Fixes a bug in TextFieldMapper serialization when index is false, and adds a
base-class test to ensure that all field mappers are tested against all variations
with defaults both included and excluded.
Fixes#58188
TIME_PARSE works correctly if both date and time parts are specified,
and a TIME object (that contains only time is returned).
Adjust docs and add a unit test that validates the behavior.
Follows: #55223
(cherry picked from commit 9d6b679a5da88f3c131b9bdba49aa92c6c272abe)
Changes:
* Adds additional examples to the `Search a data stream` section of
`Use a data stream`
* Updates existing search docs to make them aware of data streams
This is currently used to set the indexVersionCreated parameter on FieldMapper.
However, this parameter is only actually used by two implementations, and clutters
the API considerably. We should just remove it, and use it directly in the
implementations that require it.
When a numeric value in e.g. a `term` query doesn't fit into a long, it
curerently gets parsed to a BigInteger object, that the various term query
builders store untouched. This leads to serialization errors when these queries
are sent across the wire. Instead we can convert to a string representation
early on, since that is what we store e.g. when indexing big integers into
`keyword` fields anyway.
Closes#57917
Today the read/write locks used internally by CacheFile object are
wrapped into a ReleasableLock. This is not strictly required and also
prevents usage of the tryLock() methods which we would like to use
for early releasing of read operations (#58164).
This change allows to use an `index_filter` in the
field capabilities API. Indices are filtered from
the response if the provided query rewrites to `match_none`
on every shard:
````
GET metrics-*
{
"index_filter": {
"bool": {
"must": [
"range": {
"@timestamp": {
"gt": "2019"
}
}
}
}
}
````
The filtering is done on a best-effort basis, it uses the can match phase
to rewrite queries to `match_none` instead of fully executing the request.
The first shard that can match the filter is used to create the field
capabilities response for the entire index.
Closes#56195
This allows doing true CAS operations on aliases, making sure that an alias is actually properly
moved from a given source index onto a given target index. This is useful to ensure that an
alias is actually moved from a given index to another one, and not just added to another index.
The dangling_indices.import API name could cause issues in the client
libs because import is a reserved word in many languages. Rename the
API to avoid this, and rename the other APIs for consistency.
Related to #48366.
This changes the actions that would attempt to make the managed index read only to
check if the managed index is the write index of a data stream before proceeding.
The updated actions are shrink, readonly, freeze and forcemerge.
(cherry picked from commit c906f631833fee8628f898917a8613a1f436c6b1)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
The version of java printed when a test fails currently is passed in
from gradle. However, we already know this from java itself, so it is
not necessary. This commit changes how the runtime.java repro parameter
is found, as well as removes the compiler.java parameter which is no
longer relevant.
closes#57756
Currently a failed replication action will fail an entire replica. This
includes when replication fails due to potentially short lived transient
issues such as network distruptions or circuit breaking errors.
This commit implements retries using the retryable action.
As part of the "ML in Spaces" project, access to the ML UI in
Kibana is migrating to being controlled by Kibana privileges.
The ML UI will check whether the logged-in user has permission
to do something ML-related using Kibana privileges, and if they
do will call the relevant ML Elasticsearch API using the Kibana
system user. In order for this to work the kibana_system role
needs to have administrative access to ML.
Backport of #58061
Forgot the brackets here in #58214 so in the rare case where the
first update seen by the listener doesn't match it will still remove
itself and never be invoked again -> timeout.
This builds an `auto_date_histogram` aggregator that natively aggregates
from many buckets and uses it when the `auto_date_histogram` used to use
`asMultiBucketAggregator` which should save a significant amount of
memory in those cases. In particular, this happens when
`auto_date_histogram` is a sub-aggregator of a multi-bucketing aggregator
like `terms` or `histogram` or `filters`. For the most part we preserve
the original implementation when `auto_date_histogram` only collects from
a single bucket.
It isn't possible to "just port the aggregator" without taking a pretty
significant performance hit because we used to rewrite all of the
buckets every time we switched to a coarser and coarser rounding
configuration. Without some major surgery to how to delay sub-aggs
we'd end up rewriting the delay list zillions of time if there are many
buckets.
The multi-bucket version of the aggregator has a "budget" of "wasted"
buckets and only rewrites all of the buckets when we exceed that budget.
Now that we don't rebucket every time we increase the rounding we can no
longer get an accurate count of the number of buckets! So instead the
aggregator uses an estimate of the number of buckets to trigger switching
to a coarser rounding. This estimate is likely to be *terrible* when
buckets are far apart compared to the rounding. So it also uses the
difference between the first and last bucket to trigger switching to a
coarser rounding. Which covers for the shortcomings of the bucket
estimation technique pretty well. It also causes the aggregator to emit
fewer buckets in cases where they'd be reduced together on the
coordinating node. This is wonderful! But probably fairly rare.
All of that does buy us some speed improvements when the aggregator is
a child of multi-bucket aggregator:
Without metrics or time zone: 25% faster
With metrics: 15% faster
With time zone: 22% faster
Relates to #56487
This commit bumps our JNA dependency from 4.5.1 to 5.5.0, so that we are
now on the latest maintained line, and pick up a large collection of bug
fixes that have accumulated.
The main improvement here is that the total expected
count of training rows in the test is calculated as the
sum of the training fraction times the cardinality of each
class (instead of the training fraction times the total doc count).
Also relaxes slightly the error bound on the uniformity test from 0.12
to 0.13.
Closes#54122
Backport of #58180
This was a really subtle bug that we introduced a long time ago.
If a shard snapshot is in aborted state but hasn't started snapshotting on a node
we can only send the failed notification for it if the shard was actually supposed
to execute on the local node.
Without this fix, if shard snapshots were spread out across at least two data nodes
(so that each data node does not have all the primaries) the abort would actually
never wait on the data nodes. This isn't a big deal with uuid shard generations
but could lead to potential corruption on S3 when using numeric shard generations
(albeit very unlikely now that we have the 3 minute wait there).
Another negative side-effect of this bug was that master would receive a lot more
shard status update messages for aborted shards since each data node not assigned
a primary would send one message for that primary.
We don't allow converting a data stream's writeable index into a searchable
snapshot. We are currently preventing swapping a data stream's write index
with the restored index.
This adds another step that will not proceed with the searchable snapshot action
until the managed index is not the write index of a data stream anymore.
(cherry picked from commit ccd618ead7cf7f5a74b9fb34524d00024de1479a)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
The dangling indices action is not a proper master node action so it does not
retry when executed while the cluster hasn't fully formed yet.
Since we use node restarts when setting up the dangling indices state we need
to manually ensure a fully formed cluster before moving on with the tests to avoid
failures.
James Rodewig
Alan Woodward
Marios Trivyzas
Dan Hermann
Rory Hunter
Christoph Büscher
Tanguy Leroux
Jim Ferenczi
Yannick Welsch
Rory Hunter
Andrei Dan
Rene Groeschke
Ryan Ernst
Mark Vieira
Julie Tibshirani
Lee Hinman
Tim Brooks
Luca Cavanna
David Roberts
GeChenxin
Benjamin Trent
Armin Braun
Nik Everett
Ignacio Vera
Jason Tedor
Dimitris Athanasiou
Przemyslaw Gomulka
Przemysław Witek
Lisa Cawley
debadair
Przemko Robakowski