I'm creating an advance search using elasticsearch and its query string functionality..
so I got some questions about advance queries.. I read query string document but couldn't find any answer,
when in one query string I search for a normal query and a exact query.. sales AND "industrial machinery" the result is different with another query that put two query string in must array...
let me show with an example:
"query": {
"bool":{
"must":[
{
"query_string":{
"query": "sales* AND \"industrial machinery\"",
"type": "best_fields",
"fields":["title", "description"]
}
}
]
}
}
count of result : 56
"query":{
"bool":{
"must":[
{
"query_string":{
"query": "sales*",
"type": "best_fields",
"fields":["title", "description"]
},
{
"query_string":{
"query": "\"industrial machinery\"",
"type": "best_fields",
"fields":["title", "description"]
}
]
}
}
count of results: 113
I know the result of second query is correct, but I don't know why elastic made difference between this two queries..
and how can I get same result with first query? I want to get 113 docs when search with first query.
thanks for helping
Related
This is my first ever question here so I apologize if I make any mistakes.
I'm trying to make a fuzzy search (match query with fuzziness parameter) on my index that will return the results in Alphabetical order. But I need the exact matches to come first(Alphabetically ordered among themselves) and fuzzy matches later.
I have tried this to make exact matches have higher scores. But they are just being sorted by their scores:
"query":{
"bool":{
"must":[
{
"match":{
"myPropertyName":{
"query":"myWord",
"fuzziness":"AUTO"
}
}
}
],
"should":[
{
"match":{
"myPropertyName":{
"query":"myWord",
"boost":20
}
}
}
]
}
},
"sort":[
"_score",
{
"myProperty.keyword":{
"order":"asc"
}
}
],
"track_scores":true
}
Then I have tried to make the scores of all exact matches and fuzzy matches same among themselves with many methods. I can make it for fuzzy matches by using filter or constant_score but I couldn't figure a way to assign a custom score to the results of should query in my search.
How can I achieve this?
I've managed to achieve this by using a function score query with "boost_mode": "replace" and setting a custom value to weight parameter like: "weight": "10".
{
"query":{
"function_score":{
"query":{
"bool":{
"filter":[
{
"match":{
"myPropertyName":{
"query":"myWord",
"fuzziness":"AUTO"
}
}
}
]
}
},
"boost_mode":"replace",
"functions":[
{
"filter":{
"match":{
"myPropertyName":{
"query":"myWord"
}
}
},
"weight":"10"
}
]
}
},
"sort":[
"_score",
{
"myProperty.keyword":{
"order":"asc"
}
}
],
"track_scores":true
}
This way documents that match the match query will return with 0 score since it's also a filter query. Then among these documents the ones that match the function will return with 10 score since "boost_mode": "replace" and "weight: "10".
When it comes to sorting firstly Elasticsearch will sort the results by their score's since it comes first in "sort[]" array. Then documents with same scores will be sorted alphabetically among themselves.
This worked perfectly for me.
elasticsearch version: 6.4
Here is my current data:
I want to search for products which has Xbox in name. I am using the match keyword but that is not working.
Below is my elastic search query:
{
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "xbox"
}
}
},
{
"terms": {
"deep_sub": [
"Konsol Oyunları",
"Konsol Aksesuarları"
]
}
}
]
}
},
"from": 0,
"size": 50
}
Whenever you face such kind of issues, try breaking down the query. You have Match Query and Term Query. Run both of them individually and see what's not working.
From what I understand, looks like your field deep_sub is of text type and this would mean Term Query is not returning results.
You would need to create its sibling equivalent using keyword type and then run Term Query on it for exact matches.
From the above link we have the below info:
Keyword fields are only searchable by their exact value.
If you do not control the mapping, meaning if your mapping if of dynamic type, then you must have its sibling equivalent keyword field available which would be deep_sub.keyword
You can check by running GET <your_index_name>/_mapping
Your query would then be as follows:
POST <your_index_name>/_search
{
"query":{
"bool":{
"must":[
{
"match":{
"name":{
"query":"xbox"
}
}
},
{
"terms":{
"deep_sub.keyword":[ <----- Change This
"Konsol Oyunları",
"Konsol Aksesuarları"
]
}
}
]
}
},
"from":0,
"size":50
}
Let me know if this helps!
The simple query
"query": {
"simple_query_string": { "query":"great guide" }
},
returns my document as expected, containing
"groups": [
"Local Business"
],
But if I use a filter, it returns no documents:
"query": {
"bool":{
"must":[
{"simple_query_string": { "query":"great guide" }}
],
"filter":{
"terms":{
"groups":["Local Business"]
}
}
}
},
If I remove the "filter" key and values, then the document is retrieved.
Why isn't the filter matching the document ?
If the groups field is of type keyword, then the query you've mentioned works as expected.
However it wouldn't work if the field groups if of type text. In that case the below query would actually fit what you are looking for.
Query for group - Type text
POST <your_index_name>/_search
{
"query":{
"bool":{
"must":[
{
"simple_query_string":{
"query":"great guide"
}
}
],
"filter":{
"match":{
"groups":"Local Business"
}
}
}
}
}
The reason the query you've mentioned doesn't work for the field of type text is because this field goes through Analysis phase making use of Standard Analyzer by default where it would first convert Local Business into small cases and then saves local and business as two individual words in the inverted index.
Elasticsearch would only give you results if the words you query match what's available in the index.
And what keyword does is, it saves Local Business as is in inverted index.
Note: You can try the query you have by replacing groups with groups.keyword if mapping hasn't been defined and is created dynamically.
Hope this helps!
I run this query:
GET /thing/_search/?
{
"query": {
"multi_match" : {
"query": "castle pontivy",
"type": "most_fields",
"fields": [ "title", "loc" ]
}
}
}
It works and returns results from thing where title and loc contains castle and/or pontivy in a relevant order. Nice.
Now I want to continue querying like this, but I also want the result to prefer exact match on title. Which means that if one item exactly match castle pontivy in its title, it must be returned as first element (then the other results are treated as usual).
Is there a way to do this?
You could do a phrase match and give it a boost of 5, so whatever the default score is, it will add +5 to that. If you want to get more into scoring, look into function score query (I recommend you should)
Second multi_match will match the rest of the documents using most_fields.
{
"query":{
"bool":{
"should":[
{
"multi_match":{
"query":"castle pontivy",
"type":"phrase",
"fields":[
"title",
"loc"
],
"boost":5
}
},
{
"multi_match":{
"query":"castle pontivy",
"type":"most_fields",
"fields":[
"title",
"loc"
]
}
}
]
}
}
}
I'm using the following query on Elastic Search 2.3.3
es_query = {
"fields": ["title", "content"],
"query":
{
"multi_match" : {
"query": "potato tomato",
"type": "best_fields",
"fields": [ "title_cuis", "content_cuis" ]
}
}
}
I would like the results to be scored so that the first document returned is the one that contains the highest occurrence of the words "tomato" and "potato", but this doesn't seem to happen and I was wondering how I can modify the query to get that without re-indexing.
You're using best_fields, this will use the max score retrieved in matching process from title_cuis or content_cuis, separately.
Take a look to cross-fields