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"
}
}
]
Related
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": {}
}
}
}
I have a index in elastic search called professor
If for cross field i need "AND" condition
for same field array i need to OR condition
I need to search subject which is Physics or Accounting this is array of fields(OR) statement
I need to search type is Permanent(&) condition
I need to search Location is NY(&) condition
There is chance that {'type':['Contract','Guest']} type also coming as list
test = [{'id':1,'name': 'A','subject': ['Maths','Accounting'],'type':'Contract', 'Location':'NY'},
{ 'id':2,'name': 'AB','subject': ['Physics','Engineering'],'type':'Permanent','Location':'NY'},
{'id':3,'name': 'ABC','subject': ['Maths','Engineering'],'type':'Permanent','Location':'NY'}]
Query is below,3rd one got it, How to add 1 and 2
content_search = es.search(index="professor", body={
"query": {
"bool": {
"must": {
"match_all": {}
},
"filter": [
{
"term": {
"Location.keyword": "NY"
}
}
]
}
}
})
content_search ['hits']['hits']
Expected out is id [{ 'id':2,'name': 'AB','subject': ['Physics','Engineering'],'type':'Permanent','Location':'NY'}]
You need to use the bool query, to wrap all your conditions
Adding a working example with index data(same as that in question), search query, and search result
Search Query:
{
"query": {
"bool": {
"must": [
{
"match": {
"type.keyword": "Permanent"
}
},
{
"match": {
"Location.keyword": "NY"
}
}
],
"should": [
{
"match": {
"subject.keyword": "Accounting"
}
},
{
"match": {
"subject.keyword": "Physics"
}
}
],
"minimum_should_match": 1,
"boost": 1.0
}
}
}
Search Result:
"hits": [
{
"_index": "stof_64370980",
"_type": "_doc",
"_id": "2",
"_score": 1.8365774,
"_source": {
"id": 2,
"name": "AB",
"subject": [
"Physics",
"Engineering"
],
"type": "Permanent",
"Location": "NY"
}
}
]
Query is below
{
"from" : 0,
"size" : 100,
"query": {
"match_all": {}
}
}
I need to filter from the match_all if name is test
i tried with
{
"from" : 0,
"size" : 100,
"query": {
"match_all": {}
},
"filter": [ "term": { "name": "test" }}]
}
I got error 'Unknown key for a START_ARRAY in [filter].')
You will need to wrap your query in a bool query , try out this search query:
{
"from":0,
"size":10,
"query": {
"bool": {
"must": {
"match_all": {}
},
"filter": [
{
"term": {
"grocery_name": "elastic"
}
}
]
}
}
}
Update 1:
According to the comment mentioned by #Nons
Search Query:
Terms query return documents that contain an exact term in a provided
field.
{
"from":0,
"size":10,
"query": {
"bool": {
"must": {
"match_all": {}
},
"filter": [
{
"term": {
"parentName.keyword": "Developer" <-- note this
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "stof_64275684",
"_type": "_doc",
"_id": "1",
"_score": 1.0,
"_source": {
"id": "1",
"name": "A",
"parentName": "Developer",
"Data": [
{
"id": "455",
"name": "Google",
"lastUpdatedDate": "2020-09-10",
"parent_id": "1"
}
],
"Function": [
{
"id": "1",
"name": "Major"
}
]
}
}
]
You can even use a match query where the provided text is analyzed
before matching.
{
"from": 0,
"size": 10,
"query": {
"bool": {
"must": {
"match": {
"parentName": "developer"
}
}
}
}
}
I would recommend to use the Chrome ElasticSearch Head plugin. It allows to test and run searches against Elastic very easily (functionality is similar to MySql Workbech).
Please find example of usage of plugin below (combination of condition and aggregation).
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)"
}
}
}
}