honeymoose
/
OpenSearch
mirror of https://github.com/honeymoose/OpenSearch.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

[DOCS] Add ML geographic functions (elastic/x-pack-elasticsearch#1357) 

* [DOCS] Add ML geographic functions

* [DOCS] Add script_fields info to ML geo functions

* [DOCS] Remove summary count from ML geographic functions

* [DOCS] Added example title to geographic functions

* [DOCS] Remove list from ML geographic functions

Original commit: elastic/x-pack-elasticsearch@a8e495657f
This commit is contained in:
Lisa Cawley 2017-05-19 11:09:39 -07:00 committed by GitHub
parent 27b0af7eae
commit d72a8f8026
1 changed files with 64 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

74
docs/en/ml/functions/geo.asciidoc
View File

@ -1,23 +1,77 @@
[[ml-geo-functions]]
=== Geographic Functions
The {xpackml} features include the following geographic functions:
* `lat_long`
The geographic functions detect anomalies in the geographic location of the
input data.
The `field_name` that you supply must be a string of the form
`latitude,longitude`. The `latitude` and `longitude` must be in the range -180
to 180 and represent a point on the surface of the Earth.
The {xpackml} features include the following geographic function: `lat_long`.
[float]
[[ml-lat-long]]
==== Lat_long
////
The `lat_long` function detects anomalies in the geographic location of the
input data.
This function supports the following properties:
* `field_name` (required)
* `by_field_name` (optional)
* `over_field_name` (optional)
* `partition_field_name` (optional)
For more information about those properties,
see <<ml-detectorconfig,Detector Configuration Objects>>.
.Example 1: Analyzing transactions with the lat_long function
[source,js]
--------------------------------------------------
{
"function" : "lat_long",
"field_name" : "transactionCoordinates",
"by_field_name" : "creditCardNumber"
}
--------------------------------------------------
If you use this `lat_long` function in a detector in your job, it
detects anomalies where the geographic location of a credit card transaction is
unusual for a particular customer’s credit card. An anomaly might indicate fraud.
IMPORTANT: The `field_name` that you supply must be a single string that contains
two comma-separated numbers of the form `latitude,longitude`. The `latitude` and
`longitude` must be in the range -180 to 180 and represent a point on the
surface of the Earth.
For example, JSON data might contain the following transaction coordinates:
[source,js]
--------------------------------------------------
{ "function" : "lat_long", "fieldName" : "transactionCoordinates", "byFieldName" : "creditCardNumber" }
{
"time": 1460464275,
"transactionCoordinates": "40.7,-74.0",
"creditCardNumber": "1234123412341234"
}
--------------------------------------------------
////
In {es}, location data is likely to be stored in `geo_point` fields. For more
information, see {ref}/geo-point.html[Geo-point datatype]. This data type is not
supported natively in {xpackml} features. You can, however, use Painless scripts
in `script_fields` in your {dfeed} to transform the data into an appropriate
format. For example, the following Painless script transforms
`"coords": {"lat" : 41.44, "lon":90.5}` into `"lat-lon": "41.44,90.5"`:
[source,js]
--------------------------------------------------
{
"script_fields": {
"lat-lon": {
"script": {
"inline": "doc['coords'].lat + ',' + doc['coords'].lon",
"lang": "painless"
}
}
}
}
--------------------------------------------------
For more information about `script_fields`, see <<ml-datafeed-resource>>.