If there are percolator queries containing `range` queries with ranges based on the current time then this can lead to incorrect results if the `percolate` query gets cached. These ranges are changing each time the `percolate` query gets executed and if this query gets cached then the results will be based on how the range was at the time when the `percolate` query got cached.
The ExtractQueryTermsService has been renamed `QueryAnalyzer` and now only deals with analyzing the query (extracting terms and deciding if the entire query is a verified match) . The `PercolatorFieldMapper` is responsible for adding the right fields based on the analysis the `QueryAnalyzer` has performed, because this is highly dependent on the field mappings. Also the `PercolatorFieldMapper` is responsible for creating the percolate query.
Rename `fields` to `stored_fields` and add `docvalue_fields`
`stored_fields` parameter will no longer try to retrieve fields from the _source but will only return stored fields.
`fields` will throw an exception if the user uses it.
Add `docvalue_fields` as an adjunct to `fielddata_fields` which is deprecated. `docvalue_fields` will try to load the value from the docvalue and fallback to fielddata cache if docvalues are not enabled on that field.
Closes#18943
`stored_fields` parameter will no longer try to retrieve fields from the _source but will only return stored fields.
`fields` will throw an exception if the user uses it.
Add `docvalue_fields` as an adjunct to `fielddata_fields` which is deprecated. `docvalue_fields` will try to load the value from the docvalue and fallback to fielddata cache if docvalues are not enabled on that field.
Closes#18943
They have been implemented in https://issues.apache.org/jira/browse/LUCENE-7289.
Ranges are implemented so that the accuracy loss only occurs at index time,
which means that if you are searching for values between A and B, the query will
match exactly all documents whose value rounded to the closest half-float point
is between A and B.
`doc_values` for _type field are created but any attempt to load them throws an IAE.
This PR re-enables `doc_values` loading for _type, it also enables `fielddata` loading for indices created between 2.0 and 2.1 since doc_values were disabled during that period.
It also restores the old docs that gives example on how to sort or aggregate on _type field.
Remove the arbitrary limit on epoch_millis and epoch_seconds of 13 and 10
characters, respectively. Instead allow any character combination that can
be converted to a Java Long.
Update the docs to reflect this change.
* Docs: First pass at improving analyzer docs
I've rewritten the intro to analyzers plus the docs
for all analyzers to provide working examples.
I've also removed:
* analyzer aliases (see #18244)
* analyzer versions (see #18267)
* snowball analyzer (see #8690)
Next steps will be tokenizers, token filters, char filters
* Fixed two typos
Adds infrastructure so `gradle :docs:check` will extract tests from
snippets in the documentation and execute the tests. This is included
in `gradle check` so it should happen on CI and during a normal build.
By default each `// AUTOSENSE` snippet creates a unique REST test. These
tests are executed in a random order and the cluster is wiped between
each one. If multiple snippets chain together into a test you can annotate
all snippets after the first with `// TEST[continued]` to have the
generated tests for both snippets joined.
Snippets marked as `// TESTRESPONSE` are checked against the response
of the last action.
See docs/README.asciidoc for lots more.
Closes#12583. That issue is about catching bugs in the docs during build.
This catches *some* bugs in the docs during build which is a good start.
* 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.
detect_noop is pretty cheap and noop updates compartively expensive so this
feels like a sensible default.
Also had to do some testing and documentation around how _ttl works with
detect_noop.
Closes#11282
This is much more fiddly than you'd expect it to be because of the way
position_offset_gap is applied in StringFieldMapper. Instead of setting
the default to 100 its simpler to make sure that all the analyzers default
to 100 and that StringFieldMapper doesn't override the default unless the
user specifies something different. Unless the index was created before
2.1, in which case the old default of 0 has to take.
Also postition_offset_gaps less than 0 aren't allowed at all.
New tests test that:
1. the new default doesn't match phrases across values with reasonably low
slop (5)
2. the new default doest match phrases across values with reasonably high
slop (50)
3. you can override the value and phrases work as you'd expect
4. if you leave the value undefined in the mapping and define it on a
custom analyzer the the value from the custom analyzer shines through
Closes#7268
This move the `murmur3` field to the `mapper-murmur3` plugin and fixes its
defaults so that values will not be indexed by default, as the only purpose
of this field is to speed up `cardinality` aggregations on high-cardinality
string fields, which only requires doc values.
I also removed the `rehash` option from the `cardinality` aggregation as it
doesn't bring much value (rehashing is cheap) and allowed to remove the
coupling between the `cardinality` aggregation and the `murmur3` field.
Close#12874
* Centralised plugin docs in docs/plugins/
* Moved integrations into same docs
* Moved community clients into the clients section of the docs
* Removed docs/community
Closes#11734Closes#11724Closes#11636Closes#11635Closes#11632Closes#11630Closes#12046Closes#12438Closes#12579
Clinton Gormley
Martijn van Groningen
Britta Weber
Jim Ferenczi
Robert Muir
Robert Muir
Adrien Grand
G. Richard Bellamy
Nik Everett
Robin Joseph
Shane Connelly
Christoph Büscher
LeonardGC
Ibrahim Awwal
Sergii Golubev
Yanjun Huang
Nicholas Knize
Dongjoon Hyun
Rachit Gupta
Yannick Welsch
Felipe Forbeck
Imran Azad
umeku
Andrew Williams
Ben Tse
Jason Tedor
David Pilato
xuzha
loopmachine
Ryan Ernst