86 lines
2.7 KiB
Plaintext
86 lines
2.7 KiB
Plaintext
[[ml-post-data]]
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==== Post Data to Jobs
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The post data API allows you to send data to an anomaly detection job for analysis.
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The job must have been opened prior to sending data.
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===== Request
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`POST _xpack/ml/anomaly_detectors/<job_id>/_data --data-binary @<data-file.json>`
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===== Description
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File sizes are limited to 100 Mb, so if your file is larger,
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then split it into multiple files and upload each one separately in sequential time order.
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When running in real-time, it is generally recommended to arrange to perform
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many small uploads, rather than queueing data to upload larger files.
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IMPORTANT: Data can only be accepted from a single connection.
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Do not attempt to access the data endpoint from different threads at the same time.
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Use a single connection synchronously to send data, close, flush or delete a single job.
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+
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It is not currently possible to post data to multiple jobs using wildcards or a comma separated list.
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===== Path Parameters
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`job_id` (required)::
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(+string+) Identifier for the job
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===== Request Body
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`reset_start`::
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(+string+; default: ++null++) Specifies the start of the bucket resetting range
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`reset_end`::
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(+string+; default: ++null++) Specifies the end of the bucket resetting range"
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////
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===== Responses
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200
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(EmptyResponse) The cluster has been successfully deleted
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404
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(BasicFailedReply) The cluster specified by {cluster_id} cannot be found (code: clusters.cluster_not_found)
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412
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(BasicFailedReply) The Elasticsearch cluster has not been shutdown yet (code: clusters.cluster_plan_state_error)
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The following example sends data from file `data-file.json` to a job called `my_analysis`.
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////
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===== Examples
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The following example posts data from the farequote.json file to the `farequote` job:
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[source,js]
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--------------------------------------------------
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$ curl -s -H "Content-type: application/json"
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-X POST http:\/\/localhost:9200/_xpack/ml/anomaly_detectors/farequote --data-binary @farequote.json
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--------------------------------------------------
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// CONSOLE
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// TEST[skip:todo]
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When the data is sent, you receive information about the operational progress of the job.
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For example:
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----
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{
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"job_id":"farequote",
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"processed_record_count":86275,
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"processed_field_count":172550,
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"input_bytes":8678202,
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"input_field_count":258825,
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"invalid_date_count":0,
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"missing_field_count":0,
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"out_of_order_timestamp_count":0,
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"empty_bucket_count":0,
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"sparse_bucket_count":0,
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"bucket_count":1440,
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"earliest_record_timestamp":1454803200000,
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"latest_record_timestamp":1455235196000,
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"last_data_time":1491436182038,
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"input_record_count":86275
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}
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----
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For more information about these properties, see <<ml-jobcounts,Job Counts>>.
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