Currently we used the secure random number generate when generating http
request ids in the security AuditUtil. We do not need to be using this
level of randomness for this use case. Additionally, this random number
generator involves locking that blocks the http worker threads at high
concurrency loads.
This commit modifies this randomness generator to use our reproducible
randomness generator for Elasticsearch. This generator will fall back to
thread local random when used in production.
This is useful in cases where the caller of the API needs to know
the name of the realm that consumed the SAML Response and
authenticated the user and this is not self evident (i.e. because
there are many saml realms defined in ES).
Currently, the way to learn the realm name would be to make a
subsequent request to the `_authenticate` API.
When changing a job state using a mechanism that doesn't
wait for the desired state to be reached within the production
code the test code needs to loop until the cluster state has
been updated.
Closes#52451
Backport from #52179
Don't rely on the delete index api to resolve all the enrich indices for a particular enrich policy using a '[policy_name]-*' wildcard expression. With this change, the delete policy api will resolve the indices to remove and pass that directly to the delete index api.
This resolves a bug, that if `action.destructive_requires_name` setting has been set to true then the delete policy api is unable to remove the enrich indices related to the policy being deleted.
Closes#51228
Co-authored-by: bellengao <gbl_long@163.com>
audit messages are stored in the notifications index, so audit information is lost for integration
tests. This change forwards audit messages to logs, so they can help to debug issues.
relates: #51627
Following the change to store cluster state in Lucene indices
(#50907) it can take longer for all the cluster state updates
associated with node failure scenarios to be processed during
internal cluster tests where several nodes all run in the same
JVM.
Refactor the code to allow contextual parameterization of dateFormat and
name.
Separate aggs/query implementation though there's room for improvement
in the future
(cherry picked from commit e086f81b688875b33d01e4504ce7377031c8cf28)
The shard follow task cleaner executes on behalf of the user to clean up
a shard follow task after the follower index has been
deleted. Otherwise, these persistent tasks are left laying around, and
they fail to execute because the follower index has been deleted. In the
face of security, attempts to complete these persistent tasks would
fail. This is because these cleanups are executed under the system
context (this makes sense, they are happening on behalf of the user
after the user has executed an action) but the system role was never
granted the permission for persistent task completion. This commit
addresses this by adding this cluster privilege to the system role.
We marked the `init` ILM step as retryable but our test used `waitUntil`
without an assert so we didn’t catch the fact that we were not actually
able to retry this step as our ILM state didn’t contain any information
about the policy execution (as we were in the process of initialising
it).
This commit manually sets the current step to `init` when we’re moving
the ilm policy into the ERROR step (this enables us to successfully
move to the error step and later retry the step)
* ShrunkenIndexCheckStep: Use correct logger
(cherry picked from commit f78d4b3d91345a2a8fc0f48b90dd66c9959bd7ff)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
Translate to an agg query even if only literals are selected,
so that the correct number of rows is returned (number of buckets).
Fix issue with key only in GROUP BY (not in select) and WHERE clause:
Resolve aggregates and groupings based on the child plan which holds
the info info for all the fields of the underlying table.
Fixes: #41951Fixes: #41413
(cherry picked from commit 45b85809678b34a448639a420b97e25436ae851f)
The `top_metrics` agg is kind of like `top_hits` but it only works on
doc values so it *should* be faster.
At this point it is fairly limited in that it only supports a single,
numeric sort and a single, numeric metric. And it only fetches the "very
topest" document worth of metric. We plan to support returning a
configurable number of top metrics, requesting more than one metric and
more than one sort. And, eventually, non-numeric sorts and metrics. The
trick is doing those things fairly efficiently.
Co-Authored by: Zachary Tong <zach@elastic.co>
ML mappings and index templates have so far been created
programmatically. While this had its merits due to static typing,
there is consensus it would be clear to maintain those in json files.
In addition, we are going to adding ILM policies to these indices
and the component for a plugin to register ILM policies is
`IndexTemplateRegistry`. It expects the templates to be in resource
json files.
For the above reasons this commit refactors ML mappings and index
templates into json resource files that are registered via
`MlIndexTemplateRegistry`.
Backport of #51765
This commit makes the names of fetch subphases more consistent:
* Now the names end in just 'Phase', whereas before some ended in
'FetchSubPhase'. This matches the query subphases like AggregationPhase.
* Some names include 'fetch' like FetchScorePhase to avoid ambiguity about what
they do.
Ironically PreventFailingBuildIT.testSoThatTestsDoNotFail is causing failures
as documented in #52197. The no longer serves a purpose and can now be removed.
This is to support the ML categorization wizard.
Currently cluster:admin/analyze is only provided with the
"manage" cluster privilege, which is an excessive privilege
level to provide access to this single feature. It means
that the ML categorization wizard only works for extremely
highly privileged users.
Following this change the Kibana system user will be
permitted to run the _analyze endpoint on supplied strings
(not on an index). The ML UI will then call the _analyze
endpoint as the Kibana system user after first checking
that the logged-in user is permitted to create an ML job.
This will mean that users with the more reasonable
"manage_ml" cluster privilege will be permitted to use
the ML categorization wizard.
(This is also consistent with the way the ML UI will access
_all_ Elasticsearch functionality when the "ML in Spaces"
project is completed.)
Closes#51391
Relates elastic/kibana#57375
This adds a builder and parsed results for the `string_stats`
aggregation directly to the high level rest client. Without this the
HLRC can't access the `string_stats` API without the elastic licensed
`analytics` module.
While I'm in there this adds a few of our usual unit tests and
modernizes the parsing.
This commit removes the need for DeprecatedRoute and ReplacedRoute to
have an instance of a DeprecationLogger. Instead the RestController now
has a DeprecationLogger that will be used for all deprecated and
replaced route messages.
Relates #51950
Backport of #52278
Add a new cluster setting `search.allow_expensive_queries` which by
default is `true`. If set to `false`, certain queries that have
usually slow performance cannot be executed and an error message
is returned.
- Queries that need to do linear scans to identify matches:
- Script queries
- Queries that have a high up-front cost:
- Fuzzy queries
- Regexp queries
- Prefix queries (without index_prefixes enabled
- Wildcard queries
- Range queries on text and keyword fields
- Joining queries
- HasParent queries
- HasChild queries
- ParentId queries
- Nested queries
- Queries on deprecated 6.x geo shapes (using PrefixTree implementation)
- Queries that may have a high per-document cost:
- Script score queries
- Percolate queries
Closes: #29050
(cherry picked from commit a8b39ed842c7770bd9275958c9f747502fd9a3ea)
* Add more checks around parameter conversions
This commit adds two necessary verifications on received parameters:
- it checks the validity of the parameter's data type: if the declared
data type is resolved to an ES or Java type;
- it checks if the returned converter is non-null (i.e. a conversion is
possible) and generates an appropriate exception otherwise.
(cherry picked from commit eda30ac9c69383165324328c599ace39ac064342)
* Extract common optimizer tests (#52169)
(cherry picked from commit e5ad72bc22e9ec0686ab582195f0032efcb880bf)
* Hook in the optimizer rules (#52172)
(cherry picked from commit 1f90d8cc56052fbf2af604e72f9f5ca73f5e75d5)
Previously, in the in-memory sorting module
`LocalAggregationSorterListener` only the aggregate functions where used
(grabbed by the `sortingColumns`). As a consequence, if the ORDER BY
was also using columns of the GROUP BY clause, (especially in the case
of higher priority - before the aggregate functions) wrong results were
produced. E.g.:
```
SELECT gender, MAX(salary) AS max FROM test_emp
GROUP BY gender
ORDER BY gender, max
```
Add all columns of the ORDER BY to the `sortingColumns` so that the
`LocalAggregationSorterListener` can use the correct comparators in
the underlying PriorityQueue used to implement the in-memory sorting.
Fixes: #50355
(cherry picked from commit be680af11c823292c2d115bff01658f7b75abd76)
add a list of unsupported aggs in transforms and create a test that fails if a new aggregation is
added. Limitation: works only if a new agg is added to either the core or a known plugin
(Analytics, MatrixAggregation).
During a bug hunt, I caught a handful of things (unrelated to the bug) that could be potential issues:
1. Needlessly wrapping in exception handling (minor cleanup)
2. Potential of notifying listeners of a failure multiple times + even trying to notify of a success after a failure notification
Modifies SLM's and ILM's history indices to be hidden indices for added
protection against accidental querying and deletion, and improves
IndexTemplateRegistry to handle upgrading index templates.
Also modifies the REST test cleanup to delete hidden indices.