms (e.g. apache airflow, kubeflow) schedule task executions based on the status changes of upstream task executions. In addition to the capability of orchestrating a group of batch jobs, by leveraging an event based scheduler (enhanced version of airflow), flink ai flow also supports workflows that contain streaming jobs. Flink ai extended is a project extending flink to various machine learning scenarios. currently it contains the following two subprojects. flink ai flow is an open source framework that bridges big data and ai.