Today the `CoordinatorTests` run the publication process as a single
atomic action; however in production it appears possible that another
master may be elected, publish its state, then fail, then we win another
election, all in between the time we sampled our previous cluster state
and started to publish the one we first thought of.
This violates the `assertClusterStateConsistency()` assertion that
verifies the cluster state update event matches the states we actually
published and applied.
This commit adjusts the tests to run the publication process more
asynchronously so as to allow time for this behaviour to occur. This
should eventually result in a reproduction of the failure in #61437 that
will let us analyse what's really going on there and help us fix it.
Inference processors asynchronously usage write stats to the .ml-stats index after they used.
In tests the write can leak into the next test causing failures depending on which test follows.
This change waits for the usage stats docs to be written at the end of the test
If a TLS-protected connection closes unexpectedly then today we often
emit a `WARN` log, typically one of the following:
io.netty.handler.codec.DecoderException: javax.net.ssl.SSLHandshakeException: Insufficient buffer remaining for AEAD cipher fragment (2). Needs to be more than tag size (16)
io.netty.handler.codec.DecoderException: javax.net.ssl.SSLException: Received close_notify during handshake
We typically only report unexpectedly-closed connections at `DEBUG`
level, but these two messages don't follow that rule and generate a lot
of noise as a result. This commit adjusts the logging to report these
two exceptions at `DEBUG` level only.
Today we use `long` to represent the number of parts of a blob. There's
no need for this extra range, it forces us to do some casting elsewhere,
and indeed when snapshotting we iterate over the parts using an `int`
which would be an infinite loop in case of overflow anyway:
for (int i = 0; i < fileInfo.numberOfParts(); i++) {
This commit changes the representation of the number of parts of a blob
to an `int`.
We convert longs to ints using `Math.toIntExact` in places where we're
sure there will be no overflow, but this doesn't explain the intent of
these conversions very well. This commit introduces a dedicated method
for these conversions, and adds an assertion that we never overflow.
If a searchable snapshot shard fails (e.g. its node leaves the cluster)
we want to be able to start it up again on a different node as quickly
as possible to avoid unnecessarily blocking or failing searches. It
isn't feasible to fully restore such shards in an acceptably short time.
In particular we would like to be able to deal with the `can_match`
phase of a search ASAP so that we can skip unnecessary waiting on shards
that may still be warming up but which are not required for the search.
This commit solves this problem by introducing a system index that holds
much of the data required to start a shard. Today(*) this means it holds
the contents of every file with size <8kB, and the first 4kB of every
other file in the shard. This system index acts as a second-level cache,
behind the first-level node-local disk cache but in front of the blob
store itself. Reading chunks from the index is slower than reading them
directly from disk, but faster than reading them from the blob store,
and is also replicated and accessible to all nodes in the cluster.
(*) the exact heuristics for what we should put into the system index
are still under investigation and may change in future.
This second-level cache is populated when we attempt to read a chunk
which is missing from both levels of cache and must therefore be read
from the blob store.
We also introduce `SearchableSnapshotsBlobStoreCacheIntegTests` which
verify that we do not hit the blob store more than necessary when
starting up a shard that we've seen before, whether due to a node
restart or because a snapshot was mounted multiple times.
Backport of #60522
Co-authored-by: Tanguy Leroux <tlrx.dev@gmail.com>
This commit removes the tasks module that only existed to define the
tasks result index, `.tasks`, as a system index. The definition for
the tasks results system index descriptor is moved to the
`SystemIndices` class with a check that no other plugin or module
attempts to define an entry with the same source.
Additionally, this change also makes the pattern for the tasks result
index a wildcard pattern since we will need this when the index is
upgraded (reindex to new name and then alias that to .tasks).
Backport of #61540
If a search failure occurs during data frame extraction we catch
the error and retry once. However, we retry another search that is
identical to the first one. This means we will re-fetch any docs
that were already processed. This may result either to training
a model using duplicate data or in the case of outlier detection to
an error message that the process received more records than it
expected.
This commit fixes this issue by tracking the latest doc's sort key
and then using that in a range query in case we restart the search
due to a failure.
Backport of #61544
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
Backports the following commits to 7.x:
[ML] write warning if configured memory limit is too low for analytics job (#61505)
Having `_start` fail when the configured memory limit is too low can be frustrating.
We should instead warn the user that their job might not run properly if their configured limit is too low.
It might be that our estimate is too high, and their configured limit works just fine.
DeprecationLogger's constructor should not create two loggers. It was
taking parent logger instance, changing its name with a .deprecation
prefix and creating a new logger.
Most of the time parent logger was not needed. It was causing Log4j to
unnecessarily cache the unused parent logger instance.
depends on #61515
backports #58435
- Added test coverage
- Removes build script cluttering
- Splits archive building and archive checking logic
- only rely on boost for now for ML licenses(tbd)
- Use Gradle build-in untar and unzip support
* Handle dynamic versions in func tests assertions
Driven by this issue
https://github.com/elastic/elasticsearch/pull/60969#issuecomment-674962158
we apply some rework on how we handle distributions in our test cluster setups:
- If no custom modules, plugins or extra jar files are declared we do not create a cluster
specific distro folder and use the origin distribution folder instead.
- If a custom distribution folder is required, we fallback to file copy when hard linking
is not supported
Refactor the tests to not require a mock HTTP Server. This has been
the cause of flakiness and removing it doesn't affect the logical
coverage of this suite. The "fake UI" is now simulated by an
http client that makes the necessary requests to Elasticsearch APIs.
* updated shard limit doc
As the documentation was not so clear. I have updated saying this limit includes open indices with unassigned primaries and replicas count towards the limit.
* [DOCS] Incorporated edits.
Co-authored-by: Deb Adair <debadair@elastic.co>
Co-authored-by: gadekishore <50092970+gadekishore@users.noreply.github.com>
Backport to add case insensitive support for regex queries.
Forks a copy of Lucene’s RegexpQuery and RegExp from Lucene master.
This can be removed when 8.7 Lucene is released.
Closes#59235
Splitting DeprecationLogger into two. HeaderWarningLogger - responsible for adding a response warning headers and ThrottlingLogger - responsible for limiting the duplicated log entries for the same key (previously deprecateAndMaybeLog).
Introducing A ThrottlingAndHeaderWarningLogger which is a base for other common logging usages where both response warning header and logging throttling was needed.
relates #55699
relates #52369
backports #55941
The building block of the eql response is currently the SearchHit. This
is a problem since it is tied to an actual search, and thus has scoring,
highlighting, shard information and a lot of other things that are not
relevant for EQL.
This becomes a problem when doing sequence queries since the response is
not generated from one search query and thus there are no SearchHits to
speak of.
Emulating one is not just conceptually incorrect but also problematic
since most of the data is missed or made-up.
As such this PR introduces a simple class, Event, that maps nicely to
the terminology while hiding the ES internals (the use of SearchHit or
GetResult/GetResponse depending on the API used).
Fix#59764Fix#59779
Co-authored-by: Igor Motov <igor@motovs.org>
(cherry picked from commit 997376fbe6ef2894038968842f5e0635731ede65)
* Faster `equals` for `BytesArray` which is nice since with this change we use it for the search cache
* Lighter `StreamInput` for `BytesArray` that should save memory and some indirection relative to the one on the abstract bytes reference
* Lighter `writeTo` implementation
* Build a `BytesArray` instead of a PagedBytesReference whenever possible to save indirection and memory
This is mostly motivated by the performance issues we are seeing around the GET mappings
REST API which (in case of a large number of indices) will create decompressing streams in a hot loop
which takes a significant amount of time for the system calls involved in instantiating deflaters
and inflaters.
Also, this fixes a leaked deflater when deserializing cached repository data.
This method might have materialize all the bytes in a reference into a fresh `byte[]`.
Using the stream is much safer and only trivially more expensive + in most cases we now run the fast path via `BytesArray` anyway.
This optimization is more relevant in the context of CCR. When a node in
the follower cluster leaves, we reallocate the shard-follow tasks on
that node to other nodes. The new tasks will overwhelm the follower
cluster with many put-mapping, update-settings requests, although most
of them are noop. This change detects and optimizes the noop
update-settings requests.
This continues #61301, migrating all of the mappers in `server` to the
new `MapperTestCase` which is nicer than `FieldMapperTestCase` because
it doesn't depend on all of Elasticsearch.
Rene Groeschke
David Kyle
David Turner
Ioannis Kakavas
Ryan Ernst
Lisa Cawley
James Rodewig
Jason Tedor
Jay Modi
Dimitris Athanasiou
Benjamin Trent
Przemyslaw Gomulka
Przemysław Witek
Igor Motov
debadair
Nik Everett
markharwood
Brandon Morelli
Costin Leau
Armin Braun
Nhat Nguyen