[ML] Add unsigned_long support to data frame analytics

[droberts195]

A new field type unsigned_long was added to Elasticsearch in elastic/elasticsearch#60050 and core Kibana in #81115. This is a new type of numeric field. The necessary changes for the ML Java data frame analytics code to work with unsigned_long were made in elastic/elasticsearch#64066. Given that this type is supported in core Kibana now it could be argued that it is now a bug that it's not supported in the ML UI.

I did some testing with the ML Java changes combined with the following Kibana patch:

diff --git a/x-pack/plugins/ml/public/application/data_frame_analytics/common/fields.ts b/x-pack/plugins/ml/public/application/data_frame_analytics/common/fields.ts
index c606cbd1cc1..561f2f12a3f 100644
--- a/x-pack/plugins/ml/public/application/data_frame_analytics/common/fields.ts
+++ b/x-pack/plugins/ml/public/application/data_frame_analytics/common/fields.ts
@@ -33,6 +33,7 @@ export const MAX_COLUMNS = 10;
 export const DEFAULT_REGRESSION_COLUMNS = 8;
 
 export const BASIC_NUMERICAL_TYPES = new Set([
+  ES_FIELD_TYPES.UNSIGNED_LONG,
   ES_FIELD_TYPES.LONG,
   ES_FIELD_TYPES.INTEGER,
   ES_FIELD_TYPES.SHORT,

With those changes the unsigned_long fields showed up as expected when creating a new data frame analytics job, and it was possible to run that job and view the results. However, in the results grid the unsigned_long fields did not show up. So it seems that some other change is also needed. However, hopefully it is not a massive amount of work to add support for unsigned_long to the data frame analytics UI.

[elasticmachine]

Pinging @elastic/ml-ui (:ml)

[LeeDr]

I'll just add a note and screenshot from the testing I did on 7.10.0. I created an index pattern with 4 docs which have an unsigned long field "my_counter" which shows a value rounded or truncated to the precision Kibana supports, and also has a string representation of the actual value "string_counter". The values of "my_counter" do appear in the grid view;

But when I click the Outlier detection selection I get an error.

Request URL: http://localhost:5601/api/ml/data_frame/analytics/_explain
Response: {"statusCode":500,"error":"Internal Server Error","message":"exception"}