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@ -31,7 +31,7 @@ The key features for DolphinScheduler are as follows: |
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DolphinScheduler uses a decentralized multi-master and multi-worker architecture, which naturally supports horizontal scaling and high availability |
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DolphinScheduler uses a decentralized multi-master and multi-worker architecture, which naturally supports horizontal scaling and high availability |
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- High performance, its performance is N times faster than other orchestration platform and it can support tens of millions of tasks per day |
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- High performance, its performance is N times faster than other orchestration platform and it can support tens of millions of tasks per day |
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- Supports multi-tenancy |
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- Supports multi-tenancy |
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- Supports various task types: Shell, MR, Spark, SQL (MySQL, PostgreSQL, Hive, Spark SQL), Python, Procedure, Sub_Workflow, |
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- Supports various task types: Shell, MR, Spark, SQL (MySQL, OceanBase, PostgreSQL, Hive, Spark SQL), Python, Procedure, Sub_Workflow, |
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Http, K8s, Jupyter, MLflow, SageMaker, DVC, Pytorch, Amazon EMR, etc |
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Http, K8s, Jupyter, MLflow, SageMaker, DVC, Pytorch, Amazon EMR, etc |
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- Orchestrating workflows and dependencies, you can pause/stop/recover task any time, failed tasks can be set to automatically retry |
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- Orchestrating workflows and dependencies, you can pause/stop/recover task any time, failed tasks can be set to automatically retry |
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- Visualizing the running state of the task in real-time and seeing the task runtime log |
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- Visualizing the running state of the task in real-time and seeing the task runtime log |
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