I have the following query:
{
size: 6,
query: {
multi_match: {
query,
type: 'bool_prefix',
fields: ['recommendation', 'recommendation._2gram', 'recommendation._3gram'],
},
},
highlight: {
fields: {
recommendation: {},
},
},
}
I want to add fuzziness: 1 to this query, but it has issues with the type: 'bool_prefix'. I need the type: 'bool_prefix to remain there b/c its integral to how the query works, but I'd also like to add some fuzziness to it. Any ideas?
As mentioned in the official ES documentation of bool_prefix
The fuzziness, prefix_length, max_expansions, fuzzy_rewrite, and
fuzzy_transpositions parameters are supported for the terms that are
used to construct term queries, but do not have an effect on the
prefix query constructed from the final term.
Adding a working example with index mapping, data, search query, and search result
Index Mapping:
{
"mappings": {
"properties": {
"recommendation": {
"type": "search_as_you_type",
"max_shingle_size": 3
}
}
}
}
Index Data:
{
"recommendation":"good things"
}
{
"recommendation":"good"
}
Search Query:
You can add fuzziness parameter with bool_prefix, as shown below
{
"size": 6,
"query": {
"multi_match": {
"query": "goof q",
"type": "bool_prefix",
"fields": [
"recommendation",
"recommendation._2gram",
"recommendation._3gram"
],
"fuzziness": 1
}
},
"highlight": {
"fields": {
"recommendation": {}
}
}
}
Search Result:
"hits": [
{
"_index": "65817192",
"_type": "_doc",
"_id": "2",
"_score": 1.1203322,
"_source": {
"recommendation": "good things"
},
"highlight": {
"recommendation": [
"<em>good</em> things"
]
}
},
{
"_index": "65817192",
"_type": "_doc",
"_id": "1",
"_score": 0.1583319,
"_source": {
"recommendation": "good"
},
"highlight": {
"recommendation": [
"<em>good</em>"
]
}
}
]
I ended up with additional fuzzy query combined with multi_match by bool. In your case it would look like this:
{
"size": 6,
"query": {
"bool": {
"should": [
{
"multi_match": {
"query": "goof q",
"type": "bool_prefix",
"fields": [
"recommendation",
"recommendation._2gram",
"recommendation._3gram"
]
}
},
{
"fuzzy": {
"nameSearch": {
"value": "goof q",
"fuzziness": "AUTO"
}
}
}
]
}
},
"highlight": {
"fields": {
"recommendation": {}
}
}
}
Related
I'm looking for a way to fuzzy partial match against a field where the words match, however I want to also add in strict phrase matching.
i.e. say I have fields such as
foo bar
bar foo
I would like to achieve the following search behaviour:
If I search foo, I would like to return back both results.
If I search ba, I would like to return back both results.
If I search bar foo, I would like to only return back one result.
If I search bar foo foo, I don't want to return any results.
I would also like to add in single character fuzziness matching, so if a foo is mistyped as fbo then it would return back both results.
My current search and index analyzer uses an edge_gram tokenizer and is working fairly well, except if any gram matches, it will return the results regardless if the following words match. i.e. my search would return the back the following result for the search bar foo buzz
foo bar
bar foo
My tokenzier:
ngram_tokenizer: {
type: "edge_ngram",
min_gram: "2",
max_gram: "15",
token_chars: ['letter', 'digit', 'punctuation', 'symbol'],
},
My analyzer:
nGram_analyzer: {
filter: [
lowercase,
"asciifolding"
],
type: "custom",
tokenizer: "ngram_tokenizer"
},
My field mapping:
type: "search_as_you_type",
doc_values: false,
max_shingle_size: 3,
analyzer: "nGram_analyzer"
One way to achieve all your requirements is to use span_near query
Span near query are much longer, but these are suitable for doing phrase match along with fuzziness parameter
Adding a working example with index data, search queries and search results
Index Mapping:
{
"mappings": {
"properties": {
"title": {
"type": "text"
}
}
}
}
Index Data:
{
"title":"bar foo"
}
{
"title":"foo bar"
}
Search Queries:
If I search foo, I would like to return back both results.
{
"query": {
"bool": {
"must": [
{
"span_near": {
"clauses": [
{
"span_multi": {
"match": {
"fuzzy": {
"title": {
"value": "foo",
"fuzziness": 2
}
}
}
}
}
],
"slop": 0,
"in_order": true
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "67205552",
"_type": "_doc",
"_id": "2",
"_score": 0.18232156,
"_source": {
"title": "bar foo"
}
},
{
"_index": "67205552",
"_type": "_doc",
"_id": "1",
"_score": 0.18232156,
"_source": {
"title": "foo bar"
}
}
]
If I search ba, I would like to return back both results.
{
"query": {
"bool": {
"must": [
{
"span_near": {
"clauses": [
{
"span_multi": {
"match": {
"fuzzy": {
"title": {
"value": "ba",
"fuzziness": 2
}
}
}
}
}
],
"slop": 0,
"in_order": true
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "67205552",
"_type": "_doc",
"_id": "2",
"_score": 0.18232156,
"_source": {
"title": "bar foo"
}
},
{
"_index": "67205552",
"_type": "_doc",
"_id": "1",
"_score": 0.18232156,
"_source": {
"title": "foo bar"
}
}
]
If I search bar foo foo, I don't want to return any results.
{
"query": {
"bool": {
"must": [
{
"span_near": {
"clauses": [
{
"span_multi": {
"match": {
"fuzzy": {
"title": {
"value": "bar",
"fuzziness": 2
}
}
}
}
},
{
"span_multi": {
"match": {
"fuzzy": {
"title": {
"value": "foo",
"fuzziness": 2
}
}
}
}
},
{
"span_multi": {
"match": {
"fuzzy": {
"title": {
"value": "foo",
"fuzziness": 2
}
}
}
}
}
],
"slop": 0,
"in_order": true
}
}
]
}
}
}
Search Result will be empty
I got fields like that:
names: ["Red:123", "Blue:45", "Green:56"]
it's mapping is
"names": {
"type": "keyword"
},
how could I search like this
{
"query": {
"match": {
"names": "red"
}
}
}
to get all the documents where red is in element of names array?
Now it works only with
{
"query": {
"match": {
"names": "red:123"
}
}
}
You can add multi fields OR just change the type to text, to achieve your required result
Index Mapping using multi fields
{
"mappings": {
"properties": {
"names": {
"type": "text",
"fields": {
"raw": {
"type": "keyword"
}
}
}
}
}
}
Adding a working example with index data, mapping, search query, and search result
Index Mapping:
{
"mappings":{
"properties":{
"names":{
"type":"text"
}
}
}
}
Index Data:
{
"names": [
"Red:123",
"Blue:45",
"Green:56"
]
}
Search Query:
{
"query": {
"match": {
"names": "red"
}
}
}
Search Result:
"hits": [
{
"_index": "64665127",
"_type": "_doc",
"_id": "1",
"_score": 0.2876821,
"_source": {
"names": [
"Red:123",
"Blue:45",
"Green:56"
]
}
}
]
I have this ElasticSearch query for ES version 7:
{
"from": 0,
"simple_query_string": {
"query": "*"
},
"query": {
"bool": {
"must": [
{
"term": {
"organization_id": "fred"
}
},
{
"term": {
"assigned_user_id": "24584080"
}
}
]
}
},
"size": 50,
"sort": {
"updated": "desc"
},
"terminate_after": 50,
}
but ES gives me back this error:
reason: Unknown key for a START_OBJECT in [simple_query_string]
my goal is to be able to use a query-string for multiple fields, and also use term/match with bool/must. Should I abandon the query string and just use bool.must[{match:"my query"}]?
You can use bool to combine multiple queries in this way. The must clause will work as logical AND, and will make sure all the conditions are matched.
You need to include the simple_query_string inside the query section
Adding Working example with sample docs, and search query.
Index Sample Data
{
"organization_id": 1,
"assigned_user_id": 2,
"title": "welcome"
}{
"organization_id": 2,
"assigned_user_id": 21,
"title": "hello"
}{
"organization_id": 3,
"assigned_user_id": 22,
"title": "hello welocome"
}
Search Query :
{
"query": {
"bool": {
"must": [
{
"simple_query_string": {
"fields" : ["title"],
"query" : "welcome"
}
},
{
"match": {
"organization_id": "1"
}
},
{
"match": {
"assigned_user_id": "2"
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_score": 3.0925694,
"_source": {
"organization_id": 1,
"assigned_user_id": 2,
"title": "welcome"
}
}
]
I have structure like this in my ElasticSearch
{
_index: 'index',
_type: 'product',
_id: '896',
_score: 0,
_source: {
entity_id: '896',
category: [
{
category_id: 2,
is_virtual: 'false'
},
{
category_id: 82,
is_virtual: 'false'
}
]
}
}
I want return all "producs" that have "82" category_id.
{
"query": {
"bool": {
"filter": {
"terms": {
"category.category_id": [
82
]
}
}
}
}
}
This query gives me 0 hits.
What is right way to do this?
Adding working example, you need to define the category as nested field and modify your search query by including the nested path
Index Mapping
{
"mappings": {
"properties": {
"entity_id": {
"type": "text"
},
"category": {
"type": "nested"
}
}
}
}
Index your document
{
"entity_id": "896",
"category": [
{
"category_id": 2,
"is_virtual": false
},
{
"category_id": 82,
"is_virtual": false
}
]
}
Proper search query, note we are using nested query which doesn't support normal filter(so your query gives error)
{
"query": {
"nested": {
"path": "category",
"query": {
"bool": {
"must": [
{
"match": {
"category.category_id": 82
}
}
]
}
}
}
}
}
Search result retuns indexed doc
"hits": [
{
"_index": "complexnested",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"entity_id": "896",
"category": [
{
"category_id": 2,
"is_virtual": false
},
{
"category_id": 82,
"is_virtual": false
}
]
}
}
]
If your query gives you no results, I suspect that category is of type nested in your index mapping. If that's the case, that's good and you can modify your query like this to use the nested query:
{
"query": {
"bool": {
"filter": {
"nested": {
"path": "category",
"query": {
"terms": {
"category.category_id": [
82
]
}
}
}
}
}
}
}
I have different types indexed in elastic search.
but, if I want to boost my results on some selected types then what should I do?
I could use type filter in boosting query, but type filter allows me only one type to be used in filter. I need results to be boosted on the basis of multiple types.
Example:
I have Person, Event, Location data indexed in elastic search where Person, Location and Event are my types.
I am searching for keyword 'London' in all types but i want Person and Event type records to be boosted than Location.
How could I achieve the same?
One of the ways of getting the desired functionality is by wrapping your query inside a bool query and then make use of the should clause, in order to boost certain documents
Small example:
POST test/person
{
"title": "london elise moore"
}
POST test/event
{
"title" : "london is a great city"
}
Without boost:
GET test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "london"
}
}
]
}
}
}
With the following response:
"hits": {
"total": 2,
"max_score": 0.2972674,
"hits": [
{
"_index": "test",
"_type": "person",
"_id": "AVVx621GYvUb9aQn6r5X",
"_score": 0.2972674,
"_source": {
"title": "london elise moore"
}
},
{
"_index": "test",
"_type": "event",
"_id": "AVVx63LrYvUb9aQn6r5Y",
"_score": 0.26010898,
"_source": {
"title": "london is a great city"
}
}
]
}
And now with the added should clause:
GET test/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": "london"
}
}
],
"should": [
{
"term": {
"_type": {
"value": "event",
"boost": 2
}
}
}
]
}
}
}
Which gives back the following response:
"hits": {
"total": 2,
"max_score": 1.0326607,
"hits": [
{
"_index": "test",
"_type": "event",
"_id": "AVVx63LrYvUb9aQn6r5Y",
"_score": 1.0326607,
"_source": {
"title": "london is a great city"
}
},
{
"_index": "test",
"_type": "person",
"_id": "AVVx621GYvUb9aQn6r5X",
"_score": 0.04235228,
"_source": {
"title": "london elise moore"
}
}
]
}
You could even leave out the extra boost in the should clause, cause if the should clause matches it will boost the result :)
Hope this helps!
I see two ways of doing that using that but both is using scripts
1. using sorting
POST c1_1/_search
{
"from": 0,
"size": 10,
"sort": [
{
"_script": {
"order": "desc",
"type": "number",
"script": "double boost = 1; if(doc['_type'].value == 'Person') { boost *= 2 }; if(doc['_type'].value == 'Event') { boost *= 3}; return _score * boost; ",
"params": {}
}
},
{
"_score": {}
}
],
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "*",
"default_operator": "and"
}
}
],
"minimum_should_match": "1"
}
}
}
Second option Using function score.
POST c1_1/_search
{
"from": 0,
"size": 10,
"query": {
"function_score": {
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "*",
"default_operator": "and"
}
}
],
"minimum_should_match": "1"
}
},
"script_score": {
"script": "_score * (doc['_type'].value == 'Person' || doc['_type'].value == 'Event'? 2 : 1)"
}
}
}
}