Update `geo-shape-type.asciidoc` to include all `GeoShapeType`s supported by the `org.elasticsearch.common.geo.builders.ShapeBuilder`.
Changes include:
1. A tabular mapping of GeoJSON types to Elasticsearch types
2. Listing all types, with brief examples, for all support Elasticsearch types
3. Putting non-standard types to the bottom (really just moving Envelope to the bottom)
4. Linking to all GeoJSON types.
5. Adding whitespace around tightly nested arrays (particularly `multipolygon`) for readability
Change the default numeric precision_step to 16 for 64-bit types,
8 for 32-bit and 16-bit types. Disable precision_step for the 8-bit
byte type.
Closes#5905
The `field_value_factor` function uses the value of a field in the
document to influence the score.
A query that looks like:
{
"query": {
"function_score": {
"query": {"match": { "body": "foo" }},
"functions": [
{
"field_value_factor": {
"field": "popularity",
"factor": 1.1,
"modifier": "square"
}
}
],
"score_mode": "max",
"boost_mode": "sum"
}
}
}
Would have the score modified by:
square(1.1 * doc['popularity'].value)
Closes#5519
Currently, boosting on `copy_to` is misleading and does not work as originally specified in #4520. Instead of boosting just the terms from the origin field, it boosts the whole destination field. If two fields copy_to a third field, one with a boost of 2 and another with a boost of 3, all the terms in the third field end up with a boost of 6. This was not the intention.
The alternative: to store the boost in a payload for every term, results in poor performance and inflexibility. Instead, users should either (1) query the common field AND the field that requires boosting, or (2) the multi_match query will soon be able to perform term-centric cross-field matching that will allow per-field boosting at query time (coming in 1.1).
Removed unused misc.asciidoc file
Added plugins directory to directory layout
Fixed transport.tcp.connect_timeout value to match the code found in NetworkService.TcpSettings
Clarified that phrase query does not preserve order of terms
Clarified merge page
Added instructions on how to build documentation to docs/README
When set to false a new strict mode of parsing is employed which
a) does not permit numbers to be passed as JSON strings in quotes
b) rejects numbers with fractions that are passed to integer, short or long fields.
Closes#4117
When upgrading to ES 1.0 the existing mappings with a multi-field type automatically get replaced to a core field with the new `fields` option.
If a `multi_field` type-ed field doesn't have a main / default field, a default field will be chosen for the multi fields syntax. The new main field type
will be equal to the first `multi_field` fields' field or type string if no fields have been configured for the `multi_field` field and in both cases
the default index will not be indexed (`index=no` is set on the default field).
If a `multi_field` typed field has a default field, that field will replace the `multi_field` typed field.
Closes to #4521
* Clean up s/ElasticSearch/Elasticsearch on docs/*
* Clean up s/ElasticSearch/Elasticsearch on src/* bin/* & pom.xml
* Clean up s/ElasticSearch/Elasticsearch on NOTICE.txt and README.textile
Closes#4634
Norms can be eagerly loaded on a per-field basis by setting norms.loading to
`eager` instead of the default `lazy`:
```
"my_string_field" : {
"type": "string",
"norms": {
"loading": "eager"
}
}
```
In case this behavior should be applied to all fields, it is possible to change
the default value by setting `index.norms.loading` to `eager`.
Close#4079
This commit allows to trade precision for memory when storing geo points.
This new field data impl accepts a `precision` parameter that controls the
maximum expected error for storing coordinates. This option can be updated on
a live index with the PUT mapping API.
Default precision is 1cm, which requires 8 bytes per geo-point (50% memory
saving compared to using 2 doubles).
Close#4386
The setting causes the upper bound for a range query/filter to be rounded up,
therefore the name `round_ceil` seems to make more sense.
Also this commit removes the redundant fourth parameter to DateMathParser.parse(..)
which was never used.
was: parse(String text, long now, boolean roundUp, boolean upperInclusive)
is now: parse(String text, long now, boolean roundCeil)
closes#3914
This commit allows for using Lucene doc values as a backend for field data,
moving the cost of building field data from the refresh operation to indexing.
In addition, Lucene doc values can be stored on disk (partially, or even
entirely), so that memory management is done at the operating system level
(file-system cache) instead of the JVM, avoiding long pauses during major
collections due to large heaps.
So far doc values are supported on numeric types and non-analyzed strings
(index:no or index:not_analyzed). Under the hood, it uses SORTED_SET doc values
which is the only type to support multi-valued fields. Since the field data API
set is a bit wider than the doc values API set, some operations are not
supported:
- field data filtering: this will fail if doc values are enabled,
- field data cache clearing, even for memory-based doc values formats,
- getting the memory usage for a specific field,
- knowing whether a field is actually multi-valued.
This commit also allows for configuring doc-values formats on a per-field basis
similarly to postings formats. In particular the doc values format of the
_version field can be configured through its own field mapper (it used to be
handled in UidFieldMapper previously).
Closes#3806
Steve Fuller
gseng
Rob Young
Simon Willnauer
Itamar Syn-Hershko
Radu Gheorghe
pickypg
Kevin Wang
Robert Muir
eliasah
Yousef
Igor Motov
Lee Hinman
David Pilato
Adrien Grand
Jun Ohtani
Clinton Gormley
Konrad Feldmeier
Martijn van Groningen
James Yu
Brusic
markharwood
Nik Everett
Britta Weber
Matt Weber
Boaz Leskes
Subhash Gopalakrishnan
gtt116