[ml] supporting date_nanos as timestamp for the input

[jguay]

At present, trying to use a field of datatype date_nanos will return error :

'fieldName' cannot be used as the time-field because it's not a valid field of type 'date'.

Some indices may only use timestamps with precision requiring datatype date_nanos, these indices cannot be used for input for machine learning jobs (unless another field of datatype date is added)

Note this feature request is limited to the input - it not related to being able to process data in nano seconds or below current second bucket_span raised in 644

[elasticmachine]

Pinging @elastic/ml-core (:ml)

[davidkyle]

Using the ml APIs directly rather than kibana it is possible to create a run a job on data with a time field of type date_nanos I have tested this on version 7.5.

The error mentioned above comes from the UI, I've raised elastic/kibana#52921 in place of this.

[sophiec20]

Re-opening. As it stands with 7.6 and prior, using timestamps containing data with precision of date_nanos is not yet supported and will be documented as a limitation. Both UI and back end work is required to add this functionality.

[droberts195]

Using the ml APIs directly rather than kibana it is possible to create a run a job on data with a time field of type date_nanos

It turns out this was only true if the extra precision was not used. In other words, a datafeed would work fine on the date_nanos type providing every timestamp was an exact number of milliseconds since the epoch, i.e. nanoseconds since the epoch was a multiple of 1000000.

#51180 fixes the case of a fractional number of milliseconds since the epoch. (And note that the smallest possible ML bucket_span remains 1 second, and anomaly detection will still operate on summary statistics at the bucket level regardless of the underlying timestamp accuracy.)

[droberts195]

I believe this is fixed in 7.7 and above by elastic/kibana#59017