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.
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).
Adds a new datafeed config option, max_empty_searches,
that tells a datafeed that has never found any data to stop
itself and close its associated job after a certain number
of real-time searches have returned no data.
Backport of #47922
This commit adds two APIs that allow to pause and resume
CCR auto-follower patterns:
// pause auto-follower
POST /_ccr/auto_follow/my_pattern/pause
// resume auto-follower
POST /_ccr/auto_follow/my_pattern/resume
The ability to pause and resume auto-follow patterns can be
useful in some situations, including the rolling upgrades of
cluster using a bi-directional cross-cluster replication scheme
(see #46665).
This commit adds a new active flag to the AutoFollowPattern
and adapts the AutoCoordinator and AutoFollower classes so
that it stops to fetch remote's cluster state when all auto-follow
patterns associate to the remote cluster are paused.
When an auto-follower is paused, remote indices that match the
pattern are just ignored: they are not added to the pattern's
followed indices uids list that is maintained in the local cluster
state. This way, when the auto-follow pattern is resumed the
indices created in the remote cluster in the meantime will be
picked up again and added as new following indices. Indices
created and then deleted in the remote cluster will be ignored
as they won't be seen at all by the auto-follower pattern at
resume time.
Backport of #47510 for 7.x
Today the `elasticsearch-shard remove-corrupted-data` tool will only truncate a
translog it determines to be corrupt. However there may be other cases in which
it is desirable to truncate the translog, for instance if an operation in the
translog cannot be replayed for some reason other than corruption. This commit
adds a `--truncate-clean-translog` option to skip the corruption check on the
translog and blindly truncate it.
Clarifies not to set `cluster.initial_master_nodes` on nodes that are joining
an existing cluster.
Co-Authored-By: James Rodewig <james.rodewig@elastic.co>
The "Conditionals with the Pipeline Processor" incorrectly documents
how to create a pipeline of pipelines with a failure condition. The
example as-is will always execute the fail processor. The change here
updates the documentation to correct guard the fail processor with an
if condition.
* Add Snapshot Lifecycle Retention documentation
This commits adds API and general purpose documentation for SLM
retention.
Relates to #43663
* Fix docs tests
* Update default now that #47604 has been merged
* Update docs/reference/ilm/apis/slm-api.asciidoc
Co-Authored-By: Gordon Brown <gordon.brown@elastic.co>
* Update docs/reference/ilm/apis/slm-api.asciidoc
Co-Authored-By: Gordon Brown <gordon.brown@elastic.co>
* Update docs with feedback
Setting `cluster.routing.allocation.disk.include_relocations` to `false` is a
bad idea since it will lead to the kinds of overshoot that were otherwise fixed
in #46079. This commit deprecates this setting so it can be removed in the next
major release.
The example use of a scoring script was incorrectly using a filter
script query, which has no scoring, and thus no _score variable
avialable. This commit converts the example doc to using the newer
script_score query.
Adds the following parameters to `outlier_detection`:
- `compute_feature_influence` (boolean): whether to compute or not
feature influence scores
- `outlier_fraction` (double): the proportion of the data set assumed
to be outlying prior to running outlier detection
- `standardization_enabled` (boolean): whether to apply standardization
to the feature values
Backport of #47600
While function scores using scripts do allow explanations, they are only
creatable with an expert plugin. This commit improves the situation for
the newer script score query by adding the ability to set the
explanation from the script itself.
To set the explanation, a user would check for `explanation != null` to
indicate an explanation is needed, and then call
`explanation.set("some description")`.
The warning section above the example tells that index name has to end with the digits but the example itself uses index name without digits which is confusing.
* [DOCS] Adds examples to the PUT dfa and the evaluate dfa APIs.
* [DOCS] Removes extra lines from examples.
* Update docs/reference/ml/df-analytics/apis/evaluate-dfanalytics.asciidoc
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
* Update docs/reference/ml/df-analytics/apis/put-dfanalytics.asciidoc
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
* [DOCS] Explains examples.
We do mention that rolling back an upgrade requires a restore from a snapshot,
but it's hidden at the bottom of the "preparing to upgrade" instructions on a
different page from the actual upgrade instructions. This commit duplicates the
preparatory instructions onto the pages containing the actual upgrade
instructions and rewords the point about rollbacks a bit.
DATE_PART(<datetime unit>, <date/datetime>) is a function that allows
the user to extract the specified unit from a date/datetime field
similar to the EXTRACT (<datetime unit> FROM <date/datetime>) but
with different names and aliases for the units and it also provides more
options like `DATE_PART('tzoffset', datetimeField)`.
Implemented following the SQL server's spec: https://docs.microsoft.com/en-us/sql/t-sql/functions/datepart-transact-sql?view=sql-server-2017
with the difference that the <datetime unit> argument is either a
literal single quoted string or gets a value from a table field, whereas
in SQL server keywords are used (unquoted identifiers) and it's not
possible to use a value coming for a table column.
Closes: #46372
(cherry picked from commit ead743d3579eb753fd314d4a58fae205e465d72e)
Currently the policy config is placed directly in the json object
of the toplevel `policies` array field. For example:
```
{
"policies": [
{
"match": {
"name" : "my-policy",
"indices" : ["users"],
"match_field" : "email",
"enrich_fields" : [
"first_name",
"last_name",
"city",
"zip",
"state"
]
}
}
]
}
```
This change adds a `config` field in each policy json object:
```
{
"policies": [
{
"config": {
"match": {
"name" : "my-policy",
"indices" : ["users"],
"match_field" : "email",
"enrich_fields" : [
"first_name",
"last_name",
"city",
"zip",
"state"
]
}
}
}
]
}
```
This allows us in the future to add other information about policies
in the get policy api response.
The UI will consume this API to build an overview of all policies.
The UI may in the future include additional information about a policy
and the plan is to include that in the get policy api, so that this
information can be gathered in a single api call.
An example of the information that is likely to be added is:
* Last policy execution time
* The status of a policy (executing, executed, unexecuted)
* Information about the last failure if exists
To be on the safe side in terms of use cases also add the alias
DATETRUNC to the DATE_TRUNC function.
Follows: #46473
(cherry picked from commit 9ac223cb1fc66486f86e218fa785a32b61e9bacc)
Enables support for Cartesian geometries shape type. We still need to
decide how to handle the distance function since it is currently using
the haversine distance formula and returns results in meters, which
doesn't make any sense for Cartesian geometries.
Closes#46412
Relates to #43644
David Roberts
Martijn van Groningen
Gordon Brown
James Rodewig
Tanguy Leroux
David Turner
Marios Trivyzas
István Zoltán Szabó
Jim Ferenczi
Florian Kelbert
Andrei Stefan
Jake Landis
Ioannis Kakavas
Lee Hinman
Hendrik Muhs
Ryan Ernst
Lisa Cawley
Dimitris Athanasiou
Przemyslaw Gomulka
debadair
Mark Tozzi
Paweł Krześniak
AndyHunt66
Russ Cam
Robin Clarke
Andrew Naguib
Yannick Welsch
Colin Goodheart-Smithe
Pius
Nicole Albee
Igor Motov