We need to get the data based on multiple values.
So I am trying to use terms query in elastic search for modelNumber field.
But it is not working as expected.can anyone let me know what is wrong with the query.
POST index_name/_Search
{
"query": {
"bool": {
"must": [
{
"terms": {
"modelNumber": [
"test 1234rthg-1234-1234512-2345",
"testMode11l-123-rtyu-xyz11"
]
}
},
{
"terms": {
"userId": [
"123",
"VALUE2"
]
}
}
]
}
}
}
Terms query returns documents that contain one or more exact terms in
a provided field.
If you have not explicitly defined any index mapping, then you need to add .keyword to the modelNumber field. This uses the keyword analyzer instead of the standard analyzer (notice the ".keyword" after modelNumber field).
{
"query": {
"bool": {
"must": [
{
"terms": {
"modelNumber.keyword": [ // note this
"test 1234rthg-1234-1234512-2345",
"testMode11l-123-rtyu-xyz11"
]
}
},
{
"terms": {
"userId": [
"123",
"VALUE2"
]
}
}
]
}
}
}
OR you need to modify the mapping of modelNUmber field as -
{
"mappings": {
"properties": {
"modelNumber": {
"type": "keyword"
}
}
}
}
Related
How would I get all values of all the ids with a given prefix from the elastic search records and make them unique.
Records
PUT items/1
{ "ids" : [ "apple_A", "orange_B" ] }
PUT items/2
{ "ids" : [ "apple_A", "apple_B" ] }
PUT items/3
{ "ids" : [ "apple_C", "banana_A" ] }
What I need is to find all the unique ids for a given prefix, for example if input is apple the output of ids should be ["apple_A", "apple_B", "apple_C"]
What I have tried so far is make use of the term aggregation, with the following query I was able to filter out the documents which have ids with given prefix but in the aggregation it will return all the ids part of the document.
{
"aggregations": {
"filterIds": {
"filter": {
"bool": {
"filter": [
{
"prefix": {
"ids.keyword": {
"value": "apple"
}
}
}
]
}
},
"aggregations": {
"uniqueIds": {
"terms": {
"field": "ids.keyword",
}
}
}
}
}
}
It's returning aggregation list as [ "appleA", "orange_B", "apple_B","apple_C", "banana_A"] if we give prefix input as apple. Basically returning all ids which have a matching filter.
Is there to get only the ids which match the prefix in array and not all the ids in the array of document ?
You can limit the returned values using the include parameter:
POST items/_search
{
"size": 0,
"aggregations": {
"filterIds": {
"filter": {
"bool": {
"filter": [
{
"prefix": {
"ids.keyword": {
"value": "apple"
}
}
}
]
}
},
"aggregations": {
"uniqueIds": {
"terms": {
"field": "ids.keyword",
"include": "apple.*" <--
}
}
}
}
}
}
Do check this other thread which deals with using regex within include -- it's very similar to your use case.
Let's say I have this dictionary:
{
"name": "Jorje",
"surname": "Costali",
"extra_information": {
"real_name": "mamino",
"fake_name": "bambino",
"age": "43",
"gang": "gang34"
}
}
How can I query to get all entries that have "extra_information.gang":"gang34" ? I would like to know how to filter after exact term or having a match.
I have tried:
{
"size": 20,
"query": {
"bool": {
"filter": [
{
"terms": {
"extra_information.gang": [
"gang34"
]
}
}
]
}
}
}
but it does not return any entries.
I have tried:
GET _search
{
"query": {
"bool": {
"must": [
{
"match": {
"extra_information.gang" : "gang34"
}
}
]
}
}
}
and works, but I want to make it into a filter, not a simple match query.
Did you try to use .keyword? like:
"terms": {
"extra_information.gang.keyword": [
"gang34"
]
}
I tried what you wrote on my nested dictionary document, it works like this to me.
My objective is to find out most recent 10 documents which match message id as MSG-1013 and Severity field must be info. Both conditions should satisfied and match text should be exact. I have tried with search query below but it does not give me expected results. What am I doing wrong here ?
{
"size": 10,
"query": {
"bool": {
"must": [
{
"match": { "messageId": "MSG-1013" }
},
{
"match": { "Severity": "Info" }
}
]
}
}
}
If I have understood you correctly, you want to find the top 10 (recent) documents having exactly fields "messageId" and "Severity". I assume, you don't need a score because your score seems to be the the document timestamp or something else like a date field. For this purpose, you could use the bool filter in combination with a sort query.
{
"query": {
"bool": {
"filter": [
{ "term": { "messageId": "MSG-1013" } },
{ "term": { "Severity": "Info" } }
]
}
},
"sort" : [
{ "documentTimestamp" : {"order" : "desc"}}
],
"size": 10
}
I have an index with some fields, my documents contains valid "category" data also contains "url"(analyzed field) data but not contains respsize..
in the other hand documents that contains "respsize" data (greater than 0) also contains "url" data but not contains "category" data..
I think you got the point, I need join or intersection whatever that a query returns all documents contains respsize and category that have same same url documents.
Here what I did so far;(url field analyzed, rest of them not_analyzed)
here documents that have category:
and other documents have respsize that I need to combine them based on url
I need a dsl query that return records that have same url token(in this scenario it will be www.domainname.com) with merge category and respsize,
I simply want field in second img "category":"27" like in img1 but of course with rest of all fields.
here is my query but not work
GET webproxylog/accesslog/_search
{
"query": {
"filtered": {
"filter" : {
"and" : {
"filters": [
{
"not": {
"filter": {
"terms": {
"category": [
"-",
"-1",
"0"
]
},
"term": {
"respsize": "0"
}
}
},
"term": {
"category": "www.hurriyet.com.tr"
}
}
],
"_cache" : true
}
}
}
},
"sort": [
{
"respsize": {
"order": "desc"
}
}
]
}
You can try the query below. It will require the url field to be the one you specify (i.e. must) and then either of the next two clauses (i.e. should) must be true, i.e. category should be not one of the given terms or the respsize must be greater than 0.
{
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"term": {
"url": "www.hurriyet.com.tr"
}
}
],
"should": [
{
"not": {
"terms": {
"category": [
"-",
"-1",
"0"
]
}
}
},
{
"range": {
"respsize": {
"gt": 0
}
}
}
]
}
}
}
}
}
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.