Commit Graph

5 Commits

Author SHA1 Message Date
Dimitris Athanasiou f49a14ce6f
[7.x][ML] Fix race condition when force stopping DF analytics job (#57680) (#57717)
When we force delete a DF analytics job, we currently first force
stop it and then we proceed with deleting the job config.
This may result in logging errors if the job config is deleted
before it is retrieved while the job is starting.

Instead of force stopping the job, it would make more sense to
try to stop the job gracefully first. So we now try that out first.
If normal stop fails, then we resort to force stopping the job to
ensure we can go through with the delete.

In addition, this commit introduces `timeout` for the delete action
and makes use of it in the child requests.

Backport of #57680
2020-06-05 17:50:01 +03:00
Dimitris Athanasiou ca0828ba07
[7.x][ML] Implement force deleting a data frame analytics job (#50553) (#50589)
Adds a `force` parameter to the delete data frame analytics
request. When `force` is `true`, the action force-stops the
jobs and then proceeds to the deletion. This can be used in
order to delete a non-stopped job with a single request.

Closes #48124

Backport of #50553
2020-01-03 13:46:02 +02:00
Lisa Cawley d62e1a3d8b [DOCS] Fixes data frame analytics job terminology in HLRC (#46758) 2019-09-16 10:07:59 -07:00
Lisa Cawley 7461259ba6 [DOCS] Adds missing icons to ML HLRC APIs (#46515) 2019-09-10 08:28:02 -07:00
Dimitris Athanasiou 126c2fd2d5
[7.x][ML] Machine learning data frame analytics (#43544) (#43592)
This merges the initial work that adds a framework for performing
machine learning analytics on data frames. The feature is currently experimental
and requires a platinum license. Note that the original commits can be
found in the `feature-ml-data-frame-analytics` branch.

A new set of APIs is added which allows the creation of data frame analytics
jobs. Configuration allows specifying different types of analysis to be performed
on a data frame. At first there is support for outlier detection.

The APIs are:

- PUT _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}/_stats
- POST _ml/data_frame/analysis/{id}/_start
- POST _ml/data_frame/analysis/{id}/_stop
- DELETE _ml/data_frame/analysis/{id}

When a data frame analytics job is started a persistent task is created and started.
The main steps of the task are:

1. reindex the source index into the dest index
2. analyze the data through the data_frame_analyzer c++ process
3. merge the results of the process back into the destination index

In addition, an evaluation API is added which packages commonly used metrics
that provide evaluation of various analysis:

- POST _ml/data_frame/_evaluate
2019-06-25 20:29:11 +03:00