Up to now a job update that reduces the model memory limit
was not allowed. However, there could definitely be cases
where reducing the limit is necessary and reasonable.
This commit makes it possible to decrease the limit as long
as it does not go below the current memory usage. We obtain
the latter from the model size stats.
The conditions under which updating the model_memory_limit
is not allowed are now:
- when the job is open
- latest model_size_stats.model_bytes < new value
relates elastic/x-pack-elasticsearch#2461
Original commit: elastic/x-pack-elasticsearch@5b35923590
Analysis limits contain settings that affect the resources
used by ML jobs. Those limits always take place. However,
explictly setting them is not required as they have reasonable
defaults. For a long time those defaults lived on the c++ side.
The job could just not have any explicit limits and that meant
defaults would be used at the c++ side. This has the disadvantage
that it is not obvious to the users what these settings are set to.
Additionally, users might not be aware of the settings existence.
On top of that, since 6.1, the default model_memory_limit was lowered
from 4GB to 1GB. For BWC, this meant that jobs where model_memory_limit
is null, the default of 4GB applies. Jobs that were created from 6.1
onwards, contain an explicit setting for model_memory_limit, which is
1GB unless the user sets it differently. This adds additional confusion.
This commit makes analysis limits an always explicit setting on the job.
Regardless of whether the user sets custom limits or not, the job object
(and response) will contain the full analysis limits values.
The possibilities for interpretation of missing values are:
- the entire analysis_limits is null: this may only happen for jobs
created prior to 6.1. Thus we set the model_memory_limit to 4GB.
- analysis_limits are non-null but model_memory_limit is: this also
may only happen for jobs prior to 6.1. Again, we set memory limit to
4GB.
- model_memory_limit is non-null: this either means the user set an
explicit value or the job was created from 6.1 onwards and it has
the explicit default of 1GB. We simply keep the given value.
For categorization_examples_limit the default has always been 4, so
we fill that in when it's missing.
Finally, note that we still need to handle potential null values
for the situation of a mixed cluster.
Original commit: elastic/x-pack-elasticsearch@5b6994ef75
This adds a new Rollup module to XPack, which allows users to configure periodic "rollup jobs" to pre-aggregate data. That data is then available later for search through a special RollupSearch API, which mimics the DSL and functionality of regular search.
Rollups are used to drastically reduce the on-disk footprint of metric-based data (e.g. timestamped document with numeric and keyword fields). It can also be used to speed up aggregations over large datasets, since the rolled data will be considerably smaller and fewer documents to search.
The PR adds seven new endpoints to interact with Rollups; create/get/delete job, start/stop job, a capabilities API similar to field-caps, and a Rollup-enabled search.
Original commit: elastic/x-pack-elasticsearch@dcde91aacf
... yet support updates. This commit introduces a few changes of how
watches are put.
The GET Watch API will never return credentials like basic auth
passwords, but a placeholder instead now. If the watcher is enabled to
encrypt sensitive settings, then the original encrypted value is
returned otherwise a "::es_redacted::" place holder.
There have been several Put Watch API changes.
The API now internally uses the Update API and versioning. This has
several implications. First if no version is supplied, we assume an
initial creation. This will work as before, however if a credential is
marked as redacted we will reject storing the watch, so users do not
accidentally store the wrong watch.
The watch xcontent parser now has an additional methods to tell the
caller if redacted passwords have been found. Based on this information
an error can be thrown.
If the user now wants to store a watch that contains a password marked
as redacted, this password will not be part of the toXContent
representation of the watch and in combinatination with update request
the existing password will be merged in. If the encrypted password is
supplied this one will be stored.
The serialization for GetWatchResponse/PutWatchRequest has changed.
The version checks for this will be put into the 6.x branch.
The Watcher UI now needs specify the version, when it wants to store a
watch. This also prevents last-write-wins scenarios and is the reason
why the put/get watch response now contains the internal version.
relates elastic/x-pack-elasticsearch#3089
Original commit: elastic/x-pack-elasticsearch@bb63be9f79
This commit adds the ability to refresh tokens that have been obtained by the API using a refresh
token. Refresh tokens are one time use tokens that are valid for 24 hours. The tokens may be used
to get a new access and refresh token if the refresh token has not been invalidated or
already refreshed.
relates elastic/x-pack-elasticsearch#2595
Original commit: elastic/x-pack-elasticsearch@23435eb815
* [DOCS] Enabled code snippet testing for start datafeed API
* [DOCS] Added datafeed creation to build.gradle
Original commit: elastic/x-pack-elasticsearch@1acb452cf0
* [DOCS] Added ML forecast API
* [DOCS] Added forecast API to build.gradle
* [DOCS] Added forecast API example
* [DOCS] Fixed forecast API intro
* [DOCS] Addressed feedback on forecast API
* [DOCS] Added duration to forecast API
* [DOCS] Removed end time from forecast API
* [DOCS] Fixed gradle errors for forecast API
Original commit: elastic/x-pack-elasticsearch@db79e3d5bb
* [DOCS] Enabled code snippet testing for put datafeed API
* [DOCS] Addressed gradle errors in put datafeed API
* [DOCS] Added job creation test to build.gradle
Original commit: elastic/x-pack-elasticsearch@3548d920c7
For the purpose of getting this API consumed by our UI, returning
overall buckets that match the job's largest `bucket_span` can
result in too much data. The UI only ever displays a few buckets
in the swimlane. Their span depends on the time range selected and
the screen resolution, but it will only ever be a relatively
low number.
This PR adds the ability to aggregate overall buckets in a user
specified `bucket_span`. That `bucket_span` may be equal or
greater to the largest job's `bucket_span`. The `overall_score`
of the result overall buckets is the max score of the
corresponding overall buckets with a span equal to the job's
largest `bucket_span`.
The implementation is now chunking the bucket requests
as otherwise the aggregation would fail when too many buckets
are matching.
Original commit: elastic/x-pack-elasticsearch@981f7a40e5
Dimitris Athanasiou
Lisa Cawley
Zachary Tong
Zachary Tong
David Kyle
Luca Cavanna
Alexander Reelsen
Jay Modi
David Roberts
Russ Cam