This commits add doc values support to geo point using the exact same approach
as for numeric data: geo points for a given document are stored uncompressed
and sequentially in a single binary doc values field.
Close#4207
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
Instead of using the '-f' parameter to start elasticsearch in the
foreground, this is now the default modus.
In order to start elasticsearch in the background, the '-d' parameter
can be used.
Closes#4392
The `text` query was replaced by the `match` query and has been
deprecated for quite a while.
The `field` query should be replaced by a `query_string` query with
the `default_field` specified.
Fixes#4033
This commit changes field data configuration updates so that they are
immediately taken into account for loading new segments. The way it works
is that field data configuration is now cached separately from the field
data cache, meaning that it is now possible to clear the field data
configuration from IndexFieldDataService while the cache will stay around. On
the next time that Elasticsearch will reload field data configuration, it will
check if there is already a cache entry, and reuse it if it exists.
To disable field data loading, all that is required is to change the field
data format to "none" (supported by all field data types) using the update
mapping API. Elasticsearch will then refuse to load field data on any new
segment, but field data which has been loaded on the previous segments will
remain available. So you need to clear the field data cache in order to
reclaim memory (otherwise memory will be reclaimed slower, as segments get
merged).
Close#4430Close#4431
When the ValuesSource has ordinals, terms ordinals are used as a cache key to
bucket ordinals. This can make terms aggregations on String terms significantly
faster.
Close#4350
The percolator uses this option to deal with the fact that the MemoryIndex doesn't support stored fields,
this is possible b/c the _source of the document being percolated is always present.
Closes#4348
This adds support for Lucene's SimpleQueryParser by adding a new type
of query called the `simple_query_string`. The `simple_query_string`
query is designed to be able to parse human-entered queries without
throwing any exceptions.
Resolves#4159
In order to be sure that memory mapped lucene directories are working
one can configure the kernel about how many memory mapped areas
a process may have. This setting ensure for the debian and redhat initscripts
as well as the systemd startup, that this setting is set high enough.
Closes#4397
This contribution is based on the feedback given in issue #4254 and
issue #4255, and should clear things up, when suggestions are being
removed and not displayed anymore after deletion of data.
The Fast Vector Highlighter can combine matches on multiple fields to
highlight a single field using `matched_fields`. This is most
intuitive for multifields that analyze the same string in different
ways. Example:
{
"query": {
"query_string": {
"query": "content.plain:running scissors",
"fields": ["content"]
}
},
"highlight": {
"order": "score",
"fields": {
"content": {
"matched_fields": ["content", "content.plain"],
"type" : "fvh"
}
}
}
}
Closes#3750
Britta Weber
Adrien Grand
Florian Schilling
Andrew Raines
Martijn van Groningen
Clinton Gormley
Richard Pijnenburg
Boaz Leskes
Chris Simpson
spenceralger
Spencer Alger
Grégory Quatannens
Alexander Reelsen
Lee Hinman
Simon Willnauer
Shay Banon
Markus Fischer
Nik Everett
Yousef
Conrad Pankoff
uboness