I have a following document:
{
"_index": "testrest",
"_type": "testrest",
"_id": "sadfasdfw1",
"_score": 1,
"_source": {,
"s_item_name": "Create",
"request_id": "35",
"Result": "Match",
}
},
I am trying to get records with term value Match in Result field and request_id of 35.
Here's my query:
{
"query": {
"bool": {
"must": [
{ "term": { "Result": "Match" }}
],
"filter": {
"term": {
"request_id": "35"
}
}
}
}
}
But I am getting 0 results.
Replacing term with match gives me results though.
This is because Result is a text field, and thus, it is analyzed and the value is indexed as match instead of Match.
In general, you should not use a term query, but prefer a match query instead. In your case, that would solve the issue.
If you absolutely want to use a term query and have a field called Result.keyword, then you can also do that.
So to recap:
{
"query": {
"bool": {
"must": [
{ "match": { "Result": "Match" }} <-- use match query
],
"filter": {
"term": {
"request_id": "35"
}
}
}
}
}
or
{
"query": {
"bool": {
"must": [
{ "term": { "Result.keyword": "Match" }} <-- use term query on keyword field
],
"filter": {
"term": {
"request_id": "35"
}
}
}
}
}
Related
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
AND
I need to search type is Permanent or GUEST condition this is array of fields(OR) statement
AND
I need to search Location is NY(&) condition
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'},
{'id':4,'name':'ABCD','subject': ['Physics','Engineering'],'type':['Contract','Guest'],'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'},{'id':4,'name':'ABCD','subject': ['Physics','Engineering'],'type':['Contract','Guest'],'Location':'NY'}]
The filter clause (query) must appear in matching documents. However
unlike must the score of the query will be ignored. Filter clauses are
executed in filter context, meaning that scoring is ignored and
clauses are considered for caching.
Please go through this Elasticsearch documentation on bool queries, to get a detailed understanding about it.
Adding a working example with index data(same as that in question), search query, and search result
Search Query:
{
"query": {
"bool": {
"must": {
"match": {
"Location.keyword": "NY"
}
},
"filter": [
{
"bool": {
"should": [
{
"match": {
"subject.keyword": "Accounting"
}
},
{
"match": {
"subject.keyword": "Physics"
}
}
]
}
},
{
"bool": {
"should": [
{
"match": {
"type.keyword": "Permanent"
}
},
{
"match": {
"type.keyword": "Guest"
}
}
]
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "stof_64370980",
"_type": "_doc",
"_id": "2",
"_score": 0.10536051,
"_source": {
"id": 2,
"name": "AB",
"subject": [
"Physics",
"Engineering"
],
"type": "Permanent",
"Location": "NY"
}
},
{
"_index": "stof_64370980",
"_type": "_doc",
"_id": "4",
"_score": 0.10536051,
"_source": {
"id": 4,
"name": "ABCD",
"subject": [
"Physics",
"Engineering"
],
"type": [
"Contract",
"Guest"
],
"Location": "NY"
}
}
]
Another Search Query:
You can even use terms query that returns documents that contain
one or more exact terms in a provided field.The terms query is the
same as the term query, except you can search for multiple values.
{
"query": {
"bool": {
"must": [
{
"terms": {
"subject.keyword": [
"Physics",
"Accounting"
]
}
},
{
"terms": {
"type.keyword": [
"Guest",
"Permanent"
]
}
},
{
"match": {
"Location.keyword": "NY"
}
}
]
}
}
}
Update 1:
{
"query": {
"bool": {
"must": [
{
"terms": {
"subject.keyword": [
"Physics",
"Accounting"
]
}
},
{
"terms": {
"type.keyword": [
"Guest",
"Permanent"
]
}
},
{
"match": {
"Location.keyword": "NY"
}
},
{
"query_string": {
"query": "ABCD"
}
}
]
}
}
}
I've got two different queries against my elasticsearch. The difference between these two queries is that the first one got the two search criteria in one boolean should query and he second splits it into two single bool should queries. The first one return the expected response but the second one doesnt match to any document even if there are documents which contains both criteria. If i refactor the second one so that the two splitted bool should queries are encapsulatec by a bool should querie it returns the expected response like it is for querie 1.
The question is why does query 2 doesn't return the response as 1 and 3 do? Am i missing something?
EDIT: provided example data
EDIT: my problem solved, it was just a spelling mistake while building the range query in my code and i doesnt recognize it -.- but maybe the explanation from the answer here will help somebody else.
1.
GET _search
{
"query": {
"bool": {
"filter": [
{
"bool": {
"should": [
{
"range": {
"streetNr": {
"from": "1",
"to": "100",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
},
{
"match": {
"geographicAddress.city": {
"query": "Berlin"
}
}
}
],
"minimum_should_match": "1"
}
}
]
}
}
}
GET _search
{
"query": {
"bool": {
"filter": [
{
"bool": {
"should": [
{
"range": {
"streetNr": {
"from": "1",
"to": "100",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
}
],
"minimum_should_match": "1"
}
},
{
"bool": {
"should": [
{
"match": {
"geographicAddress.city": {
"query": "Berlin"
}
}
}
],
"minimum_should_match": "1"
}
}
]
}
}
}
GET _search
{
"query": {
"bool": {
"filter": [
{
"bool": {
"should": [
{
"bool": {
"should": [
{
"range": {
"streetNr": {
"from": "1",
"to": "100",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
}
],
"minimum_should_match": "1"
}
},
{
"bool": {
"should": [
{
"match": {
"geographicAddress.city": {
"query": "Berlin"
}
}
}
],
"minimum_should_match": "1"
}
}
],
"minimum_should_match": "1"
}
}
]
}
}
}
Example data:
{
"_index": "stof_64371064",
"_type": "_doc",
"_id": "1",
"_score": 0.0,
"_source": {
"streetNr": 90,
"geographicAddress": {
"city": "Berlin"
}
}
},
{
"_index": "stof_64371064",
"_type": "_doc",
"_id": "2",
"_score": 0.0,
"_source": {
"streetNr": 10,
"geographicAddress": {
"city": "Berlin"
}
}
}
Please refer ES official documentation on bool query, to get a detailed understanding of various clauses.
The structure of your first search query is like -
{
"query": {
"bool": {
"filter": [
{
"bool": {
"should": [
{},
{}
],
"minimum_should_match": 1
}
}
]
}
}
}
filter clause is wrapping should query, but at the end of should clause, "minimum_should_match": 1 is added which indicates that 1 should clause must be mandatory.
The structure of your second search query is like -
{
"query": {
"bool": {
"filter": [
{
"bool": {
"should": {},
"minimum_should_match": "1"
}
},
{
"bool": {
"should": {},
"minimum_should_match": "1"
}
}
]
}
}
}
Here since you have added "minimum_should_match": "1" after every should clause, then in a way, it acts like a must clause only, as there is only one condition that needs to be matched in the should clause. filter clause is applied enclosing both the bool should clause, so when both the should clause match, then only you will get the result.
The structure of your third search query is like -
{
"query": {
"bool": {
"filter": [
{
"bool": {
"should": [
{
"bool": {
"should": [
{}
],
"minimum_should_match": 1
}
},
{
"bool": {
"should": [
{}
],
"minimum_should_match": 1
}
}
],
"minimum_should_match": 1
}
}
]
}
}
}
In this, you have used multiple combinations of the bool should clause. The first outer bool should clause, wraps two more bool should clause. But here at the end of the outer should clause you have added "minimum_should_match": 1. So though here filter clause is there but it will return a result even if one bool should clause satisfy the condition.
Adding a working example with index data, search query, and search result
Index Data:
{
"streetNr":0,
"geographicAddress":{
"city":"Berlin"
}
}
{
"streetNr":90,
"geographicAddress":{
"city":"Berlin"
}
}
Search Query: (Second search query acc to your question)
{
"query": {
"bool": {
"should": [ <-- note this
{
"bool": {
"should": [
{
"range": {
"streetNr": {
"from": "1",
"to": "100",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
}
],
"minimum_should_match": "1"
}
},
{
"bool": {
"should": [
{
"match": {
"geographicAddress.city": {
"query": "Berlin"
}
}
}
],
"minimum_should_match": "1"
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "stof_64371064",
"_type": "_doc",
"_id": "1",
"_score": 0.0,
"_source": {
"streetNr": 90,
"geographicAddress": {
"city": "Berlin"
}
}
},
{
"_index": "stof_64371064",
"_type": "_doc",
"_id": "2",
"_score": 0.0,
"_source": {
"streetNr": 0,
"geographicAddress": {
"city": "Berlin"
}
}
}
]
In the should with minimum should match=1 you say that if one of the criteria is right return the document as you have set in query 1 and 3 . But in the second query you have set two criteria inside filter and elasticsearch search and returns those documents which both criterias are valid on them. Because of that your second query behaves such as a must in comparison with should in your other queries.
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).
The documents are stored in the form below in Elastic Research index.
mapping
{
"mappings": {
"properties": {
"data": {
"type": "nested"
}
}
}
}
first docs
{
"data": [
{
"value": "a"
},
{
"value": "a"
},
{
"value": "b"
}
]
}
second docs
{
"data": [
{
"value": "a"
},
{
"value": "a"
},
{
"value": "a"
}
]
}
I want to return the document only when all values in the array are 'a' (second docs)
In this case, how should I make the query condition?
The nested query searches nested field objects as if they were indexed
as separate documents. If an object matches the search, the nested
query returns the root parent document.
When using a combination of bool query with must and must_not, it searches for each individual nested object and eliminates the objects that do not match, but if there are some nested objects left, that match with your query, you will get your results.
Try out this below search query, where all the documents are discarded who have a nested object with the b value.
Search Query:
{
"query": {
"bool": {
"must_not": {
"nested": {
"path": "data",
"query": {
"term": {
"data.value": "b"
}
}
}
}
}
}
}
Search Result:
"hits": [
{
"_index": "stof_64329782",
"_type": "_doc",
"_id": "2",
"_score": 0.0,
"_source": {
"data": [
{
"value": "a"
},
{
"value": "a"
},
{
"value": "a"
}
]
}
}
]
Search Query with the combination of multiple bool and nested queries:
The below search query will also give you the required result.
{
"query": {
"bool": {
"must": [
{
"nested": {
"path": "data",
"query": {
"bool": {
"must": [
{
"match": {
"data.value": "a"
}
}
]
}
}
}
}
],
"must_not": [
{
"nested": {
"path": "data",
"query": {
"bool": {
"must": [
{
"match": {
"data.value": "b"
}
}
]
}
}
}
}
]
}
}
}