Inner hits allows to embed nested inner objects, children documents or the parent document that contributed to the matching of the returned search hit as inner hits, which would otherwise be hidden.
Closes#8153Closes#3022Closes#3152
This is functionally equivalent to before, so there should be no
user-visible impact, except I added a NOTE in the docs warning about
the interaction of pagination and rescoring.
Closes#6232Closes#7707
Aggregations are collection-wide statistics, which is incompatible with the
collection mode of search_type=SCAN since it doesn't collect all matches on
calls to the search API.
Close#7429
Aggregations are collection-wide statistics so they would always be the same.
In order to save CPU/bandwidth, we can just return them on the first page.
Same as #1642 but for aggregations.
Because json objects are unordered this also adds an explicit order syntax
that looks like
"highlight": {
"fields": [
{"title":{ /*params*/ }},
{"text":{ /*params*/ }}
]
}
This is not useful for any of the builtin highlighters but will be useful
in plugins.
Closes#4649
In #4052 we added support for highlighting multi term queries using the postings highlighter. That worked only for top-level queries though, and not for multi term queries that are nested for instance within a bool query, or filtered query, or a constant score query.
The way we make this work is by walking the query structure and temporarily overriding the query rewrite method with a method that allows for multi terms extraction.
Closes#5102
Detects if rescores arrive as an array instead of a plain object. If so
then parse each element of the array as a separate rescore to be executed
one after another. It looks like this:
"rescore" : [ {
"window_size" : 100,
"query" : {
"rescore_query" : {
"match" : {
"field1" : {
"query" : "the quick brown",
"type" : "phrase",
"slop" : 2
}
}
},
"query_weight" : 0.7,
"rescore_query_weight" : 1.2
}
}, {
"window_size" : 10,
"query" : {
"score_mode": "multiply",
"rescore_query" : {
"function_score" : {
"script_score": {
"script": "log10(doc['numeric'].value + 2)"
}
}
}
}
} ]
Rescores as a single object are still supported.
Closes#4748
Adds a new FetchSubPhase, FieldDataFieldsFetchSubPhase, which loads the
field data cache for a field and returns an array of values for the
field.
Also removes `doc['<field>']` and `_source.<field>` workaround no longer
needed in field name resolving.
Closes#4492
The FVH was throwing away some boosts on queries stopping a number of
ways to boost phrase matches to the top of the list of fragments from
working.
The plain highlighter also doesn't work for this but that is because it
doesn't support the concept of the same term having a different score at
different positions.
Also update documentation claiming that FHV is nicer for weighing terms
found by query combinations.
Closes#4351
* 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
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
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
Requires field index_options set to "offsets" in order to store positions and offsets in the postings list.
Considerably faster than the plain highlighter since it doesn't require to reanalyze the text to be highlighted: the larger the documents the better the performance gain should be.
Requires less disk space than term_vectors, needed for the fast_vector_highlighter.
Breaks the text into sentences and highlights them. Uses a BreakIterator to find sentences in the text. Plays really well with natural text, not quite the same if the text contains html markup for instance.
Treats the document as the whole corpus, and scores individual sentences as if they were documents in this corpus, using the BM25 algorithm.
Uses forked version of lucene postings highlighter to support:
- per value discrete highlighting for fields that have multiple values, needed when number_of_fragments=0 since we want to return a snippet per value
- manually passing in query terms to avoid calling extract terms multiple times, since we use a different highlighter instance per doc/field, but the query is always the same
The lucene postings highlighter api is quite different compared to the existing highlighters api, the main difference being that it allows to highlight multiple fields in multiple docs with a single call, ensuring sequential IO.
The way it is introduced in elasticsearch in this first round is a compromise trying not to change the current highlight api, which works per document, per field. The main disadvantage is that we lose the sequential IO, but we can always refactor the highlight api to work with multiple documents.
Supports pre_tag, post_tag, number_of_fragments (0 highlights the whole field), require_field_match, no_match_size, order by score and html encoding.
Closes#3704
You can configure the highlighting api to return an excerpt of a field
even if there wasn't a match on the field.
The FVH makes excerpts from the beginning of the string to the first
boundary character after the requested length or the boundary_max_scan,
whichever comes first. The Plain highlighter makes excerpts from the
beginning of the string to the end of the last token before the requested
length.
Closes#1171
The clear scroll api allows clear all resources associated with a `scroll_id` by deleting the `scroll_id` and its associated SearchContext.
Closes#3657
Martijn van Groningen
Michael McCandless
Clinton Gormley
Adrien Grand
Britta Weber
Kurt Hurtado
Luke Fender
Nik Everett
Lee Hinman
Andrew O'Brien
Hannes Korte
bleskes
Randy Stauner
Simon Willnauer
Luca Cavanna
Lars Francke
Conrad Pankoff