I recently upgraded my ElasticSearch version from version 5.3 to version 5.6
"query" : {
"constant_score" : {
"query" : {
"bool" : {
"must" : {
"terms" : {
"customerId" : [ "ASERFE", "7004567457" ]
}
},
"must_not" : {
"terms" : {
"useCase" : [ "PAY", "COLLECT" ]
}
}
},
"bool" : {
"must" : {
"match" : {
"cardProductGroupName" : {
"query" : "Pre-fill Test birthday Present",
"type" : "phrase"
}
}
}
}
}
}
}
executing the query mentioned above gave me the following error -
{"root_cause":[{"type":"parsing_exception","reason":"[constant_score] query does not support [query]","line":1,"col":37}],"type":"parsing_exception","reason":"[constant_score] query does not support [query]","line":1,"col":37}
So, I searched for the solution and found this function_score query. On executing the query mentioned below I am getting the same results that I would have got with constant_score.
"query" : {
"function_score" : {
"query" : {
"bool" : {
"must" : {
"terms" : {
"customerId" : [ "ASERFE", "7004567457" ]
}
},
"must_not" : {
"terms" : {
"useCase" : [ "PAY", "COLLECT" ]
}
}
},
"bool" : {
"must" : {
"match" : {
"groupName" : {
"query" : "Pre-fill Test birthday Present",
"type" : "phrase"
}
}
}
}
},
"functions" : [ {
"script_score" : {
"script" : "1"
}
} ],
"boost_mode" : "replace"
}
}
so my question is, Does it implies that function_score with script : "1" would give same result as constant_function ?
It will give the same result indeed though performance might be worse if it will still run the "script" for each matching document.
On the other hand, constant_score still exists in 5.6 though you have to use filter+boost instead of query.
Related
I want to do a query, with one field match different values,In SQL it likes:
select * from location where address like '%California%' and address like '%145%';
I tried using must condition array, it contains several phrase match conditions, but its doesnt work!
{
"from" : 0,
"size" : 10,
"query" : {
"bool" : {
"must" : {
"bool" : {
"must" : [ {
"match" : {
"address" : {
"query" : "California",
"type" : "phrase"
}
}
}, {
"match" : {
"address" : {
"query" : "145",
"type" : "phrase"
}
}
} ]
}
}
}
},
"sort" : [ {
"pageRankScore" : {
"order" : "desc",
"unmapped_type" : "double"
}
} ]
}
Thats my code, it only do a match '145', never match 'California'.
My question is: with several values, how to do a fuzzy match in one field?
Help me, thanks a lot!
I've a problem to understand the functionality of the following Elasticsearch (ES 6.4) query:
{
"query" : {
"bool" : {
"should" : [
{
"match" : {
"title" : {
"query" : "example",
"operator" : "AND",
"boost" : 2
}
}
},
{
"multi_match" : {
"type" : "best_fields",
"query" : "example",
"operator" : "AND",
"fields" : [
"author", "content", "tags"
],
"boost" : 1
}
}
],
"must" : [
{
"range" : {
"dateCreate" : {
"gte" : "2000-01-01T00:00:00+0200",
"lte" : "2019-02-12T23:59:59+0200"
}
}
},
{
"term" : {
"client" : {
"value" : "test",
"boost" : 1
}
}
}
]
}
},
"size" : 10,
"from" : 0,
"sort" : [
{
"_score" : {
"order" : "desc"
}
}
]
}
The query is executed successfully but retrieves about 400,000 documents which is the total count of my index. It means that all documents are in the result set. But why? Is this really the correct behavior of the multi_match query?
When I was still using the query_string query, I only got the actual matching documents. That's why I'm a bit surprised.
You're missing minimum_should_match:
"bool" : {
"minimum_should_match": 1, <--- add this
"should" : [
...
below query is fetching result if i give existing record that is fine , but if i change name field from 'John' to 'John1' then still record is fetching.
{
"query" : {
"bool" : {
"must" : [
{ "match" : {"employeeId" : "1234"}},
{ "match" : {"name" : "John"}}
]
}
}
}
I tried another alternative query as well but still giving result.which query is correct in terms of performance?but both are giving results if i change name record from 'John' to 'John1'
{
"filter": {
"bool" : {
"must" : {
"term" : {
"employeeId" : "1234"
}
}
}
},
"query": {
"match" : {
"name" : {
"query" : "John",
"type" : "phrase"
}
}
}
}
This because you are doing match, if you want do exact search you need to use filter
Notice we assuce the mapping of name column is analyzed
{
"query" :{
"filtered" : {
"filter" : {
"bool" : {
"must" : [
{ "term" : {"employeeId" : "1234"}},
{ "term" : {"name" : "john"}}
]
}
}
}
}
}
I'm having some trouble turning a match_phrase query into a multi_match query for multiple fields. My original query:
{
"from" : 0,
"size" : 50,
"query" : {
"filtered" : {
"query" : {
"match_phrase" : {
"metadata.description" : "Search Terms"
}
},
"filter" : {
"bool" : {
"must" : [ {
"terms" : {
"collectionId" : [ "1", "2" ]
}
} ]
}
}
}
}
}
Returns results correctly, but when I rewrite the match_phrase piece as a multi_match to run against multiple fields:
{
"from" : 0,
"size" : 50,
"query" : {
"filtered" : {
"query" : {
"multi_match" : {
"query" : "Search Terms",
"fields" : [ "metadata.description", "metadata.title" ],
"type" : "phrase"
}
},
"filter" : {
"bool" : {
"must" : [ {
"terms" : {
"collectionId" : [ "1", "2" ]
}
} ]
}
}
}
}
}
I am not getting any results. Is there anything obvious I am doing wrong here?
EDIT:
It must be something to do with the filter, as
{
"from" : 0,
"size" : 50,
"query" : {
"match_phrase" : {
"metadata.description" : "Search Terms"
}
}
}
and
{
"from" : 0,
"size" : 50,
"query" : {
"multi_match" : {
"query" : "Search Terms",
"fields" : [ "metadata.description", "metadata.title" ],
"type" : "phrase"
}
}
}
both perform as expected.
I am not sure why, exactly, but not using a filtered query, and applying the filter at the top level
{
"from" : 0,
"size" : 50,
"query" : {
"multi_match" : {
"query" : "Search Terms",
"fields" : [ "metadata.description", "metadata.title" ],
"type" : "phrase"
}
},
"filter" : {
"bool" : {
"must" : [ {
"terms" : {
"collectionId" : [ "1", "2" ]
}
} ]
}
}
}
resolves the problem.
I have a situation in which my products are described in a few and the following structure is used:
{
"defaultDescription" : "Default Description",
"i18nDescription" : {
"pt" : "Descrição Padrão",
"de" : "Standard-Beschreibung"
}
}
Now I have the following requirement: perform a search following a list of prioritized languages (3 languages). If the first language isn't in the i18nDescription, use just the second language, if the second language isn't there use just the third one otherwise match against defaultDescription.
My solution would be something like:
// suppose request comes with the following languages: en, de, pt
{
"size":10,
"fields" : ["defaultDescription", "i18nDescription.en^50", "i18nDescription.de^20", "i18nDescription.pt^10"],
"query": {
"multi_match" : { "query" : "default", "fields" : ["description","descriptions.fr-CA"] }
}
}
But this solution will just sort the result by priority language, I would like to do something like: i18nDescription.en:search OR (i18nDescription.de:search AND _empty_:i18nDescription.en) OR (i18nDescription.pt:search AND _empty_:i18nDescription.en AND _empty_:i18nDescription.de) OR (description:search AND _empty_:i18nDescription.pt AND _empty_:i18nDescription.en AND _empty_:i18nDescription.de)
Is there a way to represent this is a ElasticSearch query?
Playing a bit with bool queries we could reach the desired effect.
It basically needs to check if one field has the text and others (that are more important) are empty, so it would consider just the most important present field.
Query would be something similar to:
{
"size":10,
"query": {
"bool" : {
"should" : [
{
"bool" : {
"must" : [
{ "multi_match" : { "fields":["defaultDescription"], "query" : "default" } },
{ "query_string" : { "query" : "+_missing_:i18nDescription.en +_missing_:i18nDescription.de +_missing_:i18nDescription.pt" } }
]
}
},
{
"bool" : {
"must" : [
{ "multi_match" : { "fields":["i18nDescription.pt"], "query" : "default" } },
{ "query_string" : { "query" : "+_missing_:i18nDescription.en +_missing_:i18nDescription.de" } }
]
}
},
{
"bool" : {
"must" : [
{ "multi_match" : { "fields":["i18nDescription.de"], "query" : "default" } },
{ "query_string" : { "query" : "+_missing_:i18nDescription.en" } }
]
}
},
{
"bool" : {
"must" : [
{ "multi_match" : { "fields":["i18nDescription.en"], "query" : "default" } }
]
}
}
]
}
}
}