Makes the following changes to the `word_delimiter_graph` token filter
docs:
* Updates the Lucene experimental admonition.
* Updates description
* Adds analyze snippet
* Adds custom analyzer and custom filter snippets
* Reorganizes and updates parameter list
* Expands and updates section re: differences between `word_delimiter`
and `word_delimiter_graph`
* [DOCS] Document `any` keyword in EQL syntax
Adds documentation for the `any` keyword to the EQL syntax docs.
Includes:
* Definition of an event type and its relationship to the event type
field.
* Example matching all event types using `any` keyword
* Example matching event types beginning with a digit
* Example using `any` with `where true`
* Remove references to `event_type_field` default
* Reuse "Events starting with digits" section
* Updates for #53073
The current consensus is that we don't need info actions for smaller items like
field mappers. We can also remove the usage action since the cluster stats API
now tracks information about mappings, like what field types are defined.
Updates the documented default `event_category_field` and `timestamp_field`
values for the EQL search API. Also updates related guidance in the
EQL requirement docs.
Relates to #53073.
Per the [Asciidoctor docs][0], Asciidoctor replaces the following
syntax with double arrows in the rendered HTML:
* => renders as ⇒
* <= renders as ⇐
This escapes several unintended replacements, such as in the Painless
docs.
Where appropriate, it also replaces some double arrow instances with
single arrows for consistency.
[0]: https://asciidoctor.org/docs/user-manual/#replacements
I discussed with @rjernst about what kind of functionality should be
reported in the info API, since it doesn't sound sensible to list every
single feature there. As a guideline, Ryan suggested that functionality
that needs to maintain state should definitely be in the info API, but
probably not field mappers like `constant_keyword`.
This commit introduces hidden aliases. These are similar to hidden
indices, in that they are not visible by default, unless explicitly
specified by name or by indicating that hidden indices/aliases are
desired.
The new alias property, `is_hidden` is implemented similarly to
`is_write_index`, except that it must be consistent across all indices
with a given alias - that is, all indices with a given alias must
specify the alias as either hidden, or all specify it as non-hidden,
either explicitly or by omitting the `is_hidden` property.
Makes the following changes to the `stop` token filter docs:
* Updates description
* Adds a link to the related Lucene filter
* Adds detailed analyze snippet
* Updates custom analyzer and custom filter snippets
* Adds a list of predefined stop words by language
Co-authored-by: ScottieL <36999642+ScottieL@users.noreply.github.com>
This field is a specialization of the `keyword` field for the case when all
documents have the same value. It typically performs more efficiently than
keywords at query time by figuring out whether all or none of the documents
match at rewrite time, like `term` queries on `_index`.
The name is up for discussion. I liked including `keyword` in it, so that we
still have room for a `singleton_numeric` in the future. However I'm unsure
whether to call it `singleton`, `constant` or something else, any opinions?
For this field there is a choice between
1. accepting values in `_source` when they are equal to the value configured
in mappings, but rejecting mapping updates
2. rejecting values in `_source` but then allowing updates to the value that
is configured in the mapping
This commit implements option 1, so that it is possible to reindex from/to an
index that has the field mapped as a keyword with no changes to the source.
Makes the following updates to the EQL search tutorial:
* Adds an API response to the basic tutorial
* Adds an example using the `event_type_field` parm
* Adds an example using the `timestamp_field`parm
* Adds an example using the `query` parm
* Updates example dataset to support more EQL query variety
Makes the following changes to the `trim` token filter docs:
* Updates description
* Adds a link to the related Lucene filter
* Adds tip about removing whitespace using tokenizers
* Adds detailed analyze snippets
* Adds custom analyzer snippet
Adds a warning admonition stating that the `index_options` mapping
parameter is intended only for `text` fields.
Removes an outdated statement regarding default values for numeric
and other datatypes.
implement transform node attributes to disable transform on certain nodes and test which nodes are allowed to do remote connections
closes#52200closes#50033closes#48734
Closes#43990. Describe how to change the default GC settings without changing
the default `jvm.options`. Give examples using `jvm.options.d`, and
`ES_JAVA_OPTS` with Docker.
Adds reporting of memory usage for data frame analytics jobs.
This commit introduces a new index pattern `.ml-stats-*` whose
first concrete index will be `.ml-stats-000001`. This index serves
to store instrumentation information for those jobs.
This adds a new configurable field called `indices_options`. This allows users to create or update the indices_options used when a datafeed reads from an index.
This is necessary for the following use cases:
- Reading from frozen indices
- Allowing certain indices in multiple index patterns to not exist yet
These index options are available on datafeed creation and update. Users may specify them as URL parameters or within the configuration object.
closes https://github.com/elastic/elasticsearch/issues/48056
Tries to load a `Mapper` instance for the mapping snippet of a dynamic template.
This should catch things like using an analyzer that is undefined or mapping attributes that are unused.
This is best effort:
* If `{{name}}` placeholder is used in the mapping snippet then validation is skipped.
* If `match_mapping_type` is not specified then validation is performed for all mapping types.
If parsing succeeds with a single mapping type then this the dynamic mapping is considered valid.
If is detected that a dynamic template mapping snippet is invalid at mapping update time then the mapping update is failed for indices created on 8.0.0-alpha1 and later. For indices created on prior version a deprecation warning is omitted instead. In 7.x clusters the mapping update will never fail in case of an invalid dynamic template mapping snippet and a deprecation warning will always be omitted.
Closes#17411Closes#24419
Co-authored-by: Adrien Grand <jpountz@gmail.com>
This change adds the recall@k metric and refactors precision@k to match
the new metric.
Recall@k is an important metric to use for learning to rank (LTR)
use-cases. Candidate generation or first ranking phase ranking functions
are often optimized for high recall, in order to generate as many
relevant candidates in the top-k as possible for a second phase of
ranking. Adding this metric allows tuning that base query for LTR.
See: https://github.com/elastic/elasticsearch/issues/51676
The introductory sections of the reference manual contains some simplified
instructions for adding a node to the cluster. Unfortunately they are a little
too simplified and only really work for clusters running on `localhost`. If you
try and follow these instructions for a distributed cluster then the new node
will, confusingly, auto-bootstrap itself into a distinct one-node cluster.
Multiple nodes running on localhost is a valid config, of course, but we should
spell out that these instructions are really only for experimentation and that
it takes a bit more work to add nodes to a distributed cluster. This commit
does so.
Also, the "important config" instructions for discovery say that you MUST set
`discovery.seed_hosts` whereas in fact it is fine to ignore this setting and
use a dynamic discovery mechanism instead. This commit weakens this statement
and links to the docs for dynamic discovery mechanisms.
Finally, this section is also overloaded with some technical details that are
not important for this context and are adequately covered elsewhere, and
completely fails to note that the default discovery port is 9300. This commit
addresses this.
Adds the `?refresh=wait_for` query argument to an index API snippet in
the term vectors API docs.
This should ensure the document is indexed and available before a
subsequent term vectors API request executes.
Fixes#52814.
Adds an explicit "important" admonition discouraging apps from using
cat APIs.
cat APIs are intended for human consumption via the command line or
Kibana console only. They are not intended for consumption by
applications.
Indices open with the `niofs` store type load much more data on-heap than
indices open with the `mmapfs` store type. This limitation is now documented
and examples have been updated to show how to update settings to use the
`mmapfs` store type rather than `niofs`.
We should be more explicit about the downsides of disabling replicas and
explain that users should be ready to re-do the entire load in case of
issues mid-way.
One architecture that we have recommended to several users to speed up
indexing involved using CCR to prevent searching from stealing resources
from indexing.
Before boost in script_score query was wrongly applied only to the subquery.
This commit makes sure that the boost is applied to the whole score
that comes out of script.
Closes#48465
Explicitly notes the Elasticsearch API endpoints that support CCS.
This should deter users from attempting to use CCS with other API
endpoints, such as `GET <index>/_doc/<_id>`.
* Adds an example request to the top of the page.
* Relocates several parameters erroneously listed under "Request body"
to the appropriate "Query parameters" section.
* Updates the "Request body" section to better document the NDJSON
structure of msearch requests.
This adds machine learning model feature importance calculations to the inference processor.
The new flag in the configuration matches the analytics parameter name: `num_top_feature_importance_values`
Example:
```
"inference": {
"field_mappings": {},
"model_id": "my_model",
"inference_config": {
"regression": {
"num_top_feature_importance_values": 3
}
}
}
```
This will write to the document as follows:
```
"inference" : {
"feature_importance" : {
"FlightTimeMin" : -76.90955548511226,
"FlightDelayType" : 114.13514762158526,
"DistanceMiles" : 13.731580450792187
},
"predicted_value" : 108.33165831875137,
"model_id" : "my_model"
}
```
This is done through calculating the [SHAP values](https://arxiv.org/abs/1802.03888).
It requires that models have populated `number_samples` for each tree node. This is not available to models that were created before 7.7.
Additionally, if the inference config is requesting feature_importance, and not all nodes have been upgraded yet, it will not allow the pipeline to be created. This is to safe-guard in a mixed-version environment where only some ingest nodes have been upgraded.
NOTE: the algorithm is a Java port of the one laid out in ml-cpp: https://github.com/elastic/ml-cpp/blob/master/lib/maths/CTreeShapFeatureImportance.cc
usability blocked by: https://github.com/elastic/ml-cpp/pull/991
This commit updates the enrich.get_policy API to specify name
as a list, in line with other URL parts that accept a comma-separated
list of values.
In addition, update the get enrich policy API docs
to align the URL part name in the documentation with
the name used in the REST API specs.
* Refresh snapshots with latest look
Add new snapshots with the connection editor to reflect the latest UI.
* Document the effect of the late added params
Add details about the Cloud ID setting, as well as those on the Misc
tab.
Updates the cross-cluster search (CCS) documentation to note how
cluster-level settings are applied.
When `ccs_minimize_roundtrips` is `true`, each cluster applies its own
cluster-level settings to the request.
When `ccs_minimize_roundtrips` is `false`, cluster-level settings for
the local cluster is used. This includes shard limit settings, such as
`action.search.shard_count.limit`, `pre_filter_shard_size`, and
`max_concurrent_shard_requests`. If these limits are set too low, the
request could be rejected.
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>
The example of how to access the nano value of a date_nanos field has
been broken since it was created. This commit fixes it to use the
correct scripting methods.
closes#51931