This change automatically pre-sort search shards on search requests that use a primary sort based on the value of a field. When possible, the can_match phase will extract the min/max (depending on the provided sort order) values of each shard and use it to pre-sort the shards prior to running the subsequent phases. This feature can be useful to ensure that shards that contain recent data are executed first so that intermediate merge have more chance to contain contiguous data (think of date_histogram for instance) but it could also be used in a follow up to early terminate sorted top-hits queries that don't require the total hit count. The latter could significantly speed up the retrieval of the most/least
recent documents from time-based indices.
Relates #49091
This commit adds a deprecation warning when starting
a node where either of the server contexts
(xpack.security.transport.ssl and xpack.security.http.ssl)
meet either of these conditions:
1. The server lacks a certificate/key pair (i.e. neither
ssl.keystore.path not ssl.certificate are configured)
2. The server has some ssl configuration, but ssl.enabled is not
specified. This new validation does not care whether ssl.enabled is
true or false (though other validation might), it simply makes it
an error to configure server SSL without being explicit about
whether to enable that configuration.
Backport of: #45892
Backport of #48277
Otherwise integration tests may fail if the monitoring interval is low:
```
[2019-10-21T09:57:25,527][ERROR][o.e.b.ElasticsearchUncaughtExceptionHandler] [integTest-0] fatal error in thread [elasticsearch[integTest-0][generic][T#4]], exiting
java.lang.AssertionError: initial cluster state not set yet
at org.elasticsearch.cluster.service.ClusterApplierService.state(ClusterApplierService.java:208) ~[elasticsearch-7.6.0-SNAPSHOT.jar:7.6.0-SNAPSHOT]
at org.elasticsearch.cluster.service.ClusterService.state(ClusterService.java:125) ~[elasticsearch-7.6.0-SNAPSHOT.jar:7.6.0-SNAPSHOT]
at org.elasticsearch.xpack.monitoring.MonitoringService$MonitoringExecution$1.doRun(MonitoringService.java:231) ~[?:?]
at org.elasticsearch.common.util.concurrent.AbstractRunnable.run(AbstractRunnable.java:37) ~[elasticsearch-7.6.0-SNAPSHOT.jar:7.6.0-SNAPSHOT]
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:515) ~[?:?]
at java.util.concurrent.FutureTask.run(FutureTask.java:264) ~[?:?]
at org.elasticsearch.common.util.concurrent.ThreadContext$ContextPreservingRunnable.run(ThreadContext.java:703) ~[elasticsearch-7.6.0-SNAPSHOT.jar:7.6.0-SNAPSHOT]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) ~[?:?]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) ~[?:?]
at java.lang.Thread.run(Thread.java:835) [?:?]
```
I ran into this when lowering the monitoring interval when investigating
enrich monitoring test: #48258
fix force stopping transform if indexer state hasn't been written and/or is set to STOPPED. In certain situations the transform could not be stopped, which means the task could not be removed. Introduces improved abstraction in order to better test state handling in future.
* SLM set the operation mode to RUNNING on first run
Set the SLM operation mode to RUNNING when setting the first SLM lifecycle
policy. Historically, SLM was not decoupled from ILM but now they are
independent components. Setting the SLM operation mode to what the ILM running
mode was when we set the first SLM lifecycle policy was a remain from those
times.
* SLM update package info
* SLM suppress unusued warning
* SLM use logger for the correct class
* SLM Add integration test for operation mode
* Use ESSingleNodeTestCase instead of ESIntegTestCase
(cherry picked from commit 4ad3d93f89d03bf9a25685a990d1a439f33ce0e6)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
If a datafeed is stopped normally and force stopped at the same
time then it is possible that the force stop removes the
persistent task while the normal stop is performing actions.
Currently this causes the normal stop to error, but since
stopping a stopped datafeed is not an error this doesn't make
sense. Instead the force stop should just take precedence.
This is a followup to #49191 and should really have been
included in the changes in that PR.
This commit moves the async calls required to retrieve the components
that make up `ExtractedFieldsExtractor` out of `DataFrameDataExtractorFactory`
and into a dedicated `ExtractorFieldsExtractorFactory` class.
A few more refactorings are performed:
- The detector no longer needs the results field. Instead, it knows
whether to use it or not based on whether the task is restarting.
- We pass more accurately whether the task is restarting or not.
- The validation of whether fields that have a cardinality limit
are valid is now performed in the detector after retrieving the
respective cardinalities.
Backport of #49315
This is a pure code rearrangement refactor. Logic for what specific ValuesSource instance to use for a given type (e.g. script or field) moved out of ValuesSourceConfig and into CoreValuesSourceType (previously just ValueSourceType; we extract an interface for future extensibility). ValueSourceConfig still selects which case to use, and then the ValuesSourceType instance knows how to construct the ValuesSource for that case.
This commit changes the ThreadContext to just use a regular ThreadLocal
over the lucene CloseableThreadLocal. The CloseableThreadLocal solves
issues with ThreadLocals that are no longer needed during runtime but
in the case of the ThreadContext, we need it for the runtime of the
node and it is typically not closed until the node closes, so we miss
out on the benefits that this class provides.
Additionally by removing the close logic, we simplify code in other
places that deal with exceptions and tracking to see if it happens when
the node is closing.
Closes#42577
This commit wraps the calls to retrieve the current step in a try/catch
so that the exception does not bubble up. Instead, step info is added
containing the exception to the existing step.
Semi-related to #49128
(cherry picked from commit 72530f8a7f40ae1fca3704effb38cf92daf29057)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This API call in most implementations is fairly IO heavy and slow
so it is more natural to be async in the first place.
Concretely though, this change is a prerequisite of #49060 since
determining the repository generation from the cluster state
introduces situations where this call would have to wait for other
operations to finish. Doing so in a blocking manner would break
`SnapshotResiliencyTests` and waste a thread.
Also, this sets up the possibility to in the future make use of async IO
where provided by the underlying Repository implementation.
In a follow-up `SnapshotsService#getRepositoryData` will be made async
as well (did not do it here, since it's another huge change to do so).
Note: This change for now does not alter the threading behaviour in any way (since `Repository#getRepositoryData` isn't forking) and is purely mechanical.
Previously, DATEDIFF for minutes and hours was doing a
rounding calculation using all the time fields (secs, msecs/micros/nanos).
Instead it should first truncate the 2 dates to the respective field (mins or hours)
zeroing out all the more detailed time fields and then make the subtraction.
(cherry picked from commit 124cd18e20429e19d52fd8dc383827ea5132d428)
The following edge cases were fixed:
1. A request to force-stop a stopping datafeed is no longer
ignored. Force-stop is an important recovery mechanism
if normal stop doesn't work for some reason, and needs
to operate on a datafeed in any state other than stopped.
2. If the node that a datafeed is running on is removed from
the cluster during a normal stop then the stop request is
retried (and will likely succeed on this retry by simply
cancelling the persistent task for the affected datafeed).
3. If there are multiple simultaneous force-stop requests for
the same datafeed we no longer fail the one that is
processed second. The previous behaviour was wrong as
stopping a stopped datafeed is not an error, so stopping
a datafeed twice simultaneously should not be either.
Backport of #49191
* [ML] ML Model Inference Ingest Processor (#49052)
* [ML][Inference] adds lazy model loader and inference (#47410)
This adds a couple of things:
- A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them
- A Model class and its first sub-class LocalModel. Used to cache model information and run inference.
- Transport action and handler for requests to infer against a local model
Related Feature PRs:
* [ML][Inference] Adjust inference configuration option API (#47812)
* [ML][Inference] adds logistic_regression output aggregator (#48075)
* [ML][Inference] Adding read/del trained models (#47882)
* [ML][Inference] Adding inference ingest processor (#47859)
* [ML][Inference] fixing classification inference for ensemble (#48463)
* [ML][Inference] Adding model memory estimations (#48323)
* [ML][Inference] adding more options to inference processor (#48545)
* [ML][Inference] handle string values better in feature extraction (#48584)
* [ML][Inference] Adding _stats endpoint for inference (#48492)
* [ML][Inference] add inference processors and trained models to usage (#47869)
* [ML][Inference] add new flag for optionally including model definition (#48718)
* [ML][Inference] adding license checks (#49056)
* [ML][Inference] Adding memory and compute estimates to inference (#48955)
* fixing version of indexed docs for model inference
The logic for `cleanupInProgress()` was backwards everywhere (method itself and
all but one user). Also, we weren't checking it when removing a repository.
This lead to a bug (in the one spot that didn't use the method backwards) that prevented
the cleanup cluster state entry from ever being removed from the cluster state if master
failed over during the cleanup process.
This change corrects the backwards logic, adds a test that makes sure the cleanup
is always removed and adds a check that prevents repository removal during cleanup
to the repositories service.
Also, the failure handling logic in the cleanup action was broken. Repeated invocation would lead to the cleanup being removed from the cluster state even if it was in progress. Fixed by adding a flag that indicates whether or not any removal of the cleanup task from the cluster state must be executed. Sorry for mixing this in here, but I had to fix it in the same PR, as the first test (for master-failover) otherwise would often just delete the blocked cleanup action as a result of a transport master action retry.
improve error handling for script errors, treating it as irrecoverable errors which puts the task
immediately into failed state, also improves the error extraction to properly report the script
error.
fixes#48467
AutoFollowIT relies on assertBusy() calls to wait for a given number of
leader indices to be created but this is prone to failures on CI. Instead,
we should use latches to indicate when auto-follow patterns must be
paused and resumed.
This commit fixes a NPE problem as reported in #49150.
But this problem uncovered that we never added proper handling
of state for data frame analytics tasks.
In this commit we improve the `MlTasks.getDataFrameAnalyticsState`
method to handle null tasks and state tasks properly.
Closes#49150
Backport of #49186
If CCR encounters a rejected execution exception, today we treat this as
fatal. This is not though, as the stuffed queue could drain. Requiring
an administrator to manually restart the follow tasks that faced such an
exception is a burden. This commit addresses this by making CCR
auto-retry on rejected execution exceptions.
We can't guarantee expected request failures if search request is across
many indexes, as if expected shards fail, some indexes may return 200.
closes#47743
The JdbcHttpClientRequestTests and HttpClientRequestTests classes both
hold a static reference to a mock web server that internally uses the
JDKs built-in HttpServer, which resides in a sun package that the
RamUsageEstimator does not have access to. This causes builds that use
a runtime of Java 8 to fail since the StaticFieldsInvariantRule is run
when Java 8 is used.
Relates #41526
Relates #49105