I have three fields status,type and search. What I want is to search the data which contains status equals to NEW or status equals to IN PROGRESS and type is equal to abc or type equals to xyz and search contains( partial match ).
My call looks like below -
{
"query": {
"bool" : {
"must" : [{
"match": {
"status": {
"query": "abc",
}
}
}, {
"match": {
"type": {
"query": "NEW",
}
}
},{
"query_string": {
"query": "*abc*", /* for partial search */
"fields": ["title", "name"]
}
}]
}
}
}
Nest your boolqueries. I think what you are missing is this:
"bool": { "should": [
{ "match": { "status": "abc" } },
{ "match": { "status": "xyz" } }
]}
This is a query which MUST match one of the should clauses as only should clauses are given.
EDIT to explain the differences:
{
"query": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"match": {
"status": "abc"
}
},
{
"match": {
"status": "xyz"
}
}
]
}
},
{
"terms": {
"type": [
"NEW",
"IN_PROGRESS"
]
}
},
{
"query_string": {
"query": "*abc*",
"fields": [
"title",
"name"
]
}
}
]
}
}
}
So you have a boolquery at top. Every of the 3 inner queries must be true.
The first is a nested boolquery which is true if status matches either abc or xyz.
The second is true if type matches exactly NEW or IN_PROGRESS - Note the difference here. The First one would also match ABC or aBc or potentially "abc XYZ" depending on your analyzer. You might want terms for both.
The third is what you had before.
Related
I have the data of this type in elastic search
{
"name":"John Doe",
"age":"31",
"state":"PA"
},
{
"name":"John Doe",
"age":"30",
"state":"VA"
},
{
"name":"John Doe",
"age":"30",
"state":"AZ"
}
I wanted to find all John Doe's in the states of AZ and CA.
i have the below query
{
"query": {
"bool": {
"must": [
{
"term": {
"name": "John Doe"
}
},
{
"terms": {
"state":["AZ,"CA"]
}
}
]
}
}
}
this is showing me scoring in the results returned , also anyway to disable scoring by using filter and term condition like this
```
{
"query": {
"bool": {
"filter": [
{
"term": {
"name": "John Doe"
}
}
]
}
}
}```
How do I query for the documents in elasticsearch with filter and array as in above
filter and must clauses both work as a logical AND operator. The only difference is that in the filter clause the scoring is ignored, whereas in the must clause the matched documents contribute to the scoring.
You can either wrap your bool must query inside the filter clause, as shown below
{
"query": {
"bool": {
"filter": {
"bool": {
"must": [
{
"term": {
"name.keyword": "John Doe"
}
},
{
"terms": {
"state.keyword": [
"AZ",
"CA"
]
}
}
]
}
}
}
}
}
Or you can replace the must clause with the filter clause
{
"query": {
"bool": {
"filter": [
{
"term": {
"name.keyword": "John Doe"
}
},
{
"terms": {
"state.keyword": [
"AZ",
"CA"
]
}
}
]
}
}
}
I have to combine two filters to match requirements:
- a specific list of values in r.status field
- one of the multiple text fields contains the value.
Result query (with using Nest, but it doesn't matter) looks like:
{
"query": {
"bool": {
"filter": [
{
"bool": {
"must": [
{
"term": {
"isActive": {
"value": true
}
}
},
{
"nested": {
"query": {
"bool": {
"must": [
{
"terms": {
"r.status": [
"VALUE_1",
"VALUE_2",
"VALUE_3"
]
}
},
{
"bool": {
"should": [
{
"match": {
"r.g.firstName": {
"type": "phrase",
"query": "SUBSTRING_VALUE"
}
}
},
{
"match": {
"r.g.lastName": {
"type": "phrase",
"query": "SUBSTRING_VALUE"
}
}
}
]
}
}
]
}
},
"path": "r"
}
}
]
}
}
]
}
}
}
Also tried with multi_match query:
{
"query": {
"bool": {
"filter": [
{
"bool": {
"must": [
{
"term": {
"isActive": {
"value": true
}
}
},
{
"nested": {
"query": {
"bool": {
"must": [
{
"terms": {
"r.status": [
"VALUE_1",
"VALUE_2",
"VALUE_3"
]
}
},
{
"multi_match": {
"query": "SUBSTRING_VALUE",
"fields": [
"r.g.firstName",
"r.g.lastName"
]
}
}
]
}
},
"path": "r"
}
}
]
}
}
]
}
}
}
FirstName and LastName are configured in index mappings as text:
"firstName": {
"type": "text"
},
"lastName": {
"type": "text"
}
Elastic gives a lot of full-text search options: multi_match, phrase, wildcards etc. But all of them fail in my case looking a sub-string in my text fields. (terms query and isActive one work well, I just tried to run only them).
What options do I have also or maybe where I made a mistake?
UPD: Combined wildcards worked for me, but such query looks ugly. Looking for a more elegant solution.
The elasticsearch way is to use ngram tokenizer.
The ngram analyzer will split your terms with a sliding window. For example, the input "Hello World" will generate the following terms:
Hel
Hell
Hello
ell
ello
...
Wor
World
orl
...
You can configure the minimum and maximum size of the sliding window (in the example the minimum size is 3). Once the sub terms are generated you can use a match query an the subfield.
Another point, it is weird to use must within a filter. If you are interested in the score, you should always use must otherwise use filter. Read this article for a good understanding.
I have been trying to combine MUST-MATCH with MULTI-MATCH but couldn't get it to work. Basically I want these MUST conditions:
"must": [{ "match": { "city": $city } },
{ "match": { "is_displayed": 1 } },
{ "match": { "status": "active" } }]
and I want these matches:
"multi_match": {
"query": $query,
"type": $selectedType,
"fields": fieldArray,
}
where $query is the textbox values $selectedType is one of the multi-match query types and fieldArray is the fields to search for. For example, when the text box value is "hello world" and fieldArray is ['title', 'cuisine'], either "hello" and/or "world" must match either or all of the specified fields. Any insight and advice is appreciated.
I guess adding another clause in must block will do the needful.
{
"query": {
"bool": {
"must": [
{
"match": {
"city": "$city"
}
},
{
"match": {
"is_displayed": 1
}
},
{
"match": {
"status": "active"
}
},
"query_string": {
"fields": fieldArray,
"query": "*$query*"
}
}
]
}
}
}
I am trying to figure out how to AND my Elastic Search query. I've tried a few different variations but I am always hitting a parser error.
What I have is a structure like this:
{
"title": "my title",
"details": [
{ "name": "one", "value": 100 },
{ "name": "two", "value": 21 }
]
}
I have defined details as a nested type in my mappings. What I'm trying to achieve is a query where it matches a part of the title and it matches various details by the detail's name and value.
I have the following query which gets me nearly there but I haven't been able to figure out how to AND the details. As an example I'd like to find anything that has:
detail of one with value less than or equal to 100
AND detail of two with value less than or equal to 25
The following query only allows me to search by one detail name/value:
"query" : {
"bool": {
"must": [
{ "match": {"title": {"query": titleQuery, "operator": "and" } } },
{
"nested": {
"path": "details",
"query": {
"bool": {
"must": [
{ "match": {"details.name" : "one"} },
{ "range": {"details.value" : { "lte": 100 } } }
]
}
}
} // nested
}
] // must
}
}
As a second question, would it be better to query the title and then move the nested part of the query into a filter?
You were so close! Just add another "nested" clause in your outer "must":
POST /test_index/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"title": {
"query": "title",
"operator": "and"
}
}
},
{
"nested": {
"path": "details",
"query": {
"bool": {
"must": [
{"match": {"details.name": "one" } },
{ "range": { "details.value": { "lte": 100 } } }
]
}
}
}
},
{
"nested": {
"path": "details",
"query": {
"bool": {
"must": [
{"match": {"details.name": "two" } },
{ "range": { "details.value": { "lte": 25 } } }
]
}
}
}
}
]
}
}
}
Here is some code I used to test it:
http://sense.qbox.io/gist/1fc30d49a810d22e85fa68d781114c2865a7c92e
EDIT: Oh, the answer to your second question is "yes", though if you're using 2.0 things have changed a little.
I am able to get data for the following elastic search query :
{
"query": {
"filtered": {
"query": [],
"filter": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"term": {
"gender": "malE"
}
},
{
"term": {
"sentiment": "positive"
}
}
]
}
}
]
}
}
}
}
}
However, If I query using "match" - I get error message with 400 status response
{
"query": {
"filtered": {
"query": [],
"filter": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"match": {
"gender": "malE"
}
},
{
"term": {
"sentiment": "positive"
}
}
]
}
}
]
}
}
}
}
}
Is match query not supported in nested bool filters ?
Since the term query looks for the exact term in the field’s inverted index and I want to query gender data as case_insensitive field - Which approach shall I try ?
Settings of the index :
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"analyzer_keyword": {
"tokenizer": "keyword",
"filter": "lowercase"
}
}
}
}
}
}
Mapping for field Gender:
{"type":"string","analyzer":"analyzer_keyword"}
The reason you're getting an error 400 is because there is no match filter, only match queries, even though there are both term queries and term filters.
Your query can be as simple as this, i.e. no need for a filtered query, simply put your term and match queries into a bool/should:
{
"query": {
"bool": {
"should": [
{
"match": {
"gender": "male"
}
},
{
"term": {
"sentiment": "positive"
}
}
]
}
}
}
This answer is for ElasticSearch 7.x. As I understand from the question, you would like to use a match query for the gender field and a term query for the sentiment field. The mappings for each of these field should look like below:
"sentiment": {
"type": "keyword"
},
"gender": {
"type": "text"
}
The corresponding search API would be:
"query": {
"bool": {
"must": [
{
"terms": {
"sentiment": [
"very positive", "positive"
]
}
},
{
"match": {
"gender": "malE"
}
}
]
}
}
This search API returns all the documents where gender is "Male"/"MALE"/"mALe" etc. So, you may have indexed the gender field holding "mALe", but, the match query for "gender": "malE" will still be able to retrieve it. In the latest version of ElasticSearch, if the query is a match type, the value (which is "gender": "malE") will be automatically lower cased internally before search begins. But, it should not be that tough for a client of the API to pass a lowercase to the match query at the onset itself. Coming to the sentiment field, since, its a keyword field, you can search for values that contain spaces too like very positive.