When using auto-generated IDs + the ingest drop processor (which looks to be used by filebeat
as well) + coordinating nodes that do not have the ingest processor functionality, this can lead
to a NullPointerException.
The issue is that markCurrentItemAsDropped() is creating an UpdateResponse with no id when
the request contains auto-generated IDs. The response serialization is lenient for our
REST/XContent format (i.e. we will send "id" : null) but the internal transport format (used for
communication between nodes) assumes for this field to be non-null, which means that it can't
be serialized between nodes. Bulk requests with ingest functionality are processed on the
coordinating node if the node has the ingest capability, and only otherwise sent to a different
node. This means that, in order to reproduce this, one needs two nodes, with the coordinating
node not having the ingest functionality.
Closes#46678
This commit reuses the same state processor that is used for autodetect
to parse state output from data frame analytics jobs. We then index the
state document into the state index.
Backport of #46804
It is possible for a running analytics job that its config is removed
from the '.ml-config' index (perhaps the user deleted the entire index,
etc.). In that case the task remains without a matching config. I have
raised #46781 to discuss how to deal with this issue.
This commit focuses on `MlMemoryTracker` and changes it so that when
we get the configs for the running tasks we leniently ignore missing ones.
This at least means memory tracking will keep working for other jobs
if one or more are missing.
In addition, this commit makes the cleanup code for native analytics
tests more robust by explicitly stopping all jobs and force-stopping
if an error occurs. This helps so that a single failing test does
not cause other tests fail due to pending tasks.
Backport of #46789
When the stop API is called while the task is running there is
a chance the task gets marked completed twice. This may cause
undesired side effects, like indexing the progress document a second
time after the stop API has returned (the cause for #46705).
This commit adds a check that the task has not been completed before
proceeding to mark it so. In addition, when we update the task's state
we could get some warnings that the task was missing if the stop API
has been called in the meantime. We now check the errors are
`ResourceNotFoundException` and ignore them if so.
Closes#46705
Backports #46721
This is fixing a bug where if an analytics job is started before any
anomaly detection job is opened, we create an index after the state
write alias.
Instead, we should create the state index and alias before starting
an analytics job and this commit makes sure this is the case.
Backport of #46602
After starting the analytics job and checking its state
the state can be any of "started", "reindexing" or
"analyzing" depending on how quickly the work is done.
Investigating the test failure reported in #45518 it appears that
the datafeed task was not found during a tast state update. There
are only two places where such an update is performed: when we set
the state to `started` and when we set it to `stopping`. We handle
`ResourceNotFoundException` in the latter but not in the former.
Thus the test reveals a rare race condition where the datafeed gets
requested to stop before we managed to update its state to `started`.
I could not reproduce this scenario but it would be my best guess.
This commit catches `ResourceNotFoundException` while updating the
state to `started` and lets the task terminate smoothly.
Closes#45518
Backport of #46495
ML users who upgrade from versions prior to 7.4 to 7.4 or later
will have ML results indices that do not have mappings for the
total_search_time_ms field. Therefore, when searching these
indices we must tolerate this field not having a mapping.
Fixes#46437
This refactors `DataFrameAnalyticsTask` into its own class.
The task has quite a lot of functionality now and I believe it would
make code more readable to have it live as its own class rather than
an inner class of the start action class.
Backport of #46402
* [ML] waiting for ml indices before waiting task assignment testFullClusterRestart
* waiting for a stable cluster after fullrestart
* removing unused imports
The test seems to have been failing due to a race condition between
stopping the task and refreshing the destination index. In particular,
we were going forward with refreshing the destination index even
though the task stopped in the meantime. This was fixed in
request.
Closes#43960
Backport of #46271
Though we allow CCS within datafeeds, users could prevent nodes from accessing remote clusters. This can cause mysterious errors and difficult to troubleshoot.
This commit adds a check to verify that `cluster.remote.connect` is enabled on the current node when a datafeed is configured with a remote index pattern.
* [ML] Regression dependent variable must be numeric
This adds a validation that the dependent variable of a regression
analysis must be numeric.
* Address review comments and fix some problems
In addition to addressing the review comments, this
commit fixes a few issues I found during testing.
In particular:
- if there were mappings for required fields but they were
not included we were not reporting the error
- if explicitly included fields had unsupported types we were
not reporting the error
Unfortunately, I couldn't get those fixed without refactoring
the code in `ExtractedFieldsDetector`.
This commit adds support for `boolean` fields in data frame
analytics (and currently both outlier detection and regression).
The analytics process expects `boolean` fields to be encoded as
integers with 0 or 1 value.
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).
* [ML] Adding data frame analytics stats to _usage API (#45820)
* [ML] Adding data frame analytics stats to _usage API
* making the size of analytics stats 10k
* adjusting backport
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
We cannot know how long the analysis will take to complete thus we should not have
a timeout. Note that if the process crashes, the result processor will pick the
exception due to the stream closing.
Closes#45723
Changes the order of parameters in Geometries from lat, lon to lon, lat
and moves all Geometry classes are moved to the
org.elasticsearch.geomtery package.
Backport of #45332Closes#45048
* 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.
In the FIPS JVM the JVM default locale seems to leak into places
where it should be overridden. This change skips assertions
in TimestampFormatFinderTests.testGuessIsDayFirstFromLocale
that may be impacted.
Fixes#45140
When doing a fieldwise Levenshtein distance comparison
between CSV rows, this change ignores all fields that
have long values, not just the longest field.
This approach works better for CSV formats that have
multiple freeform text fields rather than just a single
"message" field.
Fixes#45047
Benjamin Trent
Yannick Welsch
Dimitris Athanasiou
Przemysław Witek
David Roberts
Igor Motov
Armin Braun
Mark Vieira
Przemyslaw Gomulka
Jason Tedor