honeymoose
/
OpenSearch
mirror of https://github.com/honeymoose/OpenSearch.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
OpenSearch/docs/java-rest/high-level/ml/delete-data-frame-analytics...

42 lines
1.3 KiB
Plaintext
Raw Normal View History

[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 13:29:11 -04:00
--
:api: delete-data-frame-analytics
:request: DeleteDataFrameAnalyticsRequest
:response: AcknowledgedResponse
--
[DOCS] Adds missing icons to ML HLRC APIs (#46515)
2019-09-10 11:26:56 -04:00
[role="xpack"]
[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 13:29:11 -04:00
[id="{upid}-{api}"]
[DOCS] Fixes data frame analytics job terminology in HLRC (#46758)
2019-09-16 13:00:44 -04:00
=== Delete {dfanalytics-jobs} API
[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 13:29:11 -04:00
[DOCS] Fixes data frame analytics job terminology in HLRC (#46758)
2019-09-16 13:00:44 -04:00
Delete an existing {dfanalytics-job}.
[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 13:29:11 -04:00
The API accepts a +{request}+ object as a request and returns a +{response}+.
[id="{upid}-{api}-request"]
[DOCS] Fixes data frame analytics job terminology in HLRC (#46758)
2019-09-16 13:00:44 -04:00
==== Delete {dfanalytics-jobs} request
[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 13:29:11 -04:00
[DOCS] Fixes data frame analytics job terminology in HLRC (#46758)
2019-09-16 13:00:44 -04:00
A +{request}+ object requires a {dfanalytics-job} ID.
[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 13:29:11 -04:00
["source","java",subs="attributes,callouts,macros"]
---------------------------------------------------
include-tagged::{doc-tests-file}[{api}-request]
---------------------------------------------------
[DOCS] Fixes data frame analytics job terminology in HLRC (#46758)
2019-09-16 13:00:44 -04:00
<1> Constructing a new request referencing an existing {dfanalytics-job}.
[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 13:29:11 -04:00
[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 06:46:02 -05:00
==== Optional arguments
The following arguments are optional:
["source","java",subs="attributes,callouts,macros"]
---------------------------------------------------
[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 10:50:01 -04:00
include-tagged::{doc-tests-file}[{api}-request-options]
[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 06:46:02 -05:00
---------------------------------------------------
<1> Use to forcefully delete a job that is not stopped. This method is quicker than stopping
and deleting the job. Defaults to `false`.
[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 10:50:01 -04:00
<2> Use to set the time to wait until the job is deleted. Defaults to 1 minute.
[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 06:46:02 -05:00
[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 13:29:11 -04:00
include::../execution.asciidoc[]
[id="{upid}-{api}-response"]
==== Response
[DOCS] Fixes data frame analytics job terminology in HLRC (#46758)
2019-09-16 13:00:44 -04:00
The returned +{response}+ object acknowledges the {dfanalytics-job} deletion.