[DOCS] Add ML configuration details and examples for script fields (elastic/x-pack-elasticsearch#1593)
* [DOCS] Add ML info about script fields * [DOCS] Add links to ML script fields page * [DOCS] Add ML API examples to transforms.asciidoc * [DOCS] Addressed feedback in ML script field examples * [DOCS] Add preview to ML script fields example * [DOCS] Expanded code snippets in ML transform examples * [DOCS] Add output for ML scripted fields example * [DOCS] Add output for more ML scripted field examples * [DOCS] Add output for final ML scripted field examples * [DOC] Add Kibana details for ML script fields * [DOCS] Remove example from ML transforms Original commit: elastic/x-pack-elasticsearch@51057b029f
This commit is contained in:
Lisa Cawley
GitHub
parent
431118b123
commit
2b1d5f2cf2
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@ -31,7 +31,9 @@ The scenarios in this section describe some best practices for generating useful
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* <<ml-configuring-aggregation>>
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* <<ml-configuring-categories>>
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* <<ml-configuring-pop>>
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* <<ml-configuring-transform>>
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include::aggregations.asciidoc[]
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include::categories.asciidoc[]
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include::populations.asciidoc[]
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include::transforms.asciidoc[]
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@ -74,5 +74,4 @@ format. For example, the following Painless script transforms
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}
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--------------------------------------------------
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For more information about `script_fields`, see
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{ref}/ml-datafeed-resource.html[Datafeed Resources].
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For more information, see <<ml-configuring-transform>>.
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@ -0,0 +1,611 @@
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[[ml-configuring-transform]]
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=== Transforming Data With Script Fields
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If you use {dfeeds}, you can add scripts to transform your data before
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it is analyzed. {dfeeds-cap} contain an optional `script_fields` property, where
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you can specify scripts that evaluate custom expressions and return script
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fields.
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If your {dfeed} defines script fields, you can use those fields in your job.
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For example, you can use the script fields in the analysis functions in one or
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more detectors.
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* <<ml-configuring-transform1>>
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* <<ml-configuring-transform2>>
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* <<ml-configuring-transform3>>
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* <<ml-configuring-transform4>>
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* <<ml-configuring-transform5>>
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* <<ml-configuring-transform6>>
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* <<ml-configuring-transform7>>
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* <<ml-configuring-transform8>>
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* <<ml-configuring-transform9>>
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The following indices APIs create and add content to an index that is used in
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subsequent examples:
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[source,js]
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----------------------------------
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PUT /my_index
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{
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"mappings":{
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"my_type":{
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"properties": {
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"@timestamp": {
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"type": "date"
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},
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"aborted_count": {
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"type": "long"
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},
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"another_field": {
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"type": "keyword" <1>
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},
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"clientip": {
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"type": "keyword"
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},
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"coords": {
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"properties": {
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"lat": {
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"type": "keyword"
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},
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"lon": {
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"type": "keyword"
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}
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}
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},
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"error_count": {
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"type": "long"
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},
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"query": {
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"type": "keyword"
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},
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"some_field": {
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"type": "keyword"
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},
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"tokenstring1":{
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"type":"keyword"
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},
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"tokenstring2":{
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"type":"keyword"
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},
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"tokenstring3":{
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"type":"keyword"
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}
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}
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}
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}
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}
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PUT /my_index/my_type/1
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{
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"@timestamp":"2017-03-23T13:00:00",
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"error_count":36320,
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"aborted_count":4156,
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"some_field":"JOE",
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"another_field":"SMITH ",
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"tokenstring1":"foo-bar-baz",
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"tokenstring2":"foo bar baz",
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"tokenstring3":"foo-bar-19",
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"query":"www.ml.elastic.co",
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"clientip":"123.456.78.900",
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"coords": {
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"lat" : 41.44,
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"lon":90.5
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}
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}
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----------------------------------
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// CONSOLE
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// TESTSETUP
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<1> In this example, string fields are mapped as `keyword` fields to support
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aggregation. If you want both a full text (`text`) and a keyword (`keyword`)
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version of the same field, use multi-fields. For more information, see
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{ref}/multi-fields.html[fields].
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[[ml-configuring-transform1]]
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.Example 1: Adding two numerical fields
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[source,js]
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----------------------------------
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PUT _xpack/ml/anomaly_detectors/test1
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{
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"analysis_config":{
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"bucket_span": "10m",
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"detectors":[
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{
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"function":"mean",
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"field_name": "total_error_count", <1>
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"detector_description": "Custom script field transformation"
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}
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]
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},
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"data_description": {
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"time_field":"@timestamp",
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"time_format":"epoch_ms"
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}
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}
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PUT _xpack/ml/datafeeds/datafeed-test1
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{
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"job_id": "test1",
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"indices": ["my_index"],
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"types": ["my_type"],
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"query": {
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"match_all": {
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"boost": 1
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}
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},
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"script_fields": {
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"total_error_count": { <2>
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"script": {
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"lang": "expression",
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"inline": "doc['error_count'].value + doc['aborted_count'].value"
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}
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}
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}
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}
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----------------------------------
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// CONSOLE
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// TEST[continued]
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<1> A script field named `total_error_count` is referenced in the detector
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within the job.
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<2> The script field is defined in the {dfeed}.
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This `test1` job contains a detector that uses a script field in a mean analysis
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function. The `datafeed-test1` {dfeed} defines the script field. It contains a
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script that adds two fields in the document to produce a "total" error count.
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The syntax for the `script_fields` property is identical to that used by {es}.
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For more information, see {ref}/search-request-script-fields.html[Script Fields].
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You can preview the contents of the {dfeed} by using the following API:
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[source,js]
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----------------------------------
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GET _xpack/ml/datafeeds/datafeed-test1/_preview
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----------------------------------
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// CONSOLE
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// TEST[continued]
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In this example, the API returns the following results, which contain a sum of
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the `error_count` and `aborted_count` values:
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[source,js]
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----------------------------------
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[
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{
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"@timestamp": 1490274000000,
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"total_error_count": 40476
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}
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]
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----------------------------------
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// TESTRESPONSE
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NOTE: This example demonstrates how to use script fields, but it contains
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insufficient data to generate meaningful results. For a full demonstration of
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how to create jobs with sample data, see <<ml-getting-started>>.
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You can alternatively use {kib} to create an advanced job that uses script
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fields. To add the `script_fields` property to your {dfeed}, you must use the
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**Edit JSON** tab. For example:
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[role="screenshot"]
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image::images/ml-scriptfields.jpg[Adding script fields to a {dfeed} in {kib}]
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[[ml-configuring-transform-examples]]
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==== Common Script Field Examples
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While the possibilities are limitless, there are a number of common scenarios
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where you might use script fields in your {dfeeds}.
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[NOTE]
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===============================
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Some of these examples use regular expressions. By default, regular
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expressions are disabled because they circumvent the protection that Painless
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provides against long running and memory hungry scripts. For more information,
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see {ref}/modules-scripting-painless.html[Painless Scripting Language].
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Machine learning analysis is case sensitive. For example, "John" is considered
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to be different than "john". This is one reason you might consider using scripts
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that convert your strings to upper or lowercase letters.
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===============================
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[[ml-configuring-transform2]]
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.Example 2: Concatenating strings
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[source,js]
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--------------------------------------------------
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PUT _xpack/ml/anomaly_detectors/test2
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{
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"analysis_config":{
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"bucket_span": "10m",
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"detectors":[
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{
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"function":"low_info_content",
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"field_name":"my_script_field", <1>
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"detector_description": "Custom script field transformation"
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}
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]
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},
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"data_description": {
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"time_field":"@timestamp",
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"time_format":"epoch_ms"
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}
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}
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PUT _xpack/ml/datafeeds/datafeed-test2
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{
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"job_id": "test2",
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"indices": ["my_index"],
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"types": ["my_type"],
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"query": {
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"match_all": {
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"boost": 1
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}
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},
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"script_fields": {
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"my_script_field": {
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"script": {
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"lang": "painless",
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"inline": "doc['some_field'].value + '_' + doc['another_field'].value" <2>
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}
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}
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}
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}
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GET _xpack/ml/datafeeds/datafeed-test2/_preview
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> The script field has a rather generic name in this case, since it will
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be used for various tests in the subsequent examples.
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<2> The script field uses the plus (+) operator to concatenate strings.
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The preview {dfeed} API returns the following results, which show that "JOE"
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and "SMITH " have been concatenated and an underscore was added:
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[source,js]
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----------------------------------
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[
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{
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"@timestamp": 1490274000000,
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"my_script_field": "JOE_SMITH "
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}
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]
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----------------------------------
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// TESTRESPONSE
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[[ml-configuring-transform3]]
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.Example 3: Trimming strings
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[source,js]
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--------------------------------------------------
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POST _xpack/ml/datafeeds/datafeed-test2/_update
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{
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"script_fields": {
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"my_script_field": {
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"script": {
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"lang": "painless",
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"inline": "doc['another_field'].value.trim()" <1>
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}
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}
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}
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}
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GET _xpack/ml/datafeeds/datafeed-test2/_preview
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> This script field uses the `trim()` function to trim extra white space from a
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string.
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The preview {dfeed} API returns the following results, which show that "SMITH "
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has been trimmed to "SMITH":
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[source,js]
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----------------------------------
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[
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{
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"@timestamp": 1490274000000,
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"my_script_field": "SMITH"
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}
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]
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----------------------------------
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// TESTRESPONSE
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[[ml-configuring-transform4]]
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.Example 4: Converting strings to lowercase
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[source,js]
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--------------------------------------------------
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POST _xpack/ml/datafeeds/datafeed-test2/_update
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{
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"script_fields": {
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"my_script_field": {
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"script": {
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"lang": "painless",
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"inline": "doc['some_field'].value.toLowerCase()" <1>
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}
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}
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}
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}
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GET _xpack/ml/datafeeds/datafeed-test2/_preview
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> This script field uses the `toLowerCase` function to convert a string to all
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lowercase letters. Likewise, you can use the `toUpperCase{}` function to convert
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a string to uppercase letters.
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The preview {dfeed} API returns the following results, which show that "JOE"
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has been converted to "joe":
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[source,js]
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----------------------------------
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[
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{
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"@timestamp": 1490274000000,
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"my_script_field": "joe"
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}
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]
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----------------------------------
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// TESTRESPONSE
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[[ml-configuring-transform5]]
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.Example 5: Converting strings to mixed case formats
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[source,js]
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--------------------------------------------------
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POST _xpack/ml/datafeeds/datafeed-test2/_update
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{
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"script_fields": {
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"my_script_field": {
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"script": {
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"lang": "painless",
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"inline": "doc['some_field'].value.substring(0, 1).toUpperCase() + doc['some_field'].value.substring(1).toLowerCase()" <1>
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}
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}
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}
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}
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GET _xpack/ml/datafeeds/datafeed-test2/_preview
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> This script field is a more complicated example of case manipulation. It uses
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the `subString()` function to capitalize the first letter of a string and
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converts the remaining characters to lowercase.
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The preview {dfeed} API returns the following results, which show that "JOE"
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has been converted to "Joe":
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[source,js]
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----------------------------------
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[
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{
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"@timestamp": 1490274000000,
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"my_script_field": "Joe"
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}
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]
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----------------------------------
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// TESTRESPONSE
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[[ml-configuring-transform6]]
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.Example 6: Replacing tokens
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[source,js]
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--------------------------------------------------
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POST _xpack/ml/datafeeds/datafeed-test2/_update
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{
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"script_fields": {
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"my_script_field": {
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"script": {
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"lang": "painless",
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"inline": "/\\s/.matcher(doc['tokenstring2'].value).replaceAll('_')" <1>
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}
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}
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}
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}
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GET _xpack/ml/datafeeds/datafeed-test2/_preview
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> This script field uses regular expressions to replace white
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space with underscores.
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The preview {dfeed} API returns the following results, which show that
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"foo bar baz" has been converted to "foo_bar_baz":
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[source,js]
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----------------------------------
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[
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{
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"@timestamp": 1490274000000,
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"my_script_field": "foo_bar_baz"
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}
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]
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----------------------------------
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// TESTRESPONSE
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[[ml-configuring-transform7]]
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.Example 7: Regular expression matching and concatenation
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[source,js]
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--------------------------------------------------
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POST _xpack/ml/datafeeds/datafeed-test2/_update
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{
|
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"script_fields": {
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"my_script_field": {
|
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"script": {
|
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"lang": "painless",
|
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"inline": "def m = /(.*)-bar-([0-9][0-9])/.matcher(doc['tokenstring3'].value); return m.find() ? m.group(1) + '_' + m.group(2) : '';" <1>
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}
|
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}
|
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}
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}
|
||||
|
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GET _xpack/ml/datafeeds/datafeed-test2/_preview
|
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> This script field looks for a specific regular expression pattern and emits the
|
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matched groups as a concatenated string. If no match is found, it emits an empty
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string.
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|
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The preview {dfeed} API returns the following results, which show that
|
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"foo-bar-19" has been converted to "foo_19":
|
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|
||||
[source,js]
|
||||
----------------------------------
|
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[
|
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{
|
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"@timestamp": 1490274000000,
|
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"my_script_field": "foo_19"
|
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}
|
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]
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----------------------------------
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// TESTRESPONSE
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[[ml-configuring-transform8]]
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.Example 8: Splitting strings by domain name
|
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[source,js]
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--------------------------------------------------
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PUT _xpack/ml/anomaly_detectors/test3
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{
|
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"description":"DNS tunneling",
|
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"analysis_config":{
|
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"bucket_span": "30m",
|
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"influencers": ["clientip","hrd"],
|
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"detectors":[
|
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{
|
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"function":"high_info_content",
|
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"field_name": "sub",
|
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"over_field_name": "hrd",
|
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"exclude_frequent":"all"
|
||||
}
|
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]
|
||||
},
|
||||
"data_description": {
|
||||
"time_field":"@timestamp",
|
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"time_format":"epoch_ms"
|
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}
|
||||
}
|
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|
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PUT _xpack/ml/datafeeds/datafeed-test3
|
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{
|
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"job_id": "test3",
|
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"indices": ["my_index"],
|
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"types": ["my_type"],
|
||||
"query": {
|
||||
"match_all": {
|
||||
"boost": 1
|
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}
|
||||
},
|
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"script_fields":{
|
||||
"sub":{
|
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"script":"return domainSplit(doc['query'].value, params).get(0);"
|
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},
|
||||
"hrd":{
|
||||
"script":"return domainSplit(doc['query'].value, params).get(1);"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
GET _xpack/ml/datafeeds/datafeed-test3/_preview
|
||||
--------------------------------------------------
|
||||
// CONSOLE
|
||||
// TEST[continued]
|
||||
|
||||
If you have a single field that contains a well-formed DNS domain name, you can
|
||||
use the `domainSplit()` function to split the string into its highest registered
|
||||
domain and the sub-domain, which is everything to the left of the highest
|
||||
registered domain. For example, the highest registered domain of
|
||||
`www.ml.elastic.co` is `elastic.co` and the sub-domain is `www.ml`. The
|
||||
`domainSplit()` function returns an array of two values: the first value is the
|
||||
subdomain; the second value is the highest registered domain.
|
||||
|
||||
NOTE: The `domainSplit()` function takes two arguments. The first argument is
|
||||
the string you want to split. The second argument is always `params`. This is a
|
||||
technical implementation detail related to how Painless operates internally.
|
||||
|
||||
The preview {dfeed} API returns the following results, which show that
|
||||
"www.ml.elastic.co" has been split into "elastic.co" and "www.ml":
|
||||
|
||||
[source,js]
|
||||
----------------------------------
|
||||
[
|
||||
{
|
||||
"@timestamp": 1490274000000,
|
||||
"clientip.keyword": "123.456.78.900",
|
||||
"hrd": "elastic.co",
|
||||
"sub": "www.ml"
|
||||
}
|
||||
]
|
||||
----------------------------------
|
||||
// TESTRESPONSE
|
||||
|
||||
[[ml-configuring-transform9]]
|
||||
.Example 9: Transforming geo_point data
|
||||
[source,js]
|
||||
--------------------------------------------------
|
||||
PUT _xpack/ml/anomaly_detectors/test4
|
||||
{
|
||||
"analysis_config":{
|
||||
"bucket_span": "10m",
|
||||
"detectors":[
|
||||
{
|
||||
"function":"lat_long",
|
||||
"field_name": "my_coordinates"
|
||||
}
|
||||
]
|
||||
},
|
||||
"data_description": {
|
||||
"time_field":"@timestamp",
|
||||
"time_format":"epoch_ms"
|
||||
}
|
||||
}
|
||||
|
||||
PUT _xpack/ml/datafeeds/datafeed-test4
|
||||
{
|
||||
"job_id": "test4",
|
||||
"indices": ["my_index"],
|
||||
"types": ["my_type"],
|
||||
"query": {
|
||||
"match_all": {
|
||||
"boost": 1
|
||||
}
|
||||
},
|
||||
"script_fields": {
|
||||
"my_coordinates": {
|
||||
"script": {
|
||||
"inline": "doc['coords.lat'].value + ',' + doc['coords.lon'].value",
|
||||
"lang": "painless"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
GET _xpack/ml/datafeeds/datafeed-test4/_preview
|
||||
--------------------------------------------------
|
||||
// CONSOLE
|
||||
// TEST[continued]
|
||||
|
||||
In {es}, location data can be stored in `geo_point` fields but this data type is
|
||||
not supported natively in {xpackml} analytics. This example of a script field
|
||||
transforms the data into an appropriate format. For more information,
|
||||
see <<ml-geo-functions>>.
|
||||
|
||||
The preview {dfeed} API returns the following results, which show that
|
||||
`41.44` and `90.5` have been combined into "41.44,90.5":
|
||||
|
||||
[source,js]
|
||||
----------------------------------
|
||||
[
|
||||
{
|
||||
"@timestamp": 1490274000000,
|
||||
"my_coordinates": "41.44,90.5"
|
||||
}
|
||||
]
|
||||
----------------------------------
|
||||
// TESTRESPONSE
|
||||
|
||||
////
|
||||
==== Configuring Script Fields in {dfeeds-cap}
|
||||
|
||||
//TO-DO: Add Kibana steps from
|
||||
//https://github.com/elastic/prelert-legacy/wiki/Transforming-data-with-script_fields#transforming-geo_point-data-to-a-workable-string-format
|
||||
////
|
||||
|
|
@ -48,24 +48,8 @@ A {dfeed} resource has the following properties:
|
|||
script fields to the {dfeed}.
|
||||
The <<ml-detectorconfig,detector configuration objects>> in a job can contain
|
||||
functions that use these script fields.
|
||||
For more information, see {ref}/search-request-script-fields.html[Script Fields].
|
||||
For example:
|
||||
+
|
||||
--
|
||||
[source,js]
|
||||
----------------------------------
|
||||
{
|
||||
"script_fields": {
|
||||
"total_error_count": {
|
||||
"script": {
|
||||
"lang": "painless",
|
||||
"source": "doc['error_count'].value + doc['aborted_count'].value"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
----------------------------------
|
||||
--
|
||||
For more information, see
|
||||
{xpack-ref}/ml-configuring-transform.html[Transforming Data With Script Fields].
|
||||
|
||||
`scroll_size`::
|
||||
(unsigned integer) The `size` parameter that is used in {es} searches.
|
||||
|
|
|
|||
Loading…
Reference in New Issue