I have an index with optional Date/Time field called lastChackoutDate. Trying to filter rows by range or term query returns 0 rows but I know there are some documents where value for this field exists.
Mappings query returns me an expected answer with:
... ,
"lastCheckoutDate": {
"type": "date"
},
...
Trying to identify what query can return me result I'm waiting for eventually led me to an expression:
{
"from": 0,
"query": {
"bool": {
"filter": [
{
"bool": {
"must_not": [
{
"exists": {
"field": "lastCheckoutDate"
}
}
],
"must": [
{
"nested": {
"path": "nested_path",
"query": {
"term": {
"nested_path.id": {
"value": "some_unique_id"
}
}
}
}
}
]
}
}
]
}
},
"size": 50,
"sort": [
{
"displaySequence": {
"order": "asc"
}
}
]
}
which returned me a single row with existing path/value:
hits
[0]
_source
lastCheckoutDate: 2020-01-23T00:00:00
explain of this query didn't shed a light on "exists" response details: ConstantScore(+ToParentBlockJoinQuery (nested_path.id:some_unique_id) -ConstantScore(_field_names:lastCheckoutDate)), product of:
So are there any ways to determine why field is invisible for query?
This works fine for test database which is being created and dropped each time, but existing storage always gives me 0 hits for any valid (from my POV) query. Ofc I did a migration action for existing database (at least somehow mapping info appeared for a new field).
Elastic documentation shows some examples why "exists" query may fail:
- The field in the source JSON is null or []
- The field has "index" : false set in the mapping
- The length of the field value exceeded an ignore_above setting in the mapping
- The field value was malformed and ignore_malformed was defined in the mapping
But I'm not sure that any option is true for my case.
New documents were added before migration happened. So AFAIK Elastic won't re-index existing documents until they are updated in index.
So that's why on test database I had no issues.
try this
GET /index_name/_search
{
"query": {
"bool": {
"must_not": [
{
"exists": {
"field": "fieldname"
}
}
]
}
}
}
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.
I'm working on a dataset in Elasticsearch 7.6 where one field (published_at) is conditionally set. We're migrating to a new field (published) which will either be True or False, but I need to support backwards compatibility and can't backfill the dataset for all documents. Where i've landed is needing a query to check if the published_at field exists, or if published is set to True.
Here's where i've gotten so far, but this is instead giving me all documents:
{
"query": {
"bool": {
"should": [
{"exists": {"field": "published_at"}},
{
"terms": {
"published": [
"true"
]
}
}
]
}
}
}
I'm using Elasticsearch with the python library and I have a problem using the search query when the object become a little bit complex. I have objects build like that in my index:
{
"id" : 120,
"name": bob,
"shared_status": {
"post_id": 123456789,
"text": "This is a sample",
"urls" : [
{
"url": "http://test.1.com",
"displayed_url": "test.1.com"
},
{
"url": "http://blabla.com",
"displayed_url": "blabla.com"
}
]
}
}
Now I want to do a query that will return me this document only if in one of the displayed URL's a substring "test" and there is a field "text" in the main document. So I did this query:
{
"query": {
"bool": {
"must": [
{"exists": {"field": "text"}}
]
}
}
}
}
But I don't know what query to add for the part: one of the displayed URL's a substring "test"
Is that posssible? How does the iteration on the list works?
If you didn't define an explicit mapping for your schema, elasticsearch creates a default mapping based on the data input.
urls will be of type object
displayed_url will be of type string and using standard analyzer
As you don't need any association between url and displayed_url, the current schema will work fine.
You can use a match query for full text match
GET _search
{
"query": {
"bool": {
"must": [
{
"exists": {
"field": "text"
}
},
{
"match": {
"urls.displayed_url": "test"
}
}
]
}
}
}
Per our requirement we need to find the max ID of the document before adding new document. Problem here is doc may contain string data also So had to use inline script on the elastic query to find out max id only for the document which has integer data otherwise returning 0. am using following inline script query to find max-key but not working. can you help me onthis ?.
{
"size":0,
"query":
{"bool":
{"filter":[
{"term":
{"Name":
{
"value":"Test2"
}
}}
]
}},
"aggs":{
"MaxId":{
"max":{
"field":"Key","script":{
"inline":"((doc['Key'].value).isNumber()) ? Integer.parseInt(doc['Key'].value) : 0"}}
}
}
}
The error is because the max aggregation only supports numeric fields, i.e. you cannot specify a string field (i.e. Key) in a max aggregation.
Simply remove the "field":"Key" part and only keep the script part
{
"size": 0,
"query": {
"bool": {
"filter": [
{
"term": {
"Name": "Test2"
}
}
]
}
},
"aggs": {
"MaxId": {
"max": {
"script": {
"source": "((doc['Key'].value).isNumber()) ? Integer.parseInt(doc['Key'].value) : 0"
}
}
}
}
}
I have a query that works fine when I need the property of a document
to match just one value.
However I also need to be able to search with must with two values.
So if a banana has id 1 and a lemon has id 2 and I search for yellow
I will get both if I have 1 and 2 in the must clause.
But if i have just 1 I will only get the banana.
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [
{ "match":
{ "fruit.color": "yellow" }}
],
"must" : [
{ "match": { "fruit.id" : "1" } }
]
}
}
}
I haven´t found a way to search with two values with must.
is that possible?
If the document "must" be returned only if the id is 1 or 2, that sounds like another should clause. If I'm understanding your question properly, you want documents with either id 1 OR id 2. Additionally, if the color is yellow, give it a higher score.
Here's one way you might achieve what you're looking for:
{
"query": {
"bool": {
"should": {
"match": {
"fruit.color": "yellow"
}
},
"must": {
"bool": {
"should": [
{
"match": {
"fruit.id": "1"
}
},
{
"match": {
"fruit.id": "2"
}
}
]
}
}
}
}
}
Here I put the two match queries in the should clause of a separate bool query. This achieves the OR behavior you are looking for.
Have another look at the Bool Query documentation and take note of the nuances of should. It behaves differently by default depending on whether or not there is a sibling must clause and whether or not the bool query is being executed in filter context.
Another key option that is adjustable and can help you achieve your expected results is the minimum_should_match parameter. Have a look at this documentation page.
Instead of a match query, you could simply try the terms query for ORing between multiple terms.
Match queries are generally used for analyzed fields. For exact matching, you should use term queries
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [
{ "match": { "fruit.color": "yellow" } }
],
"must" : [
{ "terms": { "fruit.id": ["1","2"] } }
]
}
}
}
term or terms query is the perfect way to fetch the exact text or id, using match query result in search inside the id or text
Ex:
id = '4'
id = '44'
Search using match query with id = 4 return both 4 & 44 since it matches 4 in both. This is where terms query come into play.
same search using terms query will return 4 only.
So the accepted is absolutely wrong. Use the #Rahul answer. Just one more thing you need to do, Instead of text you need to analyse the field as a keyword
Example for indexing a field both as a text and keyword (mapping is for flat level for nested change it accordingly).
{
"index_patterns": [ "test" ],
"mappings": {
"kb_mapping_doc": {
"_source": {
"enabled": true
},
"properties": {
"id": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword"
}
}
}
}
}
}
}
using #Rahul's answer doesn't worked because you might be analysed as a text.
id - access a text field
id.keyword - access a keyword field
it would be
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [{
"match": {
"color": "yellow"
}
}],
"must": [{
"terms": {
"id.keyword": ["1", "2"]
}
}]
}
}
}
So I would say accepted answer will return falsy results Please use #Rahul's answer with the corresponding mapping.