Without the flag we run into the situation where a broken repository (broken by some old 6.x
version of ES that is missing some snap-${uuid}.dat blobs fails to run the SLM retention task
since it always errors out).
Use `ORDER BY` to ensure order of the rows since more
than are returned in the testDate().
Follows: #56492
(cherry picked from commit 0053a1cb515b4db160d7b0bed5cf3f13c1050687)
Backport: #55377
This commit adds the ability to auto create data streams using index templates v2.
Index templates (v2) now have a data_steam field that includes a timestamp field,
if provided and index name matches with that template then a data stream
(plus first backing index) is auto created.
Relates to #53100
* QL: case sensitive support in EQL (#56404)
* adds a generic startsWith function to QL
* modifies the existent EQL startsWith function to be case sensitive
aware
* improves the existent EQL startsWith function to use a prefix query
when the function is used in a case sensitive context. Same improvement
is used in SQL's newly added STARTS_WITH function.
* adds case sensitivity to EQL configuration through a case_sensitive
parameter in the eql request, as established in #54411.
The case_sensitive parameter can be specified when running queries
(default is case insensitive)
(cherry picked from commit ee5a09ea840167566e34c28c8225dc38bc6a7ae8)
Docker informed us that for official multi-arch Docker builds, there
needs to be a single Dockerfile and build context that can be used for
each supported architecture. Therefore, rework the build to move the
relevant architecture logic into the Dockerfile, and merge the aarch64
/ x64 docker context builds.
fix count in get and get stats if explicit ids are given and ids might be
duplicated when configuration are stored in different index (versions).
fixes#56196
The Date/Time related query params of a JDBC prepared statement
serialized using java.util.Date. The rules for serializing
`java.util.Date` objects though reside in
`XContentElasticsearchExtension` which is not available in the
jdbc jar as this class is in `server` module. Therefore, a
custom extension of the `XContentBuilderExtension` iface has been
added to the jdbc module/jar.
Moreover the sql's `qa` project had as dependency the `sql-action`
module which depends on `server` so the `XContentBuilderExtension`
was available for the integ tests hiding the real problem.
Previously, when a user was setting a `java.sql.Time` to the prepStmt,
the DataType used was `DATETIME` instead of `TIME` and therefore
prevented from filtering with a `TIME` casted field:
```
SELECT * FROM test WHERE date::TIME = ?
```
Fixes: #56084
(cherry picked from commit f8d8e971bd2c85fa4aea44b5b3ba0cdcc950a4ed)
Backport of: #56569
A data stream test, which tests data stream resolvability in xpack apis failed in release builds.
A invocation of a searchable snapshot api failed, because the corresponding feature flag
wasn't enabled for xpack rest tests.
Closes#56531
Similar to what the moving function aggregation does, except merging windows of percentiles
sketches together instead of cumulatively merging final metrics
Move data stream resolvability test from IndicesOptionsIntegrationIT to DataStreamIT class.
Whether a transport action supports data streams is no longer controlled via indices options.
When no timezone is specified the session timezone is used without
conversion, fix the docs test accordingly.
Follows: #56158
(cherry picked from commit 4b79b19ea5c3d17e05cb8130f3c754ac9bfd2382)
This adds support for parsing numbers as range keys. They get converted
into a string, but we allow numbers.
While I was there I replaced the parser for `Range` with a
`ConstructingObjectParser` which will automatically add support for "did
you mean" style corrections on errors.
Closes#56402
This commit refactors the following:
* GeoPointFieldMapper and PointFieldMapper to
AbstractPointGeometryFieldMapper derived from AbstractGeometryFieldMapper.
* .setupFieldType moved up to AbstractGeometryFieldMapper
* lucene indexing moved up to AbstractGeometryFieldMapper.parse
* new addStoredFields, addDocValuesFields abstract methods for implementing
stored field and doc values field indexing in the concrete field mappers
This refactor is the next phase for setting up a framework for extending
spatial field mapper functionality in x-pack.
Currently Elasticsearch creates independent event loop groups for each
transport (http and internal) transport type. This is unnecessary and
can lead to contention when different threads access shared resources
(ex: allocators). This commit moves to a model where, by default, the
event loops are shared between the transports. The previous behavior can
be attained by specifically setting the http worker count.
This commit removes the `prefer_v2_templates` flag and setting. This was a brief setting that
allowed specifying whether V1 or V2 template should be used when an index is created. It has been
removed in favor of V2 templates always having priority.
Relates to #53101Resolves#56528
This is not a breaking change because this flag was never in a released version.
We are ensuring order in the two tests changed by waiting on latches.
The problem is, that 3s is a pretty short wait and on CI can randomly be exceeded
by pure chance. If that happened we wouldn't have visibility on it since we didn't
assert that the waits actually worked.
=> Fixed by asserting that the waits work and upping the timeout to our standard 10s
Also, moved to a per-test threadpool to make it simpler to identify which test failed,
should an unexpected task run on a closed client's pool afterall.
Async search integration tests are subject to random failures when:
* The test index has more than one replica.
* The request cache is used.
* Some shards are empty.
* The maintenance service starts a garbage collection when node is closing.
They are also slow because the test index is created/populated on each
test method.
This change refactors these integration tests in order to:
* Create the index once for the entire test suite.
* Fix the usage of the request cache and replicas.
* Ensures that all shards have at least one document.
* Increase the delay of the maintenance service garbage collection.
Closes#55895Closes#55988
Change TransportBroadcastByNodeAction and TransportBroadcastReplicationAction
to be able to resolve data streams by default. Implementations can change this ability.
This change allows to following APIs to resolve data streams: flush,
refresh (already supported data streams), force merge, clear indices cache,
indices stats (already supported data streams), segments, upgrade stats,
upgrade, validate query, searchable snapshots stats, clear searchable snapshots cache and
reload analyzers APIs.
Relates to #53100
This wires `auto_date_histogram` into the rounding optimization that I
built in #55559. This is should significantly speed up any
`auto_date_histogram`s with `time_zone`s on them.
Right now all implementations of the `terms` agg allocate a new
`Aggregator` per bucket. This uses a bunch of memory. Exactly how much
isn't clear but each `Aggregator` ends up making its own objects to read
doc values which have non-trivial buffers. And it forces all of it
sub-aggregations to do the same. We allocate a new `Aggregator` per
bucket for two reasons:
1. We didn't have an appropriate data structure to track the
sub-ordinals of each parent bucket.
2. You can only make a single call to `runDeferredCollections(long...)`
per `Aggregator` which was the only way to delay collection of
sub-aggregations.
This change switches the method that builds aggregation results from
building them one at a time to building all of the results for the
entire aggregator at the same time.
It also adds a fairly simplistic data structure to track the sub-ordinals
for `long`-keyed buckets.
It uses both of those to power numeric `terms` aggregations and removes
the per-bucket allocation of their `Aggregator`. This fairly
substantially reduces memory consumption of numeric `terms` aggregations
that are not the "top level", especially when those aggregations contain
many sub-aggregations. It also is a pretty big speed up, especially when
the aggregation is under a non-selective aggregation like
the `date_histogram`.
I picked numeric `terms` aggregations because those have the simplest
implementation. At least, I could kind of fit it in my head. And I
haven't fully understood the "bytes"-based terms aggregations, but I
imagine I'll be able to make similar optimizations to them in follow up
changes.
* [DOCS] Align with ILM changes.
* Apply suggestions from code review
Co-authored-by: James Rodewig <james.rodewig@elastic.co>
Co-authored-by: Lee Hinman <dakrone@users.noreply.github.com>
* Incorporated review comments.
Even with changes from #48854 we're still seeing significant (as in tens and hundreds of MB)
buffer usage for bulk exports in some cases which destabilizes master nodes.
Since we need to know the serialized length of the bulk body we can't do the serialization
in a streaming manner. (also it's not easily doable with the HTTP client API we're using anyway).
=> let's at least serialize on heap in compressed form and decompress as we're streaming to the
HTTP connection. For small requests this adds negligible overhead but for large requests this reduces
the size of the payload field by about an order of magnitude (empirically determined) which is a massive reduction in size when considering O(100MB) bulk requests.
Armin Braun
Marios Trivyzas
Martijn van Groningen
Andrei Stefan
James Rodewig
Rory Hunter
Dan Hermann
Hendrik Muhs
Marios Trivyzas
Rene Groeschke
Ignacio Vera
Ryan Ernst
Nik Everett
Nick Knize
debadair
Lee Hinman
Tim Brooks
Marc
Benjamin Trent
Brandon Morelli
Lee Hinman
renshuki
zhenxianyimeng
Lisa Cawley
Jim Ferenczi
Rene Groeschke
István Zoltán Szabó
Mark Vieira
Jake Landis