* Added an extra `field` parameter to the `percolator` query to indicate what percolator field should be used. This must be an existing field in the mapping of type `percolator`.
* The `.percolator` type is now forbidden. (just like any type that starts with a `.`)
This only applies for new indices created on 5.0 and later. Indices created on previous versions the .percolator type is still allowed to exist.
The new `percolator` field type isn't active in such indices and the `PercolatorQueryCache` knows how to load queries from these legacy indices.
The `PercolatorQueryBuilder` will not enforce that the `field` parameter is of type `percolator`.
This makes all numeric fields including `date`, `ip` and `token_count` use
points instead of the inverted index as a lookup structure. This is expected
to perform worse for exact queries, but faster for range queries. It also
requires less storage.
Notes about how the change works:
- Numeric mappers have been split into a legacy version that is essentially
the current mapper, and a new version that uses points, eg.
LegacyDateFieldMapper and DateFieldMapper.
- Since new and old fields have the same names, the decision about which one
to use is made based on the index creation version.
- If you try to force using a legacy field on a new index or a field that uses
points on an old index, you will get an exception.
- IP addresses now support IPv6 via Lucene's InetAddressPoint and store them
in SORTED_SET doc values using the same encoding (fixed length of 16 bytes
and sortable).
- The internal MappedFieldType that is stored by the new mappers does not have
any of the points-related properties set. Instead, it keeps setting the index
options when parsing the `index` property of mappings and does
`if (fieldType.indexOptions() != IndexOptions.NONE) { // add point field }`
when parsing documents.
Known issues that won't fix:
- You can't use numeric fields in significant terms aggregations anymore since
this requires document frequencies, which points do not record.
- Term queries on numeric fields will now return constant scores instead of
giving better scores to the rare values.
Known issues that we could work around (in follow-up PRs, this one is too large
already):
- Range queries on `ip` addresses only work if both the lower and upper bounds
are inclusive (exclusive bounds are not exposed in Lucene). We could either
decide to implement it, or drop range support entirely and tell users to
query subnets using the CIDR notation instead.
- Since IP addresses now use a different representation for doc values,
aggregations will fail when running a terms aggregation on an ip field on a
list of indices that contains both pre-5.0 and 5.0 indices.
- The ip range aggregation does not work on the new ip field. We need to either
implement range aggs for SORTED_SET doc values or drop support for ip ranges
and tell users to use filters instead. #17700Closes#16751Closes#17007Closes#11513
The doc mentions match_path in one place but the correct syntax is path_match which is mentioned everywhere else. Using the wrong string leads to errors because the mapping becomes too greedy, and matches things it shouldn't.
This is to prevent mapping explosion when dynamic keys such as UUID are used as field names. index.mapping.total_fields.limit specifies the total number of fields an index can have. An exception will be thrown when the limit is reached. The default limit is 1000. Value 0 means no limit. This setting is runtime adjustable
Closes#11443
This commit updates the documentation for GeoPointField by removing all references to the coerce and doc_values parameters. DocValues are enabled in lucene GeoPointField by default (required for boundary filtering). The QueryBuilders are updated to automatically normalize points (ignoring the coerce parameter) for any index created onOrAfter version 2.2.
Warmers are now barely useful and will be removed in 3.0. Note that this only
removes the warmer API and query-based warmers. We still have warmers internally
for eg. global ordinals.
Close#15607
This commit adds the following:
* SpatialStrategy documentation to the geo-shape reference docs.
* Updates relation documentation to geo-shape-query reference docs.
* Updates GeoShapeFiledMapper to set points_only to true if TERM strategy is used (to be consistent with documentation)
Some users may already be familiar with column stores, so saying more explicitly
that doc values are a columnar representation of the data may help them better
and/or more quickly understand what doc values are about.