At time of writing, GeoJSON did not enforce a specific ordering of vertices in
a polygon, but it now does. We occasionally get reports of Elasticsearch
rejecting apparently-valid GeoJSON because of badly oriented polygons, and it's
helpful to be able to point at this bit of the documentation when responding.
This enhancement adds Z value support (source only) to geo_shape fields. If vertices are provided with a third dimension, the third dimension is ignored for indexing but returned as part of source. Like beofre, any values greater than the 3rd dimension are ignored.
closes#23747
This will reject mapping updates to the `_default_` mapping with 7.x indices
and still emit a deprecation warning with 6.x indices.
Relates #15613
Supersedes #28248
Currently the callouts for this section are below all the examples, making it
harder to relate them to the snippets. Instead they should be moved closer
to the examples.
This adds the ability to index term prefixes into a hidden subfield, enabling prefix queries to be run without multitermquery rewrites. The subfield reuses the analysis chain of its parent text field, appending an EdgeNGramTokenFilter. It can be configured with minimum and maximum ngram lengths. Query terms with lengths outside this min-max range fall back to using prefix queries against the parent text field.
The mapping looks like this:
"my_text_field" : {
"type" : "text",
"analyzer" : "english",
"index_prefix" : { "min_chars" : 1, "max_chars" : 10 }
}
Relates to #27049
Since #25826 we reject infinite values for float, double and half_float
datatypes. This change adds this restriction to the documentation for the
supported datatypes.
Closes#27653
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
* Caps
* Fix awkward wording that took multiple passes to parse
* Floating point _number_
* Something more descriptive about the `scaled_float` scaling factor.
Add an index level setting `index.mapping.nested_objects.limit` to control
the number of nested json objects that can be in a single document
across all fields. Defaults to 10000.
Throw an error if the number of created nested documents exceed this
limit during the parsing of a document.
Closes#26962
This section was removed to hide this ability to new users.
This change restores the section and adds a warning regarding the expected performance.
Closes#27336
extract all clauses from a conjunction query.
When clauses from a conjunction are extracted the number of clauses is
also stored in an internal doc values field (minimum_should_match field).
This field is used by the CoveringQuery and allows the percolator to
reduce the number of false positives when selecting candidate matches and
in certain cases be absolutely sure that a conjunction candidate match
will match and then skip MemoryIndex validation. This can greatly improve
performance.
Before this change only a single clause was extracted from a conjunction
query. The percolator tried to extract the clauses that was rarest in order
(based on term length) to attempt less candidate queries to be selected
in the first place. However this still method there is still a very high
chance that candidate query matches are false positives.
This change also removes the influencing query extraction added via #26081
as this is no longer needed because now all conjunction clauses are extracted.
https://www.elastic.co/guide/en/elasticsearch/reference/6.x/percolator.html#_influencing_query_extractionCloses#26307
Numeric fields no longer support the index_options parameter. This changes the parameter
to be rejected in numeric field types after it was deprecated in 6.0.
Closes#21475
The percolator will add a `_percolator_document_slot` field to all percolator
hits to indicate with what document it has matched. This number matches with
the order in which the documents have been specified in the percolate query.
Also improved the support for multiple percolate queries in a search request.
The `index.percolator.map_unmapped_fields_as_text` is a more better name, because unmapped fields are mapped to a text field with default settings
and string is no longer a field type (it is either keyword or text).
* Remove the _all metadata field
This change removes the `_all` metadata field. This field is deprecated in 6
and cannot be activated for indices created in 6 so it can be safely removed in
the next major version (e.g. 7).
The percolator field mapper doesn't need to extract all terms and ranges from a bool query with must or filter clauses.
In order to help to default extraction behavior, boost fields can be configured, so that fields that are known for not being
selective enough can be ignored in favor for other fields or clauses with specific fields can forcefully take precedence over other clauses.
This can help selecting clauses for fields that don't match with a lot of percolator queries over other clauses and thus improving performance of the percolate query.
For example a status like field is something that should configured as an ignore field.
Queries on this field tend to match with more documents and so if clauses for this fields
get selected as best clause then that isn't very helpful for the candidate query that the
percolate query generates to filter out percolator queries that are likely not going to match.
The Writeble representation is less heavy to parse and that will benefit percolate performance and throughput.
The query builder's binary format has now the same bwc guarentees as the xcontent format.
Added a qa test that verifies that percolator queries written in older versions are still readable by the current version.
Today if we search across a large amount of shards we hit every shard. Yet, it's quite
common to search across an index pattern for time based indices but filtering will exclude
all results outside a certain time range ie. `now-3d`. While the search can potentially hit
hundreds of shards the majority of the shards might yield 0 results since there is not document
that is within this date range. Kibana for instance does this regularly but used `_field_stats`
to optimize the indexes they need to query. Now with the deprecation of `_field_stats` and it's upcoming removal a single dashboard in kibana can potentially turn into searches hitting hundreds or thousands of shards and that can easily cause search rejections even though the most of the requests are very likely super cheap and only need a query rewriting to early terminate with 0 results.
This change adds a pre-filter phase for searches that can, if the number of shards are higher than a the `pre_filter_shard_size` threshold (defaults to 128 shards), fan out to the shards
and check if the query can potentially match any documents at all. While false positives are possible, a negative response means that no matches are possible. These requests are not subject to rejection and can greatly reduce the number of shards a request needs to hit. The approach here is preferable to the kibana approach with field stats since it correctly handles aliases and uses the correct threadpools to execute these requests. Further it's completely transparent to the user and improves scalability of elasticsearch in general on large clusters.
