Someone please help me to add expires_at IS NULL to ES query below. I looked into Dealing with Null Values section for missing filter but the way I used it (shown at the bottom) causes not expired documents not appearing in result so obviously I'm doing something wrong here.
Note: I don't want to use or query because it is deprecated in 2.0.0-beta1.
QUERY
{
"query": {
"filtered": {
"query": {
"bool": {
"must": [
{
"term": {
"order_id": "123"
}
},
{
"term": {
"is_active": 1
}
},
{
"range": {
"expires_at": {
"gt": "2016-07-01T00:00:00+0000"
}
}
}
]
}
}
}
}
}
This is what I'm aiming at:
SELECT * FROM orders
WHERE
order_id = '123' AND
is_active = '1' AND
(expires_at > '2016-07-01T00:00:00+0000' OR expires_at IS NULL)
This is what I did, but un-expired documents won't show up in this case so this is wrong.
{
"query": {
"filtered": {
"filter": {
"missing": {
"field": "expires_at"
}
},
"query": {
"bool": {
"must": [
......
......
]
}
}
}
}
}
My ES version:
{
"status" : 200,
"name" : "Fan Boy",
"version" : {
"number" : "1.3.4",
"build_hash" : "a70f3ccb52200f8f2c87e9c370c6597448eb3e45",
"build_timestamp" : "2014-09-30T09:07:17Z",
"build_snapshot" : false,
"lucene_version" : "4.9"
},
"tagline" : "You Know, for Search"
}
This should do it:
{
"query": {
"filtered": {
"query": {
"bool": {
"must": [
{
"term": {
"order_id": "123"
}
},
{
"term": {
"is_active": 1
}
},
{
"bool": {
"should": [
{
"range": {
"expires_at": {
"gt": "20160101000000"
}
}
},
{
"filtered": {
"filter": {
"missing": {
"field": "expires_at"
}
}
}
}
]
}
}
]
}
}
}
}
}
Related
I have a document that holds data for a product the mapping is as follow:
"mappings" : {
"properties" : {
"view_score" : {
"positive_score_impact" : true,
"type" : "rank_feature"
},
"recipients" : {
"dynamic" : false,
"type" : "nested",
"enabled" : true,
"properties" : {
"type" : {
"similarity" : "boolean",
"type" : "keyword"
},
"title" : {
"type" : "text",
"fields" : {
"key" : {
"type" : "keyword"
}
}
}
}
}
}
}
And I have 2 documents with the following data:
{
"view_score": 10,
"recipients": [{"type":"gender", "title":"male"}, {"type":"gender", "title":"female"}]
}
{
"view_score": 10,
"recipients": [{"type":"gender", "title":"female"}]
}
When a user searches for a product she can say "I prefer products for females" so The products which specifies gender as just female should come before products that specifies gender as male and female both.
I have the following query which gives more score to products with just female gender:
GET _search
{
"sort": [
"_score"
],
"query": {
"script_score": {
"query": {
"bool": {
"should": [
{
"nested": {
"path": "recipients",
"ignore_unmapped": true,
"query": {
"bool": {
"boost": 10,
"must": [
{
"term": {
"recipients.type": "gender"
}
},
{
"match": {
"recipients.title": "female"
}
}
],
"must_not": {
"bool": {
"filter": [
{
"term": {
"recipients.type": "gender"
}
},
{
"match": {
"recipients.title": "male"
}
}
]
}
}
}
}
}
}
]
}
},
"script": {
"source": "return _score;"
}
}
}
}
But if I add another query to should query it won't behave the same and gives the same score to products with one or two genders in their specifications.
here is my final query which wont work as expected:
GET _search
{
"sort": [
"_score"
],
"query": {
"script_score": {
"query": {
"bool": {
"should": [
{
"rank_feature": {
"field": "view_score",
"linear": {}
}
},
{
"nested": {
"path": "recipients",
"ignore_unmapped": true,
"query": {
"bool": {
"boost": 10,
"must": [
{
"term": {
"recipients.type": "gender"
}
},
{
"match": {
"recipients.title": "female"
}
}
],
"must_not": {
"bool": {
"filter": [
{
"term": {
"recipients.type": "gender"
}
},
{
"match": {
"recipients.title": "male"
}
}
]
}
}
}
}
}
}
]
}
},
"script": {
"source": "return _score;"
}
}
}
}
So my problem is how to combine these should clause together to give more weight to the products that specify only one gender.
I have a "date_created_tranx" and "phone_number_cust" fields. Few entries of date_created_tranx are null . I want to have particular phone_number within date_range and with null value.
a = {
"query": {
"bool": {
"must": [
{
"range": {
"date_created_tranx": {
"gte": "2019-12-01",
"lte": "2020-05-07"
}
}
},
{
"regexp": {
"phone_number_cust": ".*702625.*"
}
}
]
}
}
}
b = {
"query": {
"bool": {
"must": [{
"regexp": {
"phone_number_cust": ".*702625.*"
}
}],
"must_not": [{
"exists": {
"field": "date_created_tranx"
}
}
]
}
}
}
How to combine these ??
I cannot call it twice because The result is paginated
I am totally new to elastic search . Any leads will be helpful.
I tried
doc2 = {
"query" :{
"bool" : {
"must":[
a,
b
]
}
}
}
It throws
Error: RequestError: RequestError(400, 'parsing_exception', 'no [query] registered for [query]')
The query you're looking for is this one, i.e.:
We have a constraint on the phone number and we also check that either the date_created_tranx is within bounds or does not exist (i.e. is null).
{
"query": {
"bool": {
"minimum_should_match": 1,
"should": [
{
"range": {
"date_created_tranx": {
"gte": "2019-12-01",
"lte": "2020-05-07"
}
}
},
{
"bool": {
"must_not": {
"exists": {
"field": "date_created_tranx"
}
}
}
}
],
"filter": [
{
"regexp": {
"phone_number_cust": ".*702625.*"
}
}
]
}
}
}
We have some employees and needed to find those we haven't entered their birthday or are born before 3/1/1963:
{
"query": {
"bool": {
"should": [
{
"bool": {
"must_not": [{ "exists": { "field": "birthday" } }]
}
},
{
"bool": {
"filter": [{ "range": {"birthday": { "lte": 19630301 }} }]
}
}
]
}
}
}
We now need to get distinct names...we only want 1 Jason or 1 Susan, etc. How do we apply a distinct filter to the "name" field while still filtering for the birthday as above? I've tried:
{
"query": {
"bool": {
"should": [
{
"bool": {
"must_not": [
{
"exists": {
"field": "birthday"
}
}
]
}
},
{
"bool": {
"filter": [
{
"range": {
"birthday": {
"lte": 19630301
}
}
}
]
}
}
]
}
},
"aggs": {
"uniq_gender": {
"terms": {
"field": "name"
}
}
},
"from": 0,
"size": 25
}
but just get results with duplicate Jasons and Susans. At the bottom it will show me that there are 10 Susans and 12 Jasons. Not sure how to get unique ones.
EDIT:
My mapping is very simple. The name field doesn't need to be keyword...can be text or anything else as it is just a field that just gets returned in the query.
{
"mappings": {
"birthdays": {
"properties": {
"name": {
"type": "keyword"
},
"birthday": {
"type": "date",
"format": "basic_date"
}
}
}
}
}
Without knowing your mapping, I'm guessing that your field name is not analyzed and able to be used on terms aggregation properly.
I suggest you, use filtered aggregation:
{
"aggs": {
"filtered_employes": {
"filter": {
"bool": {
"must": [
{
"bool": {
"must_not": [
{
"exists": {
"field": "birthday"
}
}
]
}
},
{
"range": {
"birthday": {
"lte": 19630301
}
}
}
]
}
},
"aggs": {
"filtered_employes_by_name": {
"terms": {
"field": "name"
}
}
}
}
}
}
In other hand your query is not correct your applying a should bool filter. Change it by must and the aggregation will return only results from employes with (missing birthday) and (born before date).
There are 2 indexes: categories, posts.
categories
name
body
posts
name
body
publish_at
publish_until
I want to do a query on both indexes with a filter on publish_at and publish_until for the posts index.
http://localhost:9200/categories,posts/_search
{
"query": {
"bool": {
"must": {
"multi_match": {
"query": "keyword",
"fields": [
"name^3",
"body"
]
}
},
"filter": [{
"bool": {
"must": [
{
"range": {
"publish_at": {
"lte" : "now"
}
}
},
{
"range": {
"publish_until": {
"gt" : "now"
}
}
}
]
}
}]
}
}
}
This query only gives me posts as results. I also want categories in my results.
How do I apply the date range filters to only indexes with publish_at and publish_until fields and skip the date range filters for the other indexes?
Ok after a day of fiddling with bool I got it working:
{
"query": {
"bool" : {
"must" : [
{
"multi_match": {
"query": "keyword",
"fields": [
"name^3",
"body"
]
}
},
{
"bool": {
"should": [
{
"bool": {
"must": [
{
"range": {
"publish_at": {
"lte" : "now"
}
}
},
{
"range": {
"publish_until": {
"gt" : "now"
}
}
}
]
}
},
{
"bool": {
"must_not": [
{
"exists": {
"field": "publish_at"
}
},
{
"exists": {
"field": "publish_until"
}
}
]
}
}
]
}
}
]
}
}
}
We are using Elasticsearch 1.6 and I have a working three term query that I need to modify with a stand alone working missing filter. Here is the current code:
The original term query with three entries
GET ...
{
"query": {
"nested": {
"path": "MAIN_FIELD",
"query": {
"bool": {
"must": [
{
"term": {
"MAIN_FIELD.ID": 1234
}
},
{
"term": {
"MAIN_FIELD.OTHER_IND": "false"
}
},
{
"term": {
"MAIN_FIELD.INDICATOR": "Y"
}
}
]
}
}
}
}
}
The stand alone missing query:
GET ...
{
"query" : {
"filtered" : {
"filter" : {
"missing" : { "field" : "MAIN_FIELD.OTHER_IND" }
}
}
}
}
How do I change the term query from the first query:
"term": {
"MAIN_FIELD.OTHER_IND": "false"
}
to use a missing filter?
I think what you want is below:
{
"query": {
"nested": {
"path": "MAIN_FIELD",
"query": {
"bool": {
"must": [
{
"term": {
"MAIN_FIELD.ID": 1234
}
},
{
"filtered": {
"filter": {
"missing": {
"field": "MAIN_FIELD.OTHER_IND"
}
}
}
},
{
"term": {
"MAIN_FIELD.INDICATOR": "Y"
}
}
]
}
}
}
}
}