[ML] Categorization should take notice of hard_limit memory status

[droberts195]

If a job's memory status goes to hard_limit then we stop modelling new entities in anomaly detection. However, categorization can still create new categories. If there are many new categories then this can cause a very significant overrun of the configured memory limit.

Some possibilities:

• When a job is in hard_limit status no new categories should be created. The input document that could not be categorized should be discarded as it cannot take part in anomaly detection without a category. A new statistic in the model size stats should be incremented to record the number of documents discarded for this reason.
• When a job is in soft_limit status, we stop recording examples for the category.