I have this query to get data from AWS elasticSearch instance v6.2
{
"query": {
"bool": {
"must": [
{
"term": {"logLevel": "error"}
},
{
"bool": {
"should": [
{
"match": {"EventCategory": "Home Management"}
}
]
}
}
],
"filter": [{
"range": { "timestamp": { "gte": 155254550880 }}
}
]
}
},
"size": 10,
"from": 0
}
My data has multiple EventCategories for example 'Home Management' and 'User Account Management'. Problem with this is inside should having match returns all data because phrase 'Management' is in both categories. If I use term instead of match, it don't returns anything at all even when the given value is exactly same as in document.
I need to get data when any of given category is matched with rest of filters.
EDIT:
There may none, one or more than one EventCategory be passed to should clause
I'm not sure why you added a should within a must. Do you expect to have more than one should cases? It looks a bit odd.
As for your question, you can't use the term query on an analysed field, but only on keyword typed fields. If your EventCategory field has the default mapping, you can run the term query against the default non-analysed multi-field of EventCategory as follows:
...
{
"term": { "EventCategory.keyword": "Home Management" }
}
...
Furthermore, if you just want to filter in/out documents without caring about their relevance, I'd recommend you to move all the conditions in the filter block, to speed-up your query and make a better use of the cache.
Below query should work.
I've just removed should and created two must clauses one for each of event and management. Note that the query is meant for text datatypes.
{
"query":{
"bool":{
"must":[
{
"term":{
"logLevel":"error"
}
},
{
"match":{
"EventCategory":"home"
}
},
{
"match":{
"EventCategory":"management"
}
}
],
"filter":[
{
"range":{
"timestamp":{
"gte":155254550880
}
}
}
]
}
},
"size":10,
"from":0
}
Hope it helps!
Related
I have a situation where I need to do elastic search based on multi-field. For Example: I have multiple fields in my postindex and I want to apply condition on four these fields (i.e. userid, channelid, createat, teamid) to meet my search requirement. When value of all these fields matched then search query displays results and if one of these is not match with values in postindex then it display no result.
I am trying to make a multifield search query for go-elasticsearch to search data from my post index. For the searcquery result four field must match otherwise it display 0 hit/no-result.
So, I think you need to write a following query :
GET postindex/_search
{
"query": {
"bool": {
"minimum_should_match": 1,
"should": [
{
"bool": {
"must": [
{
"term": {
"userid": {
"value": "mcqmycxpyjrddkie9mr13txaqe"
}
}
},
{
"term": {
"channelid": {
"value": "dnoihmrinins3qrm6bb9175ume"
}
}
},
{
"range": {
"createat": {
"gt": 1672909114890
}
}
}
]
}
},
{
"term": {
"teamid": {
"value": "qomrg11o8b8ijxoy8hrcnweoay"
}
}
}
]
}
}
}
In here, there is a bool query with should in parent scope, which is like OR. And inside the should there is another bool query with must which is like AND. We can also write the query shorter, but this will be better for you to understand.
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!
I feel like this shouldn't be as difficult as its turning out to be, I've been attempting to use the:
index/_search
and
index/_count
endpoints, using query, bool, must filter etc. It seems no matter how I construct it, I cannot use range and date, with the match filter. The elasticsearch documentation doesn't seem to show complex queries like this so I'm not exactly sure how to construct it. The main query I've been manipulating is:
{
"query":{
"bool":{
"must":{
"range":{
"date":{
"gte":"now-1d/d",
"lt" :"now/d"
}
},
"match":{
"KEY":"VALUE"
}
}
}
}
}
I either get "no query registered for date", or "unknown key for a start_object in match" Been all over stackoverflow and can't seem to find an answer to this, it seems like it should be quite a simple query to make against a data store such as this. What am I missing here?
must can take an array of conditions if you want to combine them. Try this format :
{
"query": {
"bool": {
"must": [
{
"range": {
"date": {
"gte": "now-1d/d",
"lt": "now/d"
}
}
},
{
"match": { "KEY": "VALUE" }
}
]
}
}
}
I'm creating filtering queries which operates on two fields. I would like to avoid computing relevance by Elasticsearch. How to achieve OR statement without moving to query context.
My simplified model has two boolean fields:
{
is_opened,
is_send
}
I'd like to prepare query with logic:
(is_opened == true AND is_send == true) OR (is_opened == false)
In other words I want to exclude documents with fields:
is_opened == true AND is_send == false
My query looks like that:
GET documents/default/_search
{
"query": {
"bool": {
"should": [
{
"bool":{
"must":[
{"term": {"is_opened":true}},
{"term": {"is_send":true}}
]
}
},
{
"bool":{
"must":[
{"term": {"is_opened":false}}
]
}
}
]
}
}
}
Logically it works as I expected but Elasticsearch computes relevance.
I don't need it because at the end I sort results by another field so it's a place to optimize queries.
I ask about it because Frequently used filters will be cached automatically by Elasticsearch, to speed up performance.
My results have _score field computed so I think that above query is executed in query context so Elasticsearch won't cache it automatically.
In the future I would like to create queries which operates on status fields, where logic would be more complicated. Still I need to know how to block computing _score.
I noticed that changing should to filter block computing _score but works as must operator. Is it possible to change filter behavior?
Is it possible to use another query than should?
How to force Elasticserach to stop computing _score?
Simply wrap your query inside the constant_score query:
GET documents/default/_search
{
"query": {
"constant_score": {
"filter": {
"bool": {
"should": [
{
"bool": {
"must": [
{
"term": {
"is_opened": true
}
},
{
"term": {
"is_send": true
}
}
]
}
},
{
"bool": {
"must": [
{
"term": {
"is_opened": false
}
}
]
}
}
]
}
}
}
}
}
I have data on ElasticSearch index that looks like this
{
"title": "cubilia",
"people": [
"Ling Deponte",
"Dana Madin",
"Shameka Woodard",
"Bennie Craddock",
"Sandie Bakker"
]
}
Is there a way for me to do a search for all the people whos name starts with
"ling" (should be case insensitive) and get distinct terms properly cased "Ling Deponte" not "ling deponte"?
I am find with changing mappings on the index in any way.
Edit does what I want but is really bad query:
{
"size": 0,
"aggs": {
"person": {
"filter": {
"bool":{
"should":[
{"regexp":{
"people.raw":"(.* )?[lL][iI][nN][gG].*"
}}
]}
},
"aggs": {
"top-colors": {
"terms": {
"size":10,
"field": "people.raw",
"include":
{
"pattern": ["(.* )?[lL][iI][nN][gG].*"]
}
}
}
}
}
}
}
people.raw is not_analyzed
Yes, and you can do it without a regular expression by taking advantage of Elasticsearch's full text capabilities.
GET /test/_search
{
"query": {
"match_phrase": {
"people": "Ling"
}
}
}
Note: This could also be match or match_phrase_prefix in this case. The match_phrase* queries imply an order of the values in the text. match simply looks for any of the values. Since you only have one value, it's pretty much irrelevant.
The problem is that you cannot limit the document responses to just that name because the search API returns documents. With that said, you can use nested documents and get the desired behavior via inner_hits.
You do not want to do wildcard prefixing whenever possible because it simply does not work at scale. To put it in SQL terms, that's like doing a full table scan; you effectively lose the benefit of the inverted index because it has to walk it entirely to find the actual start.
Combining the two should work pretty well though. Here, I use the query to widdle down results to what you are interested in, then I use your inner aggregation to only include based on the value.
{
"size": 0,
"query": {
"match_phrase": {
"people": "Ling"
}
}
"aggs": {
"person": {
"terms": {
"size":10,
"field": "people.raw",
"include": {
"pattern": ["(.* )?[lL][iI][nN][gG].*"]
}
}
}
}
}
Hi Please find the query it may help for your request
GET skills/skill/_search
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"bool": {
"must": [
{
"wildcard": {
"skillNames.raw": "jav*"
}
}
]
}
}
}
}
}
My intention is to find documents starting with the "jav"