Adds a parameter `training_percent` to regression. The default
value is `100`. When the parameter is set to a value less than `100`,
from the rows that can be used for training (ie. those that have a
value for the dependent variable) we randomly choose whether to actually
use for training. This enables splitting the data into a training set and
the rest, usually called testing, validation or holdout set, which allows
for validating the model on data that have not been used for training.
Technically, the analytics process considers as training the data that
have a value for the dependent variable. Thus, when we decide a training
row is not going to be used for training, we simply clear the row's
dependent variable.
The native process requires that there be a non-zero number of rows to analyze. If the flag --rows 0 is passed to the executable, it throws and does not start.
When building the configuration for the process we should not start the native process if there are no rows.
Adding some logging to indicate what is occurring.
Previously, the stats API reports a progress percentage
for DF analytics tasks that are running and are in the
`reindexing` or `analyzing` state.
This means that when the task is `stopped` there is no progress
reported. Thus, one cannot distinguish between a task that never
run to one that completed.
In addition, there are blind spots in the progress reporting.
In particular, we do not account for when data is loaded into the
process. We also do not account for when results are written.
This commit addresses the above issues. It changes progress
to being a list of objects, each one describing the phase
and its progress as a percentage. We currently have 4 phases:
reindexing, loading_data, analyzing, writing_results.
When the task stops, progress is persisted as a document in the
state index. The stats API now reports progress from in-memory
if the task is running, or returns the persisted document
(if there is one).
Regression analysis support missing fields. Even more, it is expected
that the dependent variable has missing fields to the part of the
data frame that is not for training.
This commit allows to declare that an analysis supports missing values.
For such analysis, rows with missing values are not skipped. Instead,
they are written as normal with empty strings used for the missing values.
This also contains a fix to the integration test.
Closes#45425
* [ML] better handle empty results when evaluating regression
* adding new failure test to ml_security black list
* fixing equality check for regression results
* Reenable Integ Tests in native-multi-node-tests
* The tests broken here were likely fixed by #45463 => let's reenable them and see if things run fine again
* Relates #45405, #45455
This commit adds a first draft of a regression analysis
to data frame analytics. There is high probability that
the exact syntax might change.
This commit adds the new analysis type and its parameters as
well as appropriate validation. It also modifies the extractor
and the fields detector to be able to handle categorical fields
as regression analysis supports them.
If one tries to start a DF analytics job that has already run,
the result will be that the task will fail after reindexing the
dest index from the source index. The results of the prior run
will be gone and the task state is not properly set to failed
with the failure reason.
This commit improves the behavior in this scenario. First, we
set the task state to `failed` in a set of failures that were
missed. Second, a validation is added that if the destination
index exists, it must be empty.
As data frame rows with missing values for analyzed fields are skipped,
we can be more efficient by including a query that only picks documents
that have values for all analyzed fields. Besides improving the number
of documents we go through, we also provide a more accurate measurement
of how many rows we need which reduces the memory requirements.
This also adds an integration test that runs outlier detection on data
with missing fields.
* Switch from using docvalue_fields to extracting values from _source
where applicable. Doing this means parsing the _source and handling the
numbers parsing just like Elasticsearch is doing it when it's indexing
a document.
* This also introduces a minor limitation: aliases type of fields that
are NOT part of a tree of sub-fields will not be able to be retrieved
anymore. field_caps API doesn't shed any light into a field being an
alias or not and at _source parsing time there is no way to know if a
root field is an alias or not. Fields of the type "a.b.c.alias" can be
extracted from docvalue_fields, only if the field they point to can be
extracted from docvalue_fields. Also, not all fields in a hierarchy of
fields can be evaluated to being an alias.
(cherry picked from commit 8bf8a055e38f00df5f49c8d97f632f69d6e00c2c)
* Mute failing test
tracked in #44552
* mute EvilSecurityTests
tracking in #44558
* Fix line endings in ESJsonLayoutTests
* Mute failing ForecastIT test on windows
Tracking in #44609
* mute BasicRenormalizationIT.testDefaultRenormalization
tracked in #44613
* fix mute testDefaultRenormalization
* Increase busyWait timeout windows is slow
* Mute failure unconfigured node name
* mute x-pack internal cluster test windows
tracking #44610
* Mute JvmErgonomicsTests on windows
Tracking #44669
* mute SharedClusterSnapshotRestoreIT testParallelRestoreOperationsFromSingleSnapshot
Tracking #44671
* Mute NodeTests on Windows
Tracking #44256
* Add Snapshot Lifecycle Management (#43934)
* Add SnapshotLifecycleService and related CRUD APIs
This commit adds `SnapshotLifecycleService` as a new service under the ilm
plugin. This service handles snapshot lifecycle policies by scheduling based on
the policies defined schedule.
This also includes the get, put, and delete APIs for these policies
Relates to #38461
* Make scheduledJobIds return an immutable set
* Use Object.equals for SnapshotLifecyclePolicy
* Remove unneeded TODO
* Implement ToXContentFragment on SnapshotLifecyclePolicyItem
* Copy contents of the scheduledJobIds
* Handle snapshot lifecycle policy updates and deletions (#40062)
(Note this is a PR against the `snapshot-lifecycle-management` feature branch)
This adds logic to `SnapshotLifecycleService` to handle updates and deletes for
snapshot policies. Policies with incremented versions have the old policy
cancelled and the new one scheduled. Deleted policies have their schedules
cancelled when they are no longer present in the cluster state metadata.
Relates to #38461
* Take a snapshot for the policy when the SLM policy is triggered (#40383)
(This is a PR for the `snapshot-lifecycle-management` branch)
This commit fills in `SnapshotLifecycleTask` to actually perform the
snapshotting when the policy is triggered. Currently there is no handling of the
results (other than logging) as that will be added in subsequent work.
This also adds unit tests and an integration test that schedules a policy and
ensures that a snapshot is correctly taken.
Relates to #38461
* Record most recent snapshot policy success/failure (#40619)
Keeping a record of the results of the successes and failures will aid
troubleshooting of policies and make users more confident that their
snapshots are being taken as expected.
This is the first step toward writing history in a more permanent
fashion.
* Validate snapshot lifecycle policies (#40654)
(This is a PR against the `snapshot-lifecycle-management` branch)
With the commit, we now validate the content of snapshot lifecycle policies when
the policy is being created or updated. This checks for the validity of the id,
name, schedule, and repository. Additionally, cluster state is checked to ensure
that the repository exists prior to the lifecycle being added to the cluster
state.
Part of #38461
* Hook SLM into ILM's start and stop APIs (#40871)
(This pull request is for the `snapshot-lifecycle-management` branch)
This change allows the existing `/_ilm/stop` and `/_ilm/start` APIs to also
manage snapshot lifecycle scheduling. When ILM is stopped all scheduled jobs are
cancelled.
Relates to #38461
* Add tests for SnapshotLifecyclePolicyItem (#40912)
Adds serialization tests for SnapshotLifecyclePolicyItem.
* Fix improper import in build.gradle after master merge
* Add human readable version of modified date for snapshot lifecycle policy (#41035)
* Add human readable version of modified date for snapshot lifecycle policy
This small change changes it from:
```
...
"modified_date": 1554843903242,
...
```
To
```
...
"modified_date" : "2019-04-09T21:05:03.242Z",
"modified_date_millis" : 1554843903242,
...
```
Including the `"modified_date"` field when the `?human` field is used.
Relates to #38461
* Fix test
* Add API to execute SLM policy on demand (#41038)
This commit adds the ability to perform a snapshot on demand for a policy. This
can be useful to take a snapshot immediately prior to performing some sort of
maintenance.
```json
PUT /_ilm/snapshot/<policy>/_execute
```
And it returns the response with the generated snapshot name:
```json
{
"snapshot_name" : "production-snap-2019.04.09-rfyv3j9qreixkdbnfuw0ug"
}
```
Note that this does not allow waiting for the snapshot, and the snapshot could
still fail. It *does* record this information into the cluster state similar to
a regularly trigged SLM job.
Relates to #38461
* Add next_execution to SLM policy metadata (#41221)
* Add next_execution to SLM policy metadata
This adds the next time a snapshot lifecycle policy will be executed when
retriving a policy's metadata, for example:
```json
GET /_ilm/snapshot?human
{
"production" : {
"version" : 1,
"modified_date" : "2019-04-15T21:16:21.865Z",
"modified_date_millis" : 1555362981865,
"policy" : {
"name" : "<production-snap-{now/d}>",
"schedule" : "*/30 * * * * ?",
"repository" : "repo",
"config" : {
"indices" : [
"foo-*",
"important"
],
"ignore_unavailable" : true,
"include_global_state" : false
}
},
"next_execution" : "2019-04-15T21:16:30.000Z",
"next_execution_millis" : 1555362990000
},
"other" : {
"version" : 1,
"modified_date" : "2019-04-15T21:12:19.959Z",
"modified_date_millis" : 1555362739959,
"policy" : {
"name" : "<other-snap-{now/d}>",
"schedule" : "0 30 2 * * ?",
"repository" : "repo",
"config" : {
"indices" : [
"other"
],
"ignore_unavailable" : false,
"include_global_state" : true
}
},
"next_execution" : "2019-04-16T02:30:00.000Z",
"next_execution_millis" : 1555381800000
}
}
```
Relates to #38461
* Fix and enhance tests
* Figured out how to Cron
* Change SLM endpoint from /_ilm/* to /_slm/* (#41320)
This commit changes the endpoint for snapshot lifecycle management from:
```
GET /_ilm/snapshot/<policy>
```
to:
```
GET /_slm/policy/<policy>
```
It mimics the ILM path only using `slm` instead of `ilm`.
Relates to #38461
* Add initial documentation for SLM (#41510)
* Add initial documentation for SLM
This adds the initial documentation for snapshot lifecycle management.
It also includes the REST spec API json files since they're sort of
documentation.
Relates to #38461
* Add `manage_slm` and `read_slm` roles (#41607)
* Add `manage_slm` and `read_slm` roles
This adds two more built in roles -
`manage_slm` which has permission to perform any of the SLM actions, as well as
stopping, starting, and retrieving the operation status of ILM.
`read_slm` which has permission to retrieve snapshot lifecycle policies as well
as retrieving the operation status of ILM.
Relates to #38461
* Add execute to the test
* Fix ilm -> slm typo in test
* Record SLM history into an index (#41707)
It is useful to have a record of the actions that Snapshot Lifecycle
Management takes, especially for the purposes of alerting when a
snapshot fails or has not been taken successfully for a certain amount of
time.
This adds the infrastructure to record SLM actions into an index that
can be queried at leisure, along with a lifecycle policy so that this
history does not grow without bound.
Additionally,
SLM automatically setting up an index + lifecycle policy leads to
`index_lifecycle` custom metadata in the cluster state, which some of
the ML tests don't know how to deal with due to setting up custom
`NamedXContentRegistry`s. Watcher would cause the same problem, but it
is already disabled (for the same reason).
* High Level Rest Client support for SLM (#41767)
* High Level Rest Client support for SLM
This commit add HLRC support for SLM.
Relates to #38461
* Fill out documentation tests with tags
* Add more callouts and asciidoc for HLRC
* Update javadoc links to real locations
* Add security test testing SLM cluster privileges (#42678)
* Add security test testing SLM cluster privileges
This adds a test to `PermissionsIT` that uses the `manage_slm` and `read_slm`
cluster privileges.
Relates to #38461
* Don't redefine vars
* Add Getting Started Guide for SLM (#42878)
This commit adds a basic Getting Started Guide for SLM.
* Include SLM policy name in Snapshot metadata (#43132)
Keep track of which SLM policy in the metadata field of the Snapshots
taken by SLM. This allows users to more easily understand where the
snapshot came from, and will enable future SLM features such as
retention policies.
* Fix compilation after master merge
* [TEST] Move exception wrapping for devious exception throwing
Fixes an issue where an exception was created from one line and thrown in another.
* Fix SLM for the change to AcknowledgedResponse
* Add Snapshot Lifecycle Management Package Docs (#43535)
* Fix compilation for transport actions now that task is required
* Add a note mentioning the privileges needed for SLM (#43708)
* Add a note mentioning the privileges needed for SLM
This adds a note to the top of the "getting started with SLM"
documentation mentioning that there are two built-in privileges to
assist with creating roles for SLM users and administrators.
Relates to #38461
* Mention that you can create snapshots for indices you can't read
* Fix REST tests for new number of cluster privileges
* Mute testThatNonExistingTemplatesAreAddedImmediately (#43951)
* Fix SnapshotHistoryStoreTests after merge
* Remove overridden newResponse functions that have been removed
* Fix compilation for backport
* Fix get snapshot output parsing in test
* [DOCS] Add redirects for removed autogen anchors (#44380)
* Switch <tt>...</tt> in javadocs for {@code ...}
Test clusters currently has its own set of logic for dealing with
finding different versions of Elasticsearch, downloading them, and
extracting them. This commit converts testclusters to use the
DistributionDownloadPlugin.
* HLRC: Fix '+' Not Correctly Encoded in GET Req.
* Encode `+` correctly as `%2B` in URL paths
* Keep encoding `+` as space in URL parameters
* Closes#33077
Renames `_id_copy` to `ml__id_copy` as field names starting with
underscore are deprecated. The new field name `ml__id_copy` was
chosen as an obscure enough field that users won't have in their data.
Otherwise, this field is only intented to be used by df-analytics.
If a job is opened and then closed and does nothing in
between then it should not persist any results or state
documents. This change adapts the no-op job test to
assert no results in addition to no state, and to log
any documents that cause this assertion to fail.
Relates elastic/ml-cpp#512
Relates #43680
This commit adds support for multiple source indices.
In order to deal with multiple indices having different mappings,
it attempts a best-effort approach to merge the mappings assuming
there are no conflicts. In case conflicts exists an error will be
returned.
To allow users creating custom mappings for special use cases,
the destination index is now allowed to exist before the analytics
job runs. In addition, settings are no longer copied except for
the `index.number_of_shards` and `index.number_of_replicas`.
This merges the initial work that adds a framework for performing
machine learning analytics on data frames. The feature is currently experimental
and requires a platinum license. Note that the original commits can be
found in the `feature-ml-data-frame-analytics` branch.
A new set of APIs is added which allows the creation of data frame analytics
jobs. Configuration allows specifying different types of analysis to be performed
on a data frame. At first there is support for outlier detection.
The APIs are:
- PUT _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}/_stats
- POST _ml/data_frame/analysis/{id}/_start
- POST _ml/data_frame/analysis/{id}/_stop
- DELETE _ml/data_frame/analysis/{id}
When a data frame analytics job is started a persistent task is created and started.
The main steps of the task are:
1. reindex the source index into the dest index
2. analyze the data through the data_frame_analyzer c++ process
3. merge the results of the process back into the destination index
In addition, an evaluation API is added which packages commonly used metrics
that provide evaluation of various analysis:
- POST _ml/data_frame/_evaluate
This trace logging looks like it was copy/pasted from another test,
where the logging in that test was only added to investigate a test
failure. This commit removes the trace logging.
* [ML] Adding support for geo_shape, geo_centroid, geo_point in datafeeds
* only supporting doc_values for geo_point fields
* moving validation into GeoPointField ctor
Get resources action sorts on the resource id. When there are no resources at
all, then it is possible the index does not contain a mapping for the resource
id field. In that case, the search api fails by default.
This commit adjusts the search request to ignore unmapped fields.
Closeselastic/kibana#37870
Re-enable muted tests and accommodate recent backend changes
that result in higher memory usage being reported for a job
at the start of its life-cycle
The date_histogram accepts an interval which can be either a calendar
interval (DST-aware, leap seconds, arbitrary length of months, etc) or
fixed interval (strict multiples of SI units). Unfortunately this is inferred
by first trying to parse as a calendar interval, then falling back to fixed
if that fails.
This leads to confusing arrangement where `1d` == calendar, but
`2d` == fixed. And if you want a day of fixed time, you have to
specify `24h` (e.g. the next smallest unit). This arrangement is very
error-prone for users.
This PR adds `calendar_interval` and `fixed_interval` parameters to any
code that uses intervals (date_histogram, rollup, composite, datafeed, etc).
Calendar only accepts calendar intervals, fixed accepts any combination of
units (meaning `1d` can be used to specify `24h` in fixed time), and both
are mutually exclusive.
The old interval behavior is deprecated and will throw a deprecation warning.
It is also mutually exclusive with the two new parameters. In the future the
old dual-purpose interval will be removed.
The change applies to both REST and java clients.
Muting a number of AutoDetectMemoryLimitIT tests to give CI a chance to
settle before easing in required backend changes.
relates elastic/ml-cpp#486
relates #42086
* [ML] Add validation that rejects duplicate detectors in PutJobAction
Closes#39704
* Add YML integration test for duplicate detectors fix.
* Use "== false" comparison rather than "!" operator.
* Refine error message to sound more natural.
* Put job description in square brackets in the error message.
* Use the new validation in ValidateJobConfigAction.
* Exclude YML tests for new validation from permission tests.
Ensure that there is at least a 1s delay between the time that state
is persisted by each of the two jobs in the test.
Model snapshot IDs use the current time in epoch seconds to
distinguish themselves, hence snapshots will be overwritten
by another if it occurs in the same 1s window.
Closes#40347
* [ML] Refactor common utils out of ML plugin to XPack.Core
* implementing GET filters with abstract transport
* removing added rest param
* adjusting how defaults can be supplied
The problem here was that `DatafeedJob` was updating the last end time searched
based on the `now` even though when there are aggregations, the extactor will
only search up to the floor of `now` against the histogram interval.
This commit fixes the issue by using the end time as calculated by the extractor.
It also adds an integration test that uses aggregations. This test would fail
before this fix. Unfortunately the test is slow as we need to wait for the
datafeed to work in real time.
Closes#39842
Dimitris Athanasiou
Benjamin Trent
Przemysław Witek
Armin Braun
Mark Vieira
Przemyslaw Gomulka
Andrei Stefan
Alpar Torok
Lee Hinman
Ryan Ernst
David Roberts
Jason Tedor
David Turner
Ed Savage
Zachary Tong
Ed Savage
Tom Veasey