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.
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 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.
Currently, partial snapshots will eventually build up unless they are
manually deleted. Partial snapshots may be useful if there is not a more
recent successful snapshot, but should eventually be deleted if they are
no longer useful.
With this change, partial snapshots are deleted using the following
strategy: PARTIAL snapshots will be kept until the configured
expire_after period has passed, if present, and then be deleted. If
there is no configured expire_after in the retention policy, then they
will be deleted if there is at least one more recent successful snapshot
from this policy (as they may otherwise be useful for troubleshooting
purposes). Partial snapshots are not counted towards either min_count or
max_count.
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
Joda was using ResolverStyle.STRICT when parsing. This means that date will be validated to be a correct year, year-of-month, day-of-month
However, we also want to make it works with Year-Of-Era as Joda used to, hence custom temporalquery.localdate in DateFormatters.from
Within DateFormatters we use the correct uuuu year instead of yyyy year of era
worth noting: if yyyy(without an era) is used in code, the parsing result will be a TemporalAccessor which will fail to be converted into LocalDate. We mostly use DateFormatters.from so this takes care of this. If possible the uuuu format should be used.
Changes the execution logic to create a new task using the execute request,
and attaches the new task to the policy runner to be updated. Also, a new
response is now returned from the execute api, which contains either the task
id of the execution, or the completed status of the run. The fields are mutually
exclusive to make it easier to discern what type of response it is.
rename internal indexes of transform plugin
- rename audit index and create an alias for accessing it, BWC: add an alias for old indexes to
keep them working, kibana UI will switch to use the read alias
- rename config index and provide BWC to read from old and new ones
* Separate SLM stop/start/status API from ILM
This separates a start/stop/status API for SLM from being tied to ILM's
operation mode. These APIs look like:
```
POST /_slm/stop
POST /_slm/start
GET /_slm/status
```
This allows administrators to have fine-grained control over preventing
periodic snapshots and deletions while performing cluster maintenance.
Relates to #43663
* Allow going from RUNNING to STOPPED
* Align with the OperationMode rules
* Fix slmStopping method
* Make OperationModeUpdateTask constructor private
* Wipe snapshots better in test
Failed snapshots will eventually build up unless they are deleted. While
failures may not take up much space, they add noise to the list of
snapshots and it's desirable to remove them when they are no longer
useful.
With this change, failed snapshots are deleted using the following
strategy: `FAILED` snapshots will be kept until the configured
`expire_after` period has passed, if present, and then be deleted. If
there is no configured `expire_after` in the retention policy, then they
will be deleted if there is at least one more recent successful snapshot
from this policy (as they may otherwise be useful for troubleshooting
purposes). Failed snapshots are not counted towards either `min_count`
or `max_count`.
When exceptions could be returned from another node, the exception
might be wrapped in a `RemoteTransportException`. In places where
we handled specific exceptions using `instanceof` we ought to unwrap
the cause first.
This commit attempts to fix this issue after searching code in the ML
plugin.
Backport of #47676
this commit introduces a geo-match enrich processor that looks up a specific
`geo_point` field in the enrich-index for all entries that have a geo_shape match field
that meets some specific relation criteria with the input field.
For example, the enrich index may contain documents with zipcodes and their respective
geo_shape. Ingesting documents with a geo_point field can be enriched with which zipcode
they associate according to which shape they are contained within.
this commit also refactors some of the MatchProcessor by moving a lot of the shared code to
AbstractEnrichProcessor.
Closes#42639.
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
Use case:
User with `create_doc` index privilege will be allowed to only index new documents
either via Index API or Bulk API.
There are two cases that we need to think:
- **User indexing a new document without specifying an Id.**
For this ES auto generates an Id and now ES version 7.5.0 onwards defaults to `op_type` `create` we just need to authorize on the `op_type`.
- **User indexing a new document with an Id.**
This is problematic as we do not know whether a document with Id exists or not.
If the `op_type` is `create` then we can assume the user is trying to add a document, if it exists it is going to throw an error from the index engine.
Given these both cases, we can safely authorize based on the `op_type` value. If the value is `create` then the user with `create_doc` privilege is authorized to index new documents.
In the `AuthorizationService` when authorizing a bulk request, we check the implied action.
This code changes that to append the `:op_type/index` or `:op_type/create`
to indicate the implied index action.
This commit adds support to retrieve all API keys if the authenticated
user is authorized to do so.
This removes the restriction of specifying one of the
parameters (like id, name, username and/or realm name)
when the `owner` is set to `false`.
Closes#46887
An index with an ILM policy that has a rollover action in one of the
phases was rolled over when the ILM conditions dictated regardless if
it was already rolled over (eg. manually after modifying an index
template in order to force the creation of a new index that uses the new
mappings).
This changes this behaviour and has ILM check if the index it's about to
roll has not been rolled over in the meantime.
(cherry picked from commit 37d6106feeb9f9369519117c88a9e7e30f3ac797)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This adds a default for the `slm.retention_schedule` setting, setting it
to `0 30 1 * * ?` which is 1:30am every day.
Having retention unset meant that it would never be invoked and clean up
snapshots. We determined it would be better to have a default than never
to be run. When coming to a decision, we weighed the option of an
absolute time (such as 1:30am) versus a periodic invocation (like every
12 hours). In the end we decided on the absolute time because it has
better predictability and consistency than a periodic invocation, which
would rely on when the master node were elected or restarted.
Relates to #43663
When an ML job runs the memory required can be
broken down into:
1. Memory required to load the executable code
2. Instrumented model memory
3. Other memory used by the job's main process or
ancilliary processes that is not instrumented
Previously we added a simple fixed overhead to
account for 1 and 3. This was 100MB for anomaly
detection jobs (large because of the completely
uninstrumented categorization function and
normalize process), and 20MB for data frame
analytics jobs.
However, this was an oversimplification because
the executable code only needs to be loaded once
per machine. Also the 100MB overhead for anomaly
detection jobs was probably too high in most cases
because categorization and normalization don't use
_that_ much memory.
This PR therefore changes the calculation of memory
requirements as follows:
1. A per-node overhead of 30MB for _only_ the first
job of any type to be run on a given node - this
is to account for loading the executable code
2. The established model memory (if applicable) or
model memory limit of the job
3. A per-job overhead of 10MB for anomaly detection
jobs and 5MB for data frame analytics jobs, to
account for the uninstrumented memory usage
This change will enable more jobs to be run on the
same node. It will be particularly beneficial when
there are a large number of small jobs. It will
have less of an effect when there are a small number
of large jobs.
* Remove eclipse conditionals
We used to have some meta projects with a `-test` prefix because
historically eclipse could not distinguish between test and main
source-sets and could only use a single classpath.
This is no longer the case for the past few Eclipse versions.
This PR adds the necessary configuration to correctly categorize source
folders and libraries.
With this change eclipse can import projects, and the visibility rules
are correct e.x. auto compete doesn't offer classes from test code or
`testCompile` dependencies when editing classes in `main`.
Unfortunately the cyclic dependency detection in Eclipse doesn't seem to
take the difference between test and non test source sets into account,
but since we are checking this in Gradle anyhow, it's safe to set to
`warning` in the settings. Unfortunately there is no setting to ignore
it.
This might cause problems when building since Eclipse will probably not
know the right order to build things in so more wirk might be necesarry.
* Add API to execute SLM retention on-demand (#47405)
This is a backport of #47405
This commit adds the `/_slm/_execute_retention` API endpoint. This
endpoint kicks off SLM retention and then returns immediately.
This in particular allows us to run retention without scheduling it
(for entirely manual invocation) or perform a one-off cleanup.
This commit also includes HLRC for the new API, and fixes an issue
in SLMSnapshotBlockingIntegTests where retention invoked prior to the
test completing could resurrect an index the internal test cluster
cleanup had already deleted.
Resolves#46508
Relates to #43663
* Fix AllocationRoutedStepTests.testConditionMetOnlyOneCopyAllocated
These tests were using randomly generated includes/excludes/requires for
routing, however, it was possible to generate mutually exclusive
allocation settings (about 1 out of 50,000 times for my runs).
This splits the test into three different tests, and removes the
randomization (it doesn't add anything to the testing here) to fix the
issue.
Resolves#47142
While it seemed like the PUT data frame analytics action did not
have to be a master node action as the config is stored in an index
rather than the cluster state, there are other subtle nuances which
make it worthwhile to convert it. In particular, it helps maintain
order of execution for put actions which are anyhow user driven and
are expected to have low volume.
This commit converts `TransportPutDataFrameAnalyticsAction` from
a handled transport action to a master node action.
Note this means that the action might fail in a mixed cluster
but as the API is still experimental and not widely used there will
be few moments more suitable to make this change than now.
Bulk requests currently do not allow adding "create" actions with auto-generated IDs.
This commit allows using the optype CREATE for append-only indexing operations. This is
mainly the user facing aspect of it.
Due to #47003 many clusters will have built up a
large backlog of expired results. On upgrading to
a version where that bug is fixed users could find
that the first ML daily maintenance task deletes
a very large amount of documents.
This change introduces throttling to the
delete-by-query that the ML daily maintenance uses
to delete expired results to limit it to deleting an
average 200 documents per second. (There is no
throttling for state/forecast documents as these
are expected to be lower volume.)
Additionally a rough time limit of 8 hours is applied
to the whole delete expired data action. (This is only
rough as it won't stop part way through a single
operation - it only checks the timeout between
operations.)
Relates #47103
This commit restores the model state if available in data
frame analytics jobs.
In addition, this changes the start API so that a stopped job
can be restarted. As we now store the progress in the state index
when the task is stopped, we can use it to determine what state
the job was in when it got stopped.
Note that in order to be able to distinguish between a job
that runs for the first time and another that is restarting,
we ensure reindexing progress is reported to be at least 1
for a running task.
Due to a regression bug the metadata Active Directory realm
setting is ignored (it works correctly for the LDAP realm type).
This commit redresses it.
Closes#45848
* [ML][Inference] adding .ml-inference* index and storage (#47267)
* [ML][Inference] adding .ml-inference* index and storage
* Addressing PR comments
* Allowing null definition, adding validation tests for model config
* fixing line length
* adjusting for backport
Przemysław Witek
Martijn van Groningen
Benjamin Trent
David Roberts
James Baiera
Gordon Brown
Ioannis Kakavas
Tanguy Leroux
Yogesh Gaikwad
Przemyslaw Gomulka
Chris Roberson
Hendrik Muhs
Lee Hinman
Dimitris Athanasiou
Tal Levy
Andrei Dan
Alpar Torok
Yannick Welsch
Albert Zaharovits