support train ML model in either sync or async way #124
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Signed-off-by: Yaliang Wu <ylwu@amazon.com>
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Zhangxunmt
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Jan 20, 2022
| @@ -63,6 +65,7 @@ | |||
| @Setter | |||
| private String error; | |||
| private User user; // TODO: support document level access control later | |||
| private boolean async; | |||
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| @Builder | |||
| public MLTask( | |||
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We can consider moving this class to the ml-common in the next PR.
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Yes, will send out a separate refactoring PR
Zhangxunmt
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Jan 20, 2022
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| if (request.isAsync()) { | ||
| mlTaskManager.createMLTask(mlTask, ActionListener.wrap(r -> { | ||
| String taskId = r.getId(); | ||
| mlTask.setTaskId(taskId); | ||
| if (mlTask.isAsync()) { |
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Is there any user case that the request is Sync, but the mlTask is Async? I am just wondering the difference between the two.
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Async property of MLTask is consistent with request, check line 116 of this class.
For async task, we will cache task in memory and persist task in index and it will return task id directly.
For sync task, we just cache task in memory. Will train model and return the model id.
Zhangxunmt
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Signed-off-by: Yaliang Wu ylwu@amazon.com
Description
Support training ML model in either sync or async way.
For example, PPL user should be able to train ML model in sync way; and user can use async way if the model training will be time consuming.
Main changes:
asyncURL parameter in train API. Add?async=trueif need to train model in async way, by default will train model in sync way.GetRequestto get model in predict task runnerCheck List
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