We leverage artifact transforms now when downloading and unpacking elasticsearch distributions.
This has the benefit of
- handcrafted extract tasks on the root project are not required.
- The general tight coupling to the root project has been removed.
- The overall required configurations required to handle a distribution have been reduced
- ElasticsearchDistribution has been simplified by making Extracted an ordinary Configuration
downloaded and unpacked external distributions are reused in later builds by been cached
in the gradle user home.
DistributionDownloadPlugin functional tests have been extended and ported
to DistributionDownloadPluginFuncTest.
* Fix ElasticsearchNode#getDistributionFiles (#61219)
Fixes#61647
Backport of #61474.
Part of #46106. Simplify the implementation of deprecation logging by
relying of log4j more completely, and implementing additional behaviour
through custom appenders and filters.
The fact that the data node is already blocked on writing
data files did not guarantee that the cluster state that made
the data node start snapshotting is already applied on master.
This could lead to races where the get snapshots action still
runs based on a state without the snapshot in it, tripping the assertion.
Much safer to handle this by waiting on the non-blocking snapshot create
to return, which guarantees that the CS has been applied on master.
Closes#61541
It looks like it is possible for a request to throw an exception early
before any API interaciton has happened. This can lead to the request count
map containing a `null` for the request count key.
The assertion is not correct and we should not NPE here
(as that might also hide the original exception since we are running this code in
a `finally` block from within the S3 SDK).
Closes#61670
This commit enhances the verbose output for the
`_ingest/pipeline/_simulate?verbose` api. Specifically
this adds the following:
* the pipeline processor is now included in the output
* the conditional (if) and result is now included in the output iff it was defined
* a status field is always displayed. the possible values of status are
* `success` - if the processor ran with out errors
* `error` - if the processor ran but threw an error that was not ingored
* `error_ignored` - if the processor ran but threw an error that was ingored
* `skipped` - if the process did not run (currently only possible if the if condition evaluates to false)
* `dropped` - if the the `drop` processor ran and dropped the document
* a `processor_type` field for the type of processor (e.g. set, rename, etc.)
* throw a better error if trying to simulate with a pipeline that does not exist
closes#56004
This commit adds the functionality to allocate newly created indices on nodes in the "hot" tier by
default when they are created.
This does not break existing behavior, as nodes with the `data` role are considered to be part of
the hot tier. Users that separate their deployments by using the `data_hot` (and `data_warm`,
`data_cold`, `data_frozen`) roles will have their data allocated on the hot tier nodes now by
default.
This change is a little more complicated than changing the default value for
`index.routing.allocation.include._tier` from null to "data_hot". Instead, this adds the ability to
have a plugin inject a setting into the builder for a newly created index. This has the benefit of
allowing this setting to be visible as part of the settings when retrieving the index, for example:
```
// Create an index
PUT /eggplant
// Get an index
GET /eggplant?flat_settings
```
Returns the default settings now of:
```json
{
"eggplant" : {
"aliases" : { },
"mappings" : { },
"settings" : {
"index.creation_date" : "1597855465598",
"index.number_of_replicas" : "1",
"index.number_of_shards" : "1",
"index.provided_name" : "eggplant",
"index.routing.allocation.include._tier" : "data_hot",
"index.uuid" : "6ySG78s9RWGystRipoBFCA",
"index.version.created" : "8000099"
}
}
}
```
After the initial setting of this setting, it can be treated like any other index level setting.
This new setting is *not* set on a new index if any of the following is true:
- The index is created with an `index.routing.allocation.include.<anything>` setting
- The index is created with an `index.routing.allocation.exclude.<anything>` setting
- The index is created with an `index.routing.allocation.require.<anything>` setting
- The index is created with a null `index.routing.allocation.include._tier` value
- The index was created from an existing source metadata (shrink, clone, split, etc)
Relates to #60848
The check introduced by #60640 for scroll searches, in which we log
if the index access control before the query and fetch phases differs
from when the scroll context is created, is too strict, leading to spurious
warning log messages.
The check verifies instance equality but this assumes that the fetch
phase is executed in the same thread context as the scroll context
validation. However, this is not true if the scroll search is executed
cross-cluster, and even for local scroll searches it is an unfounded assumption.
The check is hence reduced to a null check for the index access.
The fact that the access control is suitable given the indices that
are actually accessed (by the scroll) will be done in a follow-up,
after we better regulate the creation of index access controls in general.
Runtime fields need to have a SearchLookup available, when building their fielddata implementations, so that they can look up other fields, runtime or not.
To achieve that, we add a Supplier<SearchLookup> argument to the existing MappedFieldType#fielddataBuilder method.
As we introduce the ability to look up other fields while building fielddata for mapped fields, we implicitly add the ability for a field to require other fields. This requires some protection mechanism that detects dependency cycles to prevent stack overflow errors.
With this commit we also introduce detection for cycles, as well as a limit on the depth of the references for a runtime field. Note that we also plan on introducing cycles detection at compile time, so the runtime cycles detection is a last resort to prevent stack overflow errors but we hope that we can reject runtime fields from being registered in the mappings when they create a cycle in their definition.
Note that this commit does not introduce any production implementation of runtime fields, but is rather a pre-requisite to merge the runtime fields feature branch.
This is a breaking change for MapperPlugins that plug in a mapper, as the signature of MappedFieldType#fielddataBuilder changes from taking a single argument (the index name), to also accept a Supplier<SearchLookup>.
Relates to #59332
Co-authored-by: Nik Everett <nik9000@gmail.com>
The domain part of a Cloud-Id can contain an optional custom port, e.g.
cloud.example.org:9443. This feature is used for Elastic Cloud
Enterprise installations that can't use the default port 443.
This change fixes RestClient.build() to correctly handle custom ports.
Replaces the superclass of the test for `HistogramFieldMapperTests` with
one that doesn't extend `ESSingleNodeTestCase` so we don't depend on the
entire world to test the field mapper.
Continues #61301.
Today we sometimes notify a listener of completion while holding
`SparseFileTracker#mutex`. This commit move all such calls out from
under the mutex and adds assertions that the mutex is not held in the
listener.
Closes#61520
Errors from bad mappings at index creation are currently logged at DEBUG level, which
can make it difficult to work out what's going on if the index is being auto-created. This
commit ups the log level to INFO for auto-created indices, and includes some more
information in the log message.
1. Get rid of the capturing lambda on the hot path that inlines very badly
2. Remove as many bounds checks as possible, thereby reducing method size and improving inlining
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.