This adds parsing an inference model as a possible
result of the analytics process. When we do parse such a model
we persist a `TrainedModelConfig` into the inference index
that contains additional metadata derived from the running job.
Today the docs say that the low watermark has no effect on any shards that have
never been allocated, but this is confusing. Here "shard" means "replication
group" not "shard copy" but this conflicts with the "never been allocated"
qualifier since one allocates shard copies and not replication groups.
This commit removes the misleading words. A newly-created replication group
remains newly-created until one of its copies is assigned, which might be quite
some time later, but it seems better to leave this implicit.
Previously when a numeric literal was enclosed in parentheses and then
negated, the negation was lost and the number was considered positive, e.g.:
`-(5)` was considered as `5` instead of `-5`
`- ( (1.28) )` was considered as `1.28` instead of `-1.28`
Fixes: #48009
(cherry picked from commit 4dee4bf3b34081062ba2e28ab8524a066812a180)
Audit messages are stored with millisecond timestamps. If two
messages have the same millisecond timestamp then asserting on
their order is impossible given the information available.
This PR changes the assertion on audit messages in the native
data frame analytics tests to assert that the expected audit
messages exist in any order.
Fixes#48035
which is backport merge and adds a new ingest processor, named enrich processor,
that allows document being ingested to be enriched with data from other indices.
Besides a new enrich processor, this PR adds several APIs to manage an enrich policy.
An enrich policy is in charge of making the data from other indices available to the enrich processor in an efficient manner.
Related to #32789
max_empty_searches = -1 in a datafeed update implies
max_empty_searches will be unset on the datafeed when
the update is applied. The isNoop() method needs to
take this -1 to null equivalence into account.
Previously, the safety check for the 2nd argument of the DateAddProcessor was
restricting it to Integer which was wrong since we allow all non-rational
numbers, so it's changed to a Number check as it's done in other cases.
Enhanced some tests regarding the check for an integer (non-rational
argument).
(cherry picked from commit 0516b6eaf5eb98fa5bd087c3fece80139a6b118e)
We were incorrectly handling `IOExceptions` thrown by
the `InputStream` side of the upload operation, resulting
in a `ClassCastException` as we expected to never get
`IOException` from the Azure SDK code but we do in practice.
This PR also sets an assertion on `markSupported` for the
streams used by the SDK as adding the test for this scenario
revealed that the SDK client would retry uploads for
non-mark-supporting streams on `IOException` in the `InputStream`.
This change adds:
- A new option, allow_lazy_open, to anomaly detection jobs
- A new option, allow_lazy_start, to data frame analytics jobs
Both work in the same way: they allow a job to be
opened/started even if no ML node exists that can
accommodate the job immediately. In this situation
the job waits in the opening/starting state until ML
node capacity is available. (The starting state for data
frame analytics jobs is new in this change.)
Additionally, the ML nightly maintenance tasks now
creates audit warnings for ML jobs that are unassigned.
This means that jobs that cannot be assigned to an ML
node for a very long time will show a yellow warning
triangle in the UI.
A final change is that it is now possible to close a job
that is not assigned to a node without using force.
This is because previously jobs that were open but
not assigned to a node were an aberration, whereas
after this change they'll be relatively common.
This commit adds HLRC support and documentation for the SLM Start and
Stop APIs, as well as updating existing documentation where appropriate.
This commit also ensures that the SLM APIs are properly included in the
HLRC documentation.
This PR adds the ability to run the enrich policy execution task in the background,
returning a task id instead of waiting for the completed operation.
Prior to this change the `target_field` would always be a json array
field in the document being ingested. This to take into account that
multiple enrich documents could be inserted into the `target_field`.
However the default `max_matches` is `1`. Meaning that by default
only a single enrich document would be added to `target_field` json
array field.
This commit changes this; if `max_matches` is set to `1` then the single
document would be added as a json object to the `target_field` and
if it is configured to a higher value then the enrich documents will be
added as a json array (even if a single enrich document happens to be
enriched).
Elastic cloud has a concept of a cloud Id. This Id is a base64 encoded
url, split up into a few parts. This commit allows the user to pass in a
cloud id now, which is translated to a HttpHost that is defined by the
encoded parts therein.
David Woods
Benjamin Trent
Michael Basnight
Mark Vieira
jimczi
James Rodewig
François-Clément Brossard
Marios Trivyzas
Przemysław Witek
Klemen Košir
Ian Danforth
Wilder Pereira
Alex Pang
David Roberts
Martijn van Groningen
Jack Conradson
Hendrik Muhs
Uwe Schindler
Alpar Torok
Armin Braun
Tanguy Leroux
Gordon Brown
James Baiera
Tim Brooks
Jake Landis