本地英文版地址: ../en/search-suggesters.html
Suggestersedit
Suggests similar looking terms based on a provided text by using a suggester. Parts of the suggest feature are still under development.
POST twitter/_search
{
"query" : {
"match": {
"message": "tring out Elasticsearch"
}
},
"suggest" : {
"my-suggestion" : {
"text" : "tring out Elasticsearch",
"term" : {
"field" : "message"
}
}
}
}
Requestedit
The suggest feature suggests similar looking terms based on a provided text by
using a suggester. The suggest request part is defined alongside the query part
in a _search request. If the query part is left out, only suggestions are
returned.
_suggest endpoint has been deprecated in favour of using suggest via
_search endpoint. In 5.0, the _search endpoint has been optimized for
suggest only search requests.
Examplesedit
Several suggestions can be specified per request. Each suggestion is identified
with an arbitrary name. In the example below two suggestions are requested. Both
my-suggest-1 and my-suggest-2 suggestions use the term suggester, but have
a different text.
POST _search
{
"suggest": {
"my-suggest-1" : {
"text" : "tring out Elasticsearch",
"term" : {
"field" : "message"
}
},
"my-suggest-2" : {
"text" : "kmichy",
"term" : {
"field" : "user"
}
}
}
}
The below suggest response example includes the suggestion response for
my-suggest-1 and my-suggest-2. Each suggestion part contains
entries. Each entry is effectively a token from the suggest text and
contains the suggestion entry text, the original start offset and length
in the suggest text and if found an arbitrary number of options.
{
"_shards": ...
"hits": ...
"took": 2,
"timed_out": false,
"suggest": {
"my-suggest-1": [ {
"text": "tring",
"offset": 0,
"length": 5,
"options": [ {"text": "trying", "score": 0.8, "freq": 1 } ]
}, {
"text": "out",
"offset": 6,
"length": 3,
"options": []
}, {
"text": "elasticsearch",
"offset": 10,
"length": 13,
"options": []
} ],
"my-suggest-2": ...
}
}
Each options array contains an option object that includes the suggested text, its document frequency and score compared to the suggest entry text. The meaning of the score depends on the used suggester. The term suggester’s score is based on the edit distance.
Global suggest textedit
To avoid repetition of the suggest text, it is possible to define a
global text. In the example below the suggest text is defined globally
and applies to the my-suggest-1 and my-suggest-2 suggestions.
POST _search
{
"suggest": {
"text" : "tring out Elasticsearch",
"my-suggest-1" : {
"term" : {
"field" : "message"
}
},
"my-suggest-2" : {
"term" : {
"field" : "user"
}
}
}
}
The suggest text can in the above example also be specified as suggestion specific option. The suggest text specified on suggestion level override the suggest text on the global level.
Term suggesteredit
In order to understand the format of suggestions, please read the Suggesters page first.
The term suggester suggests terms based on edit distance. The provided
suggest text is analyzed before terms are suggested. The suggested terms
are provided per analyzed suggest text token. The term suggester
doesn’t take the query into account that is part of request.
Common suggest options:edit
|
|
The suggest text. The suggest text is a required option that needs to be set globally or per suggestion. |
|
|
The field to fetch the candidate suggestions from. This is a required option that either needs to be set globally or per suggestion. |
|
|
The analyzer to analyse the suggest text with. Defaults to the search analyzer of the suggest field. |
|
|
The maximum corrections to be returned per suggest text token. |
|
|
Defines how suggestions should be sorted per suggest text term. Two possible values:
|
|
|
The suggest mode controls what suggestions are included or controls for what suggest text terms, suggestions should be suggested. Three possible values can be specified:
|
Other term suggest options:edit
|
|
The maximum edit distance candidate suggestions can have in order to be considered as a suggestion. Can only be a value between 1 and 2. Any other value results in a bad request error being thrown. Defaults to 2. |
|
|
The number of minimal prefix characters that must match in order be a candidate for suggestions. Defaults to 1. Increasing this number improves spellcheck performance. Usually misspellings don’t occur in the beginning of terms. (Old name "prefix_len" is deprecated) |
|
|
The minimum length a suggest text term must have in order to be included. Defaults to 4. (Old name "min_word_len" is deprecated) |
|
|
Sets the maximum number of suggestions to be retrieved
from each individual shard. During the reduce phase only the top N
suggestions are returned based on the |
|
|
A factor that is used to multiply with the
|
|
|
The minimal threshold in number of documents a suggestion should appear in. This can be specified as an absolute number or as a relative percentage of number of documents. This can improve quality by only suggesting high frequency terms. Defaults to 0f and is not enabled. If a value higher than 1 is specified, then the number cannot be fractional. The shard level document frequencies are used for this option. |
|
|
The maximum threshold in number of documents in which a suggest text token can exist in order to be included. Can be a relative percentage number (e.g., 0.4) or an absolute number to represent document frequencies. If a value higher than 1 is specified, then fractional can not be specified. Defaults to 0.01f. This can be used to exclude high frequency terms — which are usually spelled correctly — from being spellchecked. This also improves the spellcheck performance. The shard level document frequencies are used for this option. |
|
|
Which string distance implementation to use for comparing how similar suggested terms are. Five possible values can be specified:
|
Phrase Suggesteredit
In order to understand the format of suggestions, please read the Suggesters page first.
The term suggester provides a very convenient API to access word
alternatives on a per token basis within a certain string distance. The API
allows accessing each token in the stream individually while
suggest-selection is left to the API consumer. Yet, often pre-selected
suggestions are required in order to present to the end-user. The
phrase suggester adds additional logic on top of the term suggester
to select entire corrected phrases instead of individual tokens weighted
based on ngram-language models. In practice this suggester will be
able to make better decisions about which tokens to pick based on
co-occurrence and frequencies.
API Exampleedit
In general the phrase suggester requires special mapping up front to work.
The phrase suggester examples on this page need the following mapping to
work. The reverse analyzer is used only in the last example.
PUT test
{
"settings": {
"index": {
"number_of_shards": 1,
"analysis": {
"analyzer": {
"trigram": {
"type": "custom",
"tokenizer": "standard",
"filter": ["lowercase","shingle"]
},
"reverse": {
"type": "custom",
"tokenizer": "standard",
"filter": ["lowercase","reverse"]
}
},
"filter": {
"shingle": {
"type": "shingle",
"min_shingle_size": 2,
"max_shingle_size": 3
}
}
}
}
},
"mappings": {
"properties": {
"title": {
"type": "text",
"fields": {
"trigram": {
"type": "text",
"analyzer": "trigram"
},
"reverse": {
"type": "text",
"analyzer": "reverse"
}
}
}
}
}
}
POST test/_doc?refresh=true
{"title": "noble warriors"}
POST test/_doc?refresh=true
{"title": "nobel prize"}
Once you have the analyzers and mappings set up you can use the phrase
suggester in the same spot you’d use the term suggester:
POST test/_search
{
"suggest": {
"text": "noble prize",
"simple_phrase": {
"phrase": {
"field": "title.trigram",
"size": 1,
"gram_size": 3,
"direct_generator": [ {
"field": "title.trigram",
"suggest_mode": "always"
} ],
"highlight": {
"pre_tag": "<em>",
"post_tag": "</em>"
}
}
}
}
}
The response contains suggestions scored by the most likely spelling correction first. In this case we received the expected correction "nobel prize".
{
"_shards": ...
"hits": ...
"timed_out": false,
"took": 3,
"suggest": {
"simple_phrase" : [
{
"text" : "noble prize",
"offset" : 0,
"length" : 11,
"options" : [ {
"text" : "nobel prize",
"highlighted": "<em>nobel</em> prize",
"score" : 0.48614594
}]
}
]
}
}
Basic Phrase suggest API parametersedit
|
|
The name of the field used to do n-gram lookups for the language model, the suggester will use this field to gain statistics to score corrections. This field is mandatory. |
|
|
Sets max size of the n-grams (shingles) in the |
|
|
The likelihood of a term being a
misspelled even if the term exists in the dictionary. The default is
|
|
|
The confidence level defines a factor applied to the
input phrases score which is used as a threshold for other suggest
candidates. Only candidates that score higher than the threshold will be
included in the result. For instance a confidence level of |
|
|
The maximum percentage of the terms
considered to be misspellings in order to form a correction. This method
accepts a float value in the range |
|
|
The separator that is used to separate terms in the bigram field. If not set the whitespace character is used as a separator. |
|
|
The number of candidates that are generated for each
individual query term. Low numbers like |
|
|
Sets the analyzer to analyze to suggest text with.
Defaults to the search analyzer of the suggest field passed via |
|
|
Sets the maximum number of suggested terms to be
retrieved from each individual shard. During the reduce phase, only the
top N suggestions are returned based on the |
|
|
Sets the text / query to provide suggestions for. |
|
|
Sets up suggestion highlighting. If not provided then
no |
|
|
Checks each suggestion against the specified |
POST test/_search
{
"suggest": {
"text" : "noble prize",
"simple_phrase" : {
"phrase" : {
"field" : "title.trigram",
"size" : 1,
"direct_generator" : [ {
"field" : "title.trigram",
"suggest_mode" : "always",
"min_word_length" : 1
} ],
"collate": {
"query": {
"source" : {
"match": {
"{{field_name}}" : "{{suggestion}}"
}
}
},
"params": {"field_name" : "title"},
"prune": true
}
}
}
}
}
|
This query will be run once for every suggestion. |
|
|
The |
|
|
An additional |
|
|
All suggestions will be returned with an extra |
Smoothing Modelsedit
The phrase suggester supports multiple smoothing models to balance
weight between infrequent grams (grams (shingles) are not existing in
the index) and frequent grams (appear at least once in the index). The
smoothing model can be selected by setting the smoothing parameter
to one of the following options. Each smoothing model supports specific
properties that can be configured.
|
|
A simple backoff model that backs off to lower
order n-gram models if the higher order count is |
|
|
A smoothing model that uses an additive smoothing where a
constant (typically |
|
|
A smoothing model that takes the weighted
mean of the unigrams, bigrams, and trigrams based on user supplied
weights (lambdas). Linear Interpolation doesn’t have any default values.
All parameters ( |
POST test/_search
{
"suggest": {
"text" : "obel prize",
"simple_phrase" : {
"phrase" : {
"field" : "title.trigram",
"size" : 1,
"smoothing" : {
"laplace" : {
"alpha" : 0.7
}
}
}
}
}
}
Candidate Generatorsedit
The phrase suggester uses candidate generators to produce a list of
possible terms per term in the given text. A single candidate generator
is similar to a term suggester called for each individual term in the
text. The output of the generators is subsequently scored in combination
with the candidates from the other terms for suggestion candidates.
Currently only one type of candidate generator is supported, the
direct_generator. The Phrase suggest API accepts a list of generators
under the key direct_generator; each of the generators in the list is
called per term in the original text.
Direct Generatorsedit
The direct generators support the following parameters:
|
|
The field to fetch the candidate suggestions from. This is a required option that either needs to be set globally or per suggestion. |
|
|
The maximum corrections to be returned per suggest text token. |
|
|
The suggest mode controls what suggestions are included on the suggestions
generated on each shard. All values other than
|
|
|
The maximum edit distance candidate suggestions can have in order to be considered as a suggestion. Can only be a value between 1 and 2. Any other value results in a bad request error being thrown. Defaults to 2. |
|
|
The number of minimal prefix characters that must match in order be a candidate suggestions. Defaults to 1. Increasing this number improves spellcheck performance. Usually misspellings don’t occur in the beginning of terms. (Old name "prefix_len" is deprecated) |
|
|
The minimum length a suggest text term must have in order to be included. Defaults to 4. (Old name "min_word_len" is deprecated) |
|
|
A factor that is used to multiply with the
|
|
|
The minimal threshold in number of documents a suggestion should appear in. This can be specified as an absolute number or as a relative percentage of number of documents. This can improve quality by only suggesting high frequency terms. Defaults to 0f and is not enabled. If a value higher than 1 is specified, then the number cannot be fractional. The shard level document frequencies are used for this option. |
|
|
The maximum threshold in number of documents in which a suggest text token can exist in order to be included. Can be a relative percentage number (e.g., 0.4) or an absolute number to represent document frequencies. If a value higher than 1 is specified, then fractional can not be specified. Defaults to 0.01f. This can be used to exclude high frequency terms — which are usually spelled correctly — from being spellchecked. This also improves the spellcheck performance. The shard level document frequencies are used for this option. |
|
|
A filter (analyzer) that is applied to each of the tokens passed to this candidate generator. This filter is applied to the original token before candidates are generated. |
|
|
A filter (analyzer) that is applied to each of the generated tokens before they are passed to the actual phrase scorer. |
The following example shows a phrase suggest call with two generators:
the first one is using a field containing ordinary indexed terms, and the
second one uses a field that uses terms indexed with a reverse filter
(tokens are index in reverse order). This is used to overcome the limitation
of the direct generators to require a constant prefix to provide
high-performance suggestions. The pre_filter and post_filter options
accept ordinary analyzer names.
POST test/_search
{
"suggest": {
"text" : "obel prize",
"simple_phrase" : {
"phrase" : {
"field" : "title.trigram",
"size" : 1,
"direct_generator" : [ {
"field" : "title.trigram",
"suggest_mode" : "always"
}, {
"field" : "title.reverse",
"suggest_mode" : "always",
"pre_filter" : "reverse",
"post_filter" : "reverse"
} ]
}
}
}
}
pre_filter and post_filter can also be used to inject synonyms after
candidates are generated. For instance for the query captain usq we
might generate a candidate usa for the term usq, which is a synonym for
america. This allows us to present captain america to the user if this
phrase scores high enough.
Completion Suggesteredit
In order to understand the format of suggestions, please
read the Suggesters page first. For more flexible
search-as-you-type searches that do not use suggesters, see the
search_as_you_type field type.
The completion suggester provides auto-complete/search-as-you-type
functionality. This is a navigational feature to guide users to
relevant results as they are typing, improving search precision.
It is not meant for spell correction or did-you-mean functionality
like the term or phrase suggesters.
Ideally, auto-complete functionality should be as fast as a user
types to provide instant feedback relevant to what a user has already
typed in. Hence, completion suggester is optimized for speed.
The suggester uses data structures that enable fast lookups,
but are costly to build and are stored in-memory.
Mappingedit
To use this feature, specify a special mapping for this field, which indexes the field values for fast completions.
PUT music
{
"mappings": {
"properties" : {
"suggest" : {
"type" : "completion"
},
"title" : {
"type": "keyword"
}
}
}
}
Mapping supports the following parameters:
|
|
The index analyzer to use, defaults to |
|
|
The search analyzer to use, defaults to value of |
|
|
Preserves the separators, defaults to |
|
|
Enables position increments, defaults to |
|
|
Limits the length of a single input, defaults to |
Indexingedit
You index suggestions like any other field. A suggestion is made of an
input and an optional weight attribute. An input is the expected
text to be matched by a suggestion query and the weight determines how
the suggestions will be scored. Indexing a suggestion is as follows:
PUT music/_doc/1?refresh
{
"suggest" : {
"input": [ "Nevermind", "Nirvana" ],
"weight" : 34
}
}
The following parameters are supported:
|
|
The input to store, this can be an array of strings or just a string. This field is mandatory. This value cannot contain the following UTF-16 control characters:
|
|
|
A positive integer or a string containing a positive integer, which defines a weight and allows you to rank your suggestions. This field is optional. |
You can index multiple suggestions for a document as follows:
PUT music/_doc/1?refresh
{
"suggest" : [
{
"input": "Nevermind",
"weight" : 10
},
{
"input": "Nirvana",
"weight" : 3
}
]
}
You can use the following shorthand form. Note that you can not specify a weight with suggestion(s) in the shorthand form.
PUT music/_doc/1?refresh
{
"suggest" : [ "Nevermind", "Nirvana" ]
}
Queryingedit
Suggesting works as usual, except that you have to specify the suggest
type as completion. Suggestions are near real-time, which means
new suggestions can be made visible by refresh and
documents once deleted are never shown. This request:
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"prefix" : "nir",
"completion" : {
"field" : "suggest"
}
}
}
}
|
Prefix used to search for suggestions |
|
|
Type of suggestions |
|
|
Name of the field to search for suggestions in |
returns this response:
{
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits": ...
"took": 2,
"timed_out": false,
"suggest": {
"song-suggest" : [ {
"text" : "nir",
"offset" : 0,
"length" : 3,
"options" : [ {
"text" : "Nirvana",
"_index": "music",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"suggest": ["Nevermind", "Nirvana"]
}
} ]
} ]
}
}
_source meta-field must be enabled, which is the default
behavior, to enable returning _source with suggestions.
The configured weight for a suggestion is returned as _score. The
text field uses the input of your indexed suggestion. Suggestions
return the full document _source by default. The size of the _source
can impact performance due to disk fetch and network transport overhead.
To save some network overhead, filter out unnecessary fields from the _source
using source filtering to minimize
_source size. Note that the _suggest endpoint doesn’t support source
filtering but using suggest on the _search endpoint does:
POST music/_search
{
"_source": "suggest",
"suggest": {
"song-suggest" : {
"prefix" : "nir",
"completion" : {
"field" : "suggest",
"size" : 5
}
}
}
}
|
Filter the source to return only the |
|
|
Name of the field to search for suggestions in |
|
|
Number of suggestions to return |
Which should look like:
{
"took": 6,
"timed_out": false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits": {
"total" : {
"value": 0,
"relation": "eq"
},
"max_score" : null,
"hits" : []
},
"suggest": {
"song-suggest" : [ {
"text" : "nir",
"offset" : 0,
"length" : 3,
"options" : [ {
"text" : "Nirvana",
"_index": "music",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"suggest": ["Nevermind", "Nirvana"]
}
} ]
} ]
}
}
The basic completion suggester query supports the following parameters:
|
|
The name of the field on which to run the query (required). |
|
|
The number of suggestions to return (defaults to |
|
|
Whether duplicate suggestions should be filtered out (defaults to |
The completion suggester considers all documents in the index. See Context Suggester for an explanation of how to query a subset of documents instead.
In case of completion queries spanning more than one shard, the suggest is executed in two phases, where the last phase fetches the relevant documents from shards, implying executing completion requests against a single shard is more performant due to the document fetch overhead when the suggest spans multiple shards. To get best performance for completions, it is recommended to index completions into a single shard index. In case of high heap usage due to shard size, it is still recommended to break index into multiple shards instead of optimizing for completion performance.
Skip duplicate suggestionsedit
Queries can return duplicate suggestions coming from different documents.
It is possible to modify this behavior by setting skip_duplicates to true.
When set, this option filters out documents with duplicate suggestions from the result.
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"prefix" : "nor",
"completion" : {
"field" : "suggest",
"skip_duplicates": true
}
}
}
}
When set to true, this option can slow down search because more suggestions need to be visited to find the top N.
Fuzzy queriesedit
The completion suggester also supports fuzzy queries — this means you can have a typo in your search and still get results back.
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"prefix" : "nor",
"completion" : {
"field" : "suggest",
"fuzzy" : {
"fuzziness" : 2
}
}
}
}
}
Suggestions that share the longest prefix to the query prefix will
be scored higher.
The fuzzy query can take specific fuzzy parameters. The following parameters are supported:
|
|
The fuzziness factor, defaults to |
|
|
if set to |
|
|
Minimum length of the input before fuzzy
suggestions are returned, defaults |
|
|
Minimum length of the input, which is not
checked for fuzzy alternatives, defaults to |
|
|
If |
If you want to stick with the default values, but
still use fuzzy, you can either use fuzzy: {}
or fuzzy: true.
Regex queriesedit
The completion suggester also supports regex queries meaning you can express a prefix as a regular expression
POST music/_search?pretty
{
"suggest": {
"song-suggest" : {
"regex" : "n[ever|i]r",
"completion" : {
"field" : "suggest"
}
}
}
}
The regex query can take specific regex parameters. The following parameters are supported:
|
|
Possible flags are |
|
|
Regular expressions are dangerous because it’s easy to accidentally
create an innocuous looking one that requires an exponential number of
internal determinized automaton states (and corresponding RAM and CPU)
for Lucene to execute. Lucene prevents these using the
|
Context Suggesteredit
The completion suggester considers all documents in the index, but it is often desirable to serve suggestions filtered and/or boosted by some criteria. For example, you want to suggest song titles filtered by certain artists or you want to boost song titles based on their genre.
To achieve suggestion filtering and/or boosting, you can add context mappings while
configuring a completion field. You can define multiple context mappings for a
completion field.
Every context mapping has a unique name and a type. There are two types: category
and geo. Context mappings are configured under the contexts parameter in
the field mapping.
It is mandatory to provide a context when indexing and querying a context enabled completion field.
The following defines types, each with two context mappings for a completion field:
PUT place
{
"mappings": {
"properties" : {
"suggest" : {
"type" : "completion",
"contexts": [
{
"name": "place_type",
"type": "category"
},
{
"name": "location",
"type": "geo",
"precision": 4
}
]
}
}
}
}
PUT place_path_category
{
"mappings": {
"properties" : {
"suggest" : {
"type" : "completion",
"contexts": [
{
"name": "place_type",
"type": "category",
"path": "cat"
},
{
"name": "location",
"type": "geo",
"precision": 4,
"path": "loc"
}
]
},
"loc": {
"type": "geo_point"
}
}
}
}
|
Defines a |
|
|
Defines a |
|
|
Defines a |
|
|
Defines a |
Adding context mappings increases the index size for completion field. The completion index is entirely heap resident, you can monitor the completion field index size using Index stats.
Category Contextedit
The category context allows you to associate one or more categories with suggestions at index
time. At query time, suggestions can be filtered and boosted by their associated categories.
The mappings are set up like the place_type fields above. If path is defined
then the categories are read from that path in the document, otherwise they must
be sent in the suggest field like this:
PUT place/_doc/1
{
"suggest": {
"input": ["timmy's", "starbucks", "dunkin donuts"],
"contexts": {
"place_type": ["cafe", "food"]
}
}
}
If the mapping had a path then the following index request would be enough to
add the categories:
PUT place_path_category/_doc/1
{
"suggest": ["timmy's", "starbucks", "dunkin donuts"],
"cat": ["cafe", "food"]
}
If context mapping references another field and the categories are explicitly indexed, the suggestions are indexed with both set of categories.
Category Queryedit
Suggestions can be filtered by one or more categories. The following filters suggestions by multiple categories:
POST place/_search?pretty
{
"suggest": {
"place_suggestion" : {
"prefix" : "tim",
"completion" : {
"field" : "suggest",
"size": 10,
"contexts": {
"place_type": [ "cafe", "restaurants" ]
}
}
}
}
}
If multiple categories or category contexts are set on the query they are merged as a disjunction. This means that suggestions match if they contain at least one of the provided context values.
Suggestions with certain categories can be boosted higher than others. The following filters suggestions by categories and additionally boosts suggestions associated with some categories:
POST place/_search?pretty
{
"suggest": {
"place_suggestion" : {
"prefix" : "tim",
"completion" : {
"field" : "suggest",
"size": 10,
"contexts": {
"place_type": [
{ "context" : "cafe" },
{ "context" : "restaurants", "boost": 2 }
]
}
}
}
}
}
|
The context query filter suggestions associated with
categories cafe and restaurants and boosts the
suggestions associated with restaurants by a
factor of |
In addition to accepting category values, a context query can be composed of
multiple category context clauses. The following parameters are supported for a
category context clause:
|
|
The value of the category to filter/boost on. This is mandatory. |
|
|
The factor by which the score of the suggestion
should be boosted, the score is computed by
multiplying the boost with the suggestion weight,
defaults to |
|
|
Whether the category value should be treated as a
prefix or not. For example, if set to |
If a suggestion entry matches multiple contexts the final score is computed as the maximum score produced by any matching contexts.
Geo location Contextedit
A geo context allows you to associate one or more geo points or geohashes with suggestions
at index time. At query time, suggestions can be filtered and boosted if they are within
a certain distance of a specified geo location.
Internally, geo points are encoded as geohashes with the specified precision.
Geo Mappingedit
In addition to the path setting, geo context mapping accepts the following settings:
|
|
This defines the precision of the geohash to be indexed and can be specified
as a distance value ( |
The index time precision setting sets the maximum geohash precision that
can be used at query time.
Indexing geo contextsedit
geo contexts can be explicitly set with suggestions or be indexed from a geo point field in the
document via the path parameter, similar to category contexts. Associating multiple geo location context
with a suggestion, will index the suggestion for every geo location. The following indexes a suggestion
with two geo location contexts:
PUT place/_doc/1
{
"suggest": {
"input": "timmy's",
"contexts": {
"location": [
{
"lat": 43.6624803,
"lon": -79.3863353
},
{
"lat": 43.6624718,
"lon": -79.3873227
}
]
}
}
}
Geo location Queryedit
Suggestions can be filtered and boosted with respect to how close they are to one or more geo points. The following filters suggestions that fall within the area represented by the encoded geohash of a geo point:
POST place/_search
{
"suggest": {
"place_suggestion" : {
"prefix" : "tim",
"completion" : {
"field" : "suggest",
"size": 10,
"contexts": {
"location": {
"lat": 43.662,
"lon": -79.380
}
}
}
}
}
}
When a location with a lower precision at query time is specified, all suggestions that fall within the area will be considered.
If multiple categories or category contexts are set on the query they are merged as a disjunction. This means that suggestions match if they contain at least one of the provided context values.
Suggestions that are within an area represented by a geohash can also be boosted higher than others, as shown by the following:
POST place/_search?pretty
{
"suggest": {
"place_suggestion" : {
"prefix" : "tim",
"completion" : {
"field" : "suggest",
"size": 10,
"contexts": {
"location": [
{
"lat": 43.6624803,
"lon": -79.3863353,
"precision": 2
},
{
"context": {
"lat": 43.6624803,
"lon": -79.3863353
},
"boost": 2
}
]
}
}
}
}
}
|
The context query filters for suggestions that fall under
the geo location represented by a geohash of (43.662, -79.380)
with a precision of 2 and boosts suggestions
that fall under the geohash representation of (43.6624803, -79.3863353)
with a default precision of 6 by a factor of |
If a suggestion entry matches multiple contexts the final score is computed as the maximum score produced by any matching contexts.
In addition to accepting context values, a context query can be composed of
multiple context clauses. The following parameters are supported for a
category context clause:
|
|
A geo point object or a geo hash string to filter or boost the suggestion by. This is mandatory. |
|
|
The factor by which the score of the suggestion
should be boosted, the score is computed by
multiplying the boost with the suggestion weight,
defaults to |
|
|
The precision of the geohash to encode the query geo point.
This can be specified as a distance value ( |
|
|
Accepts an array of precision values at which
neighbouring geohashes should be taken into account.
precision value can be a distance value ( |
Returning the type of the suggesteredit
Sometimes you need to know the exact type of a suggester in order to parse its results. The typed_keys parameter
can be used to change the suggester’s name in the response so that it will be prefixed by its type.
Considering the following example with two suggesters term and phrase:
POST _search?typed_keys
{
"suggest": {
"text" : "some test mssage",
"my-first-suggester" : {
"term" : {
"field" : "message"
}
},
"my-second-suggester" : {
"phrase" : {
"field" : "message"
}
}
}
}
In the response, the suggester names will be changed to respectively term#my-first-suggester and
phrase#my-second-suggester, reflecting the types of each suggestion:
{
"suggest": {
"term#my-first-suggester": [
{
"text": "some",
"offset": 0,
"length": 4,
"options": []
},
{
"text": "test",
"offset": 5,
"length": 4,
"options": []
},
{
"text": "mssage",
"offset": 10,
"length": 6,
"options": [
{
"text": "message",
"score": 0.8333333,
"freq": 4
}
]
}
],
"phrase#my-second-suggester": [
{
"text": "some test mssage",
"offset": 0,
"length": 16,
"options": [
{
"text": "some test message",
"score": 0.030227963
}
]
}
]
},
...
}