This commit changes the default out-of-the-box configuration for the
number of shards from five to one. We think this will help address a
common problem of oversharding. For users with time-based indices that
need a different default, this can be managed with index templates. For
users with non-time-based indices that find they need to re-shard with
the split API in place they no longer need to resort only to
reindexing.
Since this has the impact of changing the default number of shards used
in REST tests, we want to ensure that we still have coverage for issues
that could arise from multiple shards. As such, we randomize (rarely)
the default number of shards in REST tests to two. This is managed via a
global index template. However, some tests check the templates that are
in the cluster state during the test. Since this template is randomly
there, we need a way for tests to skip adding the template used to set
the number of shards to two. For this we add the default_shards feature
skip. To avoid having to write our docs in a complicated way because
sometimes they might be behind one shard, and sometimes they might be
behind two shards we apply the default_shards feature skip to all docs
tests. That is, these tests will always run with the default number of
shards (one).
* Clarify documentation of scroll_id
The Scroll API may return the same scroll ID for multiple requests due to server side state. This is not clear from the current documentation.
* Further clarify scroll ID return behaviour
Some features have been deprecated since `6.0` like the `_parent` field or the
ability to have multiple types per index. This allows to remove quite some
code, which in-turn will hopefully make it easier to proceed with the removal
of types.
The rank_eval documentation was missing an explanation of the parameter
`k` that controls the number of top hits that are used in the ranking evaluation.
Closes#29205
Increase the default limit of `index.highlight.max_analyzed_offset` to 1M instead of previous 10K.
Enhance an error message when offset increased to include field name, index name and doc_id.
Relates to https://github.com/elastic/kibana/issues/16764
* Search option terminate_after does not handle post_filters and aggregations correctly
This change fixes the handling of the `terminate_after` option when post_filters (or min_score) are used.
`post_filter` should be applied before `terminate_after` in order to terminate the query when enough document are accepted
by the post_filters.
This commit also changes the type of exception thrown by `terminate_after` in order to ensure that multi collectors (aggregations)
do not try to continue the collection when enough documents have been collected.
Closes#28411
Adds allow_partial_search_results flag to search requests with default setting = true.
When false, will error if search either timeouts, has partial errors or has missing shards rather
than returning partial search results. A cluster-level setting provides a default for search requests with no flag.
Closes#27435
This change adds support for the new ranking evaluation API to the High Level Rest Client.
This mostly means adding support for parsing the various response objects back from the
REST representation. It includes one change to the response syntax where previously we didn't
print the type of the metric details section but we now need it to pick the right parser to
parse this section back.
Closes#28198
* Limit the analyzed text for highlighting
- Introduce index level settings to control the max number of character
to be analyzed for highlighting
- Throw an error if analysis is required on a larger text
Closes#27517
Allowing `_doc` as a type will enable users to make the transition to 7.0
smoother since the index APIs will be `PUT index/_doc/id` and `POST index/_doc`.
This also moves most of the documentation to `_doc` as a type name.
Closes#27750Closes#27751
Also include _type and _id for parent/child hits inside inner hits.
In the case of top_hits aggregation the nested search hits are
directly returned and are not grouped by a root or parent document, so
it is important to include the _id and _index attributes in order to know
to what documents these nested search hits belong to.
Closes#27053
Today we require users to prepare their indices for split operations.
Yet, we can do this automatically when an index is created which would
make the split feature a much more appealing option since it doesn't have
any 3rd party prerequisites anymore.
This change automatically sets the number of routinng shards such that
an index is guaranteed to be able to split once into twice as many shards.
The number of routing shards is scaled towards the default shard limit per index
such that indices with a smaller amount of shards can be split more often than
larger ones. For instance an index with 1 or 2 shards can be split 10x
(until it approaches 1024 shards) while an index created with 128 shards can only
be split 3x by a factor of 2. Please note this is just a default value and users
can still prepare their indices with `index.number_of_routing_shards` for custom
splitting.
NOTE: this change has an impact on the document distribution since we are changing
the hash space. Documents are still uniformly distributed across all shards but since
we are artificually changing the number of buckets in the consistent hashign space
document might be hashed into different shards compared to previous versions.
This is a 7.0 only change.
Some code-paths use anonymous classes (such as NonCollectingAggregator
in terms agg), which messes up the display name of the profiler. If
we encounter an anonymous class, we need to grab the super's name.
Another naming issue was that ProfileAggs were not delegating to the
wrapped agg's name for toString(), leading to ugly display.
This PR also fixes up the profile documentation. Some of the examples were
executing against empty indices, which shows different profile results
than a populated index (and made for confusing examples).
Finally, I switched the agg display names from the fully qualified name
to the simple name, so that it's similar to how the query profiles work.
Closes#26405