Hi,
I've created a query builder DSL for Kotlin language that mimics the JSON query DSL.
This makes it easier to translate the documentation targeting the JSON api onto kotlin code.
Please consider adding it to the list of community clients.
Thanks,
Mike Buhot
This commit actually bounds the size of the generic thread pool. The
generic thread pool was of type cached, a thread pool with an unbounded
number of workers and an unbounded work queue. With this commit, the
generic thread pool is now of type scaling. As such, the cached thread
pool type has been removed. By default, the generic thread pool is
constructed with a core pool size of four, a max pool size of 128 and
idle workers can be reaped after a keep-alive time of thirty seconds
expires. The work queue for this thread pool remains unbounded.
The getting started docs use dynamic mappings. With the recent change to
string split into text and keyword, text lost the default ability to do
aggs. This was added back in #17188. This change updates the getting
started examples to use the keyword multi field added to dynamically
mapped text fields.
closes#17941
Lucene allows to create a ICUTokenizer with a special config argument
enabling the customization of the rule based iterator by providing
custom rules files.
This commit enable this feature. Users could provide a list of RBBI rule
files to ICU tokenizer.
closes#13146
* `rename` processor, renamed `to` to `target_field`
* `date` processor, renamed `match_field` to `field` and renamed `match_formats` to `formats`
* `geoip` processor, renamed `source_field` to `field` and renamed `fields` to `properties`
* `attachment` processor, renamed `source_field` to `field` and renamed `fields` to `properties`
Closes#17835
Adds a `fingerprint` token filter which uses Lucene's FingerprintFilter,
and a `fingerprint` analyzer that combines the Fingerprint filter with
lowercasing, stop word removal and asciifolding.
Closes#13325
In Elasticsearch 5.0.0, by default unquoted field names in JSON will be
rejected. This can cause issues, however, for documents that were
already indexed with unquoted field names. To alleviate this, a system
property has been added that can be enabled so migration can occur.
This system property will be removed in Elasticsearch 6.0.0
Resolves#17674
* 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`.
We advertise in our documentation that byte units are like `kb`, `mb`... But we actually only support the simple notation `k` or `m`.
This commit adds support for the documented form and keeps the non documented options to avoid any breaking change.
It also adds support for `micros`, `nanos` and `d` as a time unit in `_cat` API.
Remove the support for `b` as a SizeValue unit. Actually, for numbers, when using raw numbers without unit, there is no text to add/parse after the number. For example, you don't write `10` as `10b`. We support option like `size=` in `_cat` API which means that we want to display raw data without unit (singles).
Documentation updated accordingly.
Add test for the empty size option.
Fix missing TimeValues options for some cat APIs
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 change adds a new option to the geo_* queries: ignore_unmapped. If this option is set to false, the toQuery method on the QueryBuilder will throw an exception if the field specified in the query is unmapped. If the option is set to true, the toQuery method on the QueryBuilder will return a MatchNoDocsQuery. The default value is false so the queries work how they do today (throwing an exception on unmapped field)
