ı want to find a field, Which field did find the search query?
this can be any query I am not writing a specific query
for example
ı searching dilo abinin phrase or any word, and found bellow document
{
"name":"dilo abinin",
"surname: "sürücü"
}
ı want to get name keyword
You can use highlighting, to see which field matched your query
Index API
{
"name":"dilo abinin",
"surname": "sürücü"
}
Search Query:
{
"query": {
"query_string": {
"query": "dilo abinin"
}
},
"highlight": {
"fields": {
"*": {}
}
}
}
Search Result:
"hits": [
{
"_index": "65325154",
"_type": "_doc",
"_id": "1",
"_score": 0.5753642,
"_source": {
"name": "dilo abinin",
"surname": "sürücü"
},
"highlight": {
"name": [ // note this
"<em>dilo</em> <em>abinin</em>"
],
"name.keyword": [
"<em>dilo abinin</em>"
]
}
}
]
Related
I have an index = "es_demo" , where I need to find similar documents to given "_id",
I don't think it is working as the returned results have same "_id" as mentioned in the query .
And as written in the elastic documentation having "include" parameter as "false" will not be returning the "ids" mentioned in the query.
{
"query": {
"more_like_this": {
"fields": "_doc",
"like": {
"docs": [
{
"_id": "5fac83afdce931230ef44c0a"
},
{
"_id": "5f80096adce931230e8bdb2d"
}
]
}
}
},
"include": "false"
}
Can someone please help me out here I think the query I wrote is wrong.
I also tried these queries :
{
"query": {
"more_like_this": {
"fields": "_doc",
"like": [
{
"_id": "5fac83afdce931230ef44c0a"
},
{
"_id": "5f80096adce931230e8bdb2d"
}
]
}
}
}
{
"query": {
"more_like_this": {
"fields": "_doc",
"like": [
{
"_id": "5fac83afdce931230ef44c0a"
},
{
"_id": "5f80096adce931230e8bdb2d"
}
]
}
},
"include": "False"
}
The first result I got was the same document with "_id": "5fac83afdce931230ef44c0a" for every query
The query below works for my index movies.
Remember about parameter fields:
A list of fields to fetch and analyze the text from. Defaults to the
index.query.default_field index setting, which has a default value of
*. The * value matches all fields eligible for term-level queries, excluding metadata fields.
Query (edit for you case)
GET idx_movies/_search
{
"_source": [
"title"
],
"query": {
"more_like_this": {
"fields": [
"title", "description"
],
"like": [
{
"_id": "GjP1WYUBQB-6H-4Z96IG"
}
],
"min_term_freq":1
}
}
}
I have a issue in Elastic search 1.4 phrase query. I am creating a below index with the data.
curl -XPUT localhost:9200/test
curl -XPOST localhost:9200/test/doc/1 -d '{"field1" : "abc-xyz"}'
curl -XPOST localhost:9200/test/doc/2 -d '{"field1" : "bcd-gyz"}'
So by default field1 is analyzed by elastic search with default analyzer.
I am searching below phrase query but its not returning any result.
{
"query": {
"filtered": {
"filter": {
"bool": {
"should": [
{
"query": {
"multi_match": {
"query": "abc\\-xyz OR bcd\\-gyz",
"type": "phrase",
"fields": [
"field1"
]
}
}
}
]
}
}
}
}
}
So elastic search phrase query is not working with OR operator. Any idea why its not working, is it a limitation of elastic search because of special character hyphen (-) in text?
Based on the comment, adding a answer using query string which works with OR in phrase with multiple search, it didn't work with multiple multi-match hence have to use query string.
Using the same indexed doc, added in previous answer, but with below search query.
{
"query": {
"bool": {
"must": [
{
"query_string": {
"query": "\"abc-xyz\" OR \"bcd-gyz\"",
"fields": [
"title"
]
}
}
]
}
}
}
Search results
"hits": [
{
"_index": "phrasemulti",
"_type": "doc",
"_id": "1",
"_score": 0.05626005,
"_source": {
"title": "bcd-gyz"
}
},
{
"_index": "phrasemulti",
"_type": "doc",
"_id": "2",
"_score": 0.05626005,
"_source": {
"title": "abc-xyz"
}
}
]
When you remove few char, pharse query won't work or when you change operator to AND, sample data doesn't return search results which is expected.
{
"query": {
"bool": {
"must": [
{
"query_string": {
"query": "\"abc-xyz\" OR \"bcd-gz\"",
"fields": [
"title"
]
}
}
]
}
}
}
Returns only one search result, as there is no phrase bcd-gz exist in sample data.
"hits": [
{
"_index": "phrasemulti",
"_type": "doc",
"_id": "2",
"_score": 0.05626005,
"_source": {
"title": "abc-xyz"
}
}
]
Below query works fine for me
{
"query": {
"filtered": {
"filter": {
"bool": {
"should": [
{
"query": {
"multi_match": {
"query": "abc-xyz", // note passing only one query without escaping hyphen
"type": "phrase",
"fields": [
"title"
]
}
}
}
]
}
}
}
}
}
Search results with explain param
"hits": [
{
"_shard": 3,
"_node": "1h3iipehS2abfclj51Vtsg",
"_index": "phrasemulti",
"_type": "doc",
"_id": "2",
"_score": 1.0,
"_source": {
"title": "abc-xyz"
},
"_explanation": {
"value": 1.0,
"description": "ConstantScore(BooleanFilter(QueryWrapperFilter(title:\"abc xyz\"))), product of:",
"details": [
{
"value": 1.0,
"description": "boost"
},
{
"value": 1.0,
"description": "queryNorm"
}
]
}
}
]
Verified its returning results according to phrase as query abc-xy doesn't return any result.
I have a search index of filenames containing over 100,000 entries that share about 500 unique variations of the main filename field. I have recently made some modifications to certain filename values that are being generated from my data. I was wondering if there is a way to link certain queries to return an exact match. In the following query:
"query": {
"bool": {
"must": [
{
"match": {
"filename": "foo-bar"
}
}
],
}
}
how would it be possible to modify the index and associate the results so that above query will also match results foo-bar-baz, but not foo-bar-foo or any other variation?
Thanks in advance for your help
You can use a term query instead of a match query. Perfect to use on a keyword:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
Adding a working example with index data and search query. (Using the default mapping)
Index Data:
{
"fileName": "foo-bar"
}
{
"fileName": "foo-bar-baz"
}
{
"fileName": "foo-bar-foo"
}
Search Query:
{
"query": {
"bool": {
"should": [
{
"match": {
"fileName.keyword": "foo-bar"
}
},
{
"match": {
"fileName.keyword": "foo-bar-baz"
}
}
]
}
}
}
Search Result:
"hits": [
{
"_index": "test",
"_type": "_doc",
"_id": "1",
"_score": 0.9808291,
"_source": {
"fileName": "foo-bar"
}
},
{
"_index": "test",
"_type": "_doc",
"_id": "2",
"_score": 0.9808291,
"_source": {
"fileName": "foo-bar-baz"
}
}
]
I have a fuzzy query with customized AUTO:10,20 fuzziness value.
{
"query": {
"match": {
"name": {
"query": "nike",
"fuzziness": "AUTO:10,20"
}
}
}
}
How to convert it to a query_string query? I tried nike~AUTO:10,20 but it is not working.
It's possible with query_strng as well, let me show using the same example as OP provided, both match_query provided by OP matches and query_string fetches the same document with same score.
And according to this and this ES docs, Elasticsearch supports AUTO:10,20 format, which is shown in my example as well.
Also
Index mapping
{
"mappings": {
"properties": {
"name": {
"type": "text"
}
}
}
}
Index some doc
{
"name" : "nike"
}
Search query using match with fuzziness
{
"query": {
"match": {
"name": {
"query": "nike",
"fuzziness": "AUTO:10,20"
}
}
}
}
And result
"hits": [
{
"_index": "so-query",
"_type": "_doc",
"_id": "1",
"_score": 0.9808292,
"_source": {
"name": "nike"
}
}
]
Query_string with fuzziness
{
"query": {
"query_string": {
"fields": ["name"],
"query": "nike",
"fuzziness": "AUTO:10,20"
}
}
}
And result
"hits": [
{
"_index": "so-query",
"_type": "_doc",
"_id": "1",
"_score": 0.9808292,
"_source": {
"name": "nike"
}
}
]
Lucene syntax only allows you to specify "fuzziness" with the tilde symbol "~", optionally followed by 0, 1 or 2 to indicate the edit distance.
Elasticsearch Query DSL supports a configurable special value for AUTO which then is used to build the proper Lucene query.
You would need to implement that logic on your application side, by evaluating the desired edit distance based on the length of your search term and then use <searchTerm>~<editDistance> in your query_string-query.
I have a query in which i want to add a must_not clause that would discard all records that have blank data for a some field. I tried a lot of ways but none worked. when I issue the same query (mentioned below) with other specific fields then it works fine.
this query should get all records that do not have "registrationType1" field empty/blank
query:
{
"size": 20,
"_source": [
"registrationType1"
],
"query": {
"bool": {
"must_not": [
{
"term": {
"registrationType1": ""
}
}
]
}
}
}
the results below still contains "registrationType1" with empty values
results:
**"_source": {
"registrationType1": ""}}
, * {
"_index": "oh_animal",
"_type": "animals",
"_id": "3842002",
"_score": 1,
"_source": {
"registrationType1": "A&R"}}
, * {
"_index": "oh_animal",
"_type": "animals",
"_id": "3842033",
"_score": 1,
"_source": {
"registrationType1": "AMHA"}}
, * {
"_index": "oh_animal",
"_type": "animals",
"_id": "3842213",
"_score": 1,
"_source": {
"registrationType1": "AMHA"}}
, * {
"_index": "oh_animal",
"_type": "animals",
"_id": "3842963",
"_score": 1,
"_source": {
"registrationType1": ""}}
, * {
"_index": "oh_animal",
"_type": "animals",
"_id": "3869063",
"_score": 1,
"_source": {
"registrationType1": ""}}**
PFB mappings for the field above
"registrationType1": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
You need to use the keyword subfield in order to do this:
{
"size": 20,
"_source": [
"registrationType1"
],
"query": {
"bool": {
"must_not": [
{
"term": {
"registrationType1.keyword": "" <-- change this
}
}
]
}
}
}
If you do not specify any text value on the text fields, there is basically nothing to analyze and return the documents accordingly.
In similar way, if you remove must_not and replace it with must, it would show empty results.
What you can do is, looking at your mapping, query must_not on keyword field. Keyword fields won't be analysed and in that way your query would return the results as you expect.
Query
POST myemptyindex/_search
{
"query": {
"bool": {
"must_not": [
{
"term": {
"registrationType1.keyword": ""
}
}
]
}
}
}
Hope this helps!
I am using elasticsearch version 7.2,
I replicated your data and ingested in my elastic index,and tried querying with and without .keyword.
I am getting the desired result when using the ".keyword" in the field name.It is not returning the docs which have registrationType1="".
Note - The query does not works when not using the ".keyword"
I have added my sample code below, have a look if that helps.
from elasticsearch import Elasticsearch
es = Elasticsearch()
es.indices.create(index="test", ignore=400, body={
"mappings": {
"_doc": {
"properties": {
"registrationType1": {
"type": "text",
"field": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
})
data = {
"registrationType1": ""
}
es.index(index="test",doc_type="_doc",body=data,id=1)
search = es.search(index="test", body={
"size": 20,
"_source": [
"registrationType1"
],
"query": {
"bool": {
"must_not": [
{
"term": {
"registrationType1.keyword": ""
}
}
]
}
}
})
print(search)
Executing the above should not return any results as we are inserting empty for the field
There was some issue with the mappings itself, I deleted the index and re-indexed it with new mappings and its working now.