This commit removes the documentation for some specific Searchable Snapshot REST APIs:
- clear cache
- searchable snapshot stats
- repository stats
These APIs are low-level and are useful to investigate the behavior of snapshot
backed indices but we expect them to be removed in the future or to appear in
a different form.
Avoiding a number of noop updates that were observed to cause trouble (as in needless noop CS publishing) which can become an issue when working with a large number of concurrent snapshot operations.
Also this sets up some simplifications made in the clone snapshot branch.
Backporting #62205 to 7.x branch.
This is similar to what happens for indices. Initially we decided to let each test cleanup the
data streams it created.
The reason behind this was that client yaml test runners would need to be modified to do this too and
because data steams were new, we waited with that and let each test cleanup the data stream it created.
However we sometimes have very hard to debug test failures, because many tests fail because another test
failed mid way and didn't clean up the data streams it created. Given that and data streams exist in
the code base for a while now, we should automatically delete all data streams after each yaml test.
Relates to #62190
* preserve data streams for rolling upgrade yaml tests
Previously the "mappings" field of the response from the
find_file_structure endpoint was not a drop-in for the
mappings format of the create index endpoint - the
"properties" layer was missing. The reason for omitting
it initially was that the assumption was that the
find_file_structure endpoint would only ever return very
simple mappings without any nested objects. However,
this will not be true in the future, as we will improve
mappings detection for complex JSON objects. As a first
step it makes sense to move the returned mappings closer
to the standard format.
This is a small building block towards fixing #55616
- Extract distribution archives defaults into plugin
- Added basic test coverage
- Avoid packaging/unpackaging cycle when relying on locally build distributions
- Provide DSL for setting up distribution archives
- Cleanup archives build script
The hard bounds were incorrectly scaled for intervals, which was
causing incorrect buckets to show up or no buckets at all for
interval other than 1.
Closes#62126
Add test for item-level error when no write index defined for an alia…
Co-authored-by: Jake Landis <jake.landis@elastic.co>
Co-authored-by: bellengao <gbl_long@163.com>
This commit removes `integTest` task from all es-plugins.
Most relevant projects have been converted to use yamlRestTest, javaRestTest,
or internalClusterTest in prior PRs.
A few projects needed to be adjusted to allow complete removal of this task
* x-pack/plugin - converted to use yamlRestTest and javaRestTest
* plugins/repository-hdfs - kept the integTest task, but use `rest-test` plugin to define the task
* qa/die-with-dignity - convert to javaRestTest
* x-pack/qa/security-example-spi-extension - convert to javaRestTest
* multiple projects - remove the integTest.enabled = false (yay!)
related: #61802
related: #60630
related: #59444
related: #59089
related: #56841
related: #59939
related: #55896
This prevent `keyword` valued runtime scripts from emitting too many
values or values that take up too much space. Without this you can put
allocate a ton of memory with the script by sticking it into a tight
loop. Painless has some protections against this but:
1. I don't want to rely on them out of sheer paranoia
2. They don't really kick in when the script uses callbacks like we do
anyway.
Relates to #59332
The `global_ordinals` implementation of `terms` had a bug when
`min_doc_count: 0` that'd cause sub-aggregations to have array index out
of bounds exceptions. Ooops. My fault. This fixes the bug by assigning
ordinals to those buckets.
Closes#62084
* [ML] only persist progress if it has changed
We already search for the previously stored progress document.
For optimization purposes, and to prevent restoring the same
progress after a failed analytics job is stopped,
this commit does an equality check between the previously stored progress and current progress
If the progress has changed, persistence continues as normal.
The windows service script does a little munging of the parsed JVM
option string, converting whitespaces to semicolons. We recently added
an optional Java 14 JDK flag to our system JVM flags. On earlier JDKs,
the windows service batch script would encounter a double whitespace
when this option was missing and convert it into double semicolons.
Double semicolons, in turn, don't work in the arguments to the windows
service command, and led to a lot of JVM options being dropped,
including "es.path.conf", which is required for startup.
This commit puts in a double defense. First, it removes any empty-string
options from the system options list in the Java Options Parser code.
Second, it munges out double semicolons if they do appear in the parsed
option output.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
When a tree model is provided, it is possible that it is a stump.
Meaning, it only has one node with no splits
This implies that the tree has no features. In this case,
having zero feature_names is appropriate. In any other case,
this should be considered a validation failure.
This commit adds the validation if there is more than 1 node,
that the feature_names in the model are non-empty.
closes#60759
Fixing a few spots where NOOP tasks on the snapshot pool were created needlessly.
Especially when it comes to mixed master+data nodes and concurrent snapshots these
hurt delete operation performance needlessly.
Fetch failures are currently tracked byy AsyncSearchTask like ordinary shard failures. Though they should be treated differently or they end up causing weird scenarios like total=num_shards and successful=num_shards as the query phase ran fine yet the failed count would reflect the number of shards where fetch failed.
Given that partial results only include aggs for now and are complete even if fetch fails, we can ignore fetch failures in async search, as they will be anyways included in the response. They are in fact either received as a failure when all shards fail during fetch, or as part of the final response when only some shards fail during fetch.
As part of #60275 QueryPhaseResultConsumer ended up calling SearchProgressListener#onPartialReduce directly instead of notifyPartialReduce. That means we don't catch exceptions that may occur while executing the progress listener callback.
This commit fixes the call and adds a test for this scenario.
Currently, the async search task is the task that will be running through the whole execution of an async search. While the submit async search task prints out the search as part of its description, async search task doesn't while it should.
With this commit we address that while also making sure that the description highlights that the task is originated from an async search.
Also, we streamline the way the description is printed out by SearchTask so that it does not get forgotten in the future.
Wildcard field bug fix for term and prefix queries.
We now escape any * or ? characters in the search string before delegating to the main wildcardQuery() method.
Closes#62081
In many cases we don't need a `StreamInput` or `StreamOutput`
wrapper around these streams so I this commit adjusts the API
to just normal streams and adds the wrapping where necessary.
Kibana often highlights *everything* like this:
```
POST /_search
{
"query": ...,
"size": 500,
"highlight": {
"fields": {
"*": { ... }
}
}
}
```
This can get slow when there are hundreds of mapped fields. I tested
this locally and unscientifically and it took a request from 20ms to
150ms when there are 100 fields. I've seen clusters with 2000 fields
where simple search go from 500ms to 1500ms just by turning on this sort
of highlighting. Even when the query is just a `range` that and the
fields are all numbers and stuff so it won't highlight anything.
This speeds up the `unified` highlighter in this case in a few ways:
1. Build the highlighting infrastructure once field rather than once pre
document per field. This cuts out a *ton* of work analyzing the query
over and over and over again.
2. Bail out of the highlighter before loading values if we can't produce
any results.
Combined these take that local 150ms case down to 65ms. This is unlikely
to be really useful when there are only a few fetched docs and only a
few fields, but we often end up having many fields with many fetched
docs.
This also adds the ability to define a serialization check on Parameters, used
in this case to only serialize format and locale parameters if the mapper is a
date range.
James Rodewig
Francisco Fernández Castaño
Adam Locke
Tanguy Leroux
Armin Braun
Ignacio Vera
Martijn van Groningen
Hendrik Muhs
Andrei Stefan
Yannick Welsch
David Roberts
Rene Groeschke
Jake Landis
Igor Motov
Nik Everett
Lisa Cawley
Christoph Büscher
Dan Hermann
Benjamin Trent
William Brafford
Luca Cavanna
Rory Hunter
David Kyle
markharwood
Dimitris Athanasiou
Yang Wang
Julie Tibshirani
Alan Woodward