How to filter results from wildcard query with geolocation? My query look like this
{
"query": {
"bool" : {
"should": [
{
"wildcard": {
"title": {
"value": "*football*"
}
}
},
{
"wildcard": {
"description": {
"value": "*football*"
}
}
}
],
"filter" : {
"geo_distance" : {
"distance" : "90km",
"geolocation" : "45.50, 40.10"
}
}
}
}
}
But query always return results by geo_distance, like to skip wildcard params. I want to return only results where distance is max 90km but which contains "football" in title or description...
All you need to do is to add minimum_should_match: 1 in your query:
{
"query": {
"bool" : {
"minimum_should_match": 1, <-- add this
"should": [
{
"wildcard": {
"title": {
"value": "*football*"
}
}
},
{
"wildcard": {
"description": {
"value": "*football*"
}
}
}
],
"filter" : {
"geo_distance" : {
"distance" : "90km",
"geolocation" : "45.50, 40.10"
}
}
}
}
}
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 huge nested object which has lots of levels
i want to create a query which will return only the leaf / some object in the middle,
and the query is supposed to query multiple levels in the tree.
for example:
my DB is saving the whole company structure.
company -> wards -> employees -> working hours
i want to make a query that will return only the working hours of the employees in ward 2 which started later than 3pm this month
i tried to use inner_hits - but to no use.
as requested, sample document and expected result:
company:[{
properties:{companyId: 112}
ward:[{
properties: {wardId: 223}
employee:{
properties: {employeeId: 334},
workingHours: [
{ date: "1.1.2021", numOfHours: 4},
{ date: "1.2.2021", numOfHours: 7}
]
}]
}]
}]
the query:
I need to return the working hours of date "1.2.21" , of employee 334, of ward 223. and only the working hours, not the whole tree.
expected result:
4 or { date: "1.1.2021", numOfHours: 4} , whatever is simpler
hope its clear now
You need to add inner_hits to all nested queries
You can either parse entire result to get matched working hours(from inner hits) o can use response filtering to remove additional data
Mapping
PUT index123
{
"mappings": {
"properties": {
"company": {
"type": "nested",
"properties": {
"ward": {
"type": "nested",
"properties": {
"employee": {
"type": "nested",
"properties": {
"workingHours": {
"type": "nested",
"properties": {
"date": {
"type": "date"
}
}
}
}
}
}
}
}
}
}
}
}
Data
"_index" : "index123",
"_type" : "_doc",
"_id" : "9gGYI3oBt-MOenya6BcN",
"_score" : 1.0,
"_source" : {
"company" : [
{
"companyId" : 112,
"ward" : [
{
"wardId" : 223,
"employee" : {
"employeeId" : 334,
"workingHours" : [
{
"date" : "2021-01-01",
"numOfHours" : 4
},
{
"date" : "2021-01-02",
"numOfHours" : 7
}
]
}
}
]
}
]
}
}
Query
GET index123/_search?filter_path=hits.hits.inner_hits.ward.hits.hits.inner_hits.employee.hits.hits.inner_hits.workingHours.hits.hits._source
{
"query": {
"nested": {
"inner_hits": {
"name":"ward"
},
"path": "company.ward",
"query": {
"bool": {
"must": [
{
"term": {
"company.ward.wardId": {
"value": 223
}
}
},
{
"nested": {
"inner_hits": {
"name":"employee"
},
"path": "company.ward.employee",
"query": {
"bool": {
"must": [
{
"term": {
"company.ward.employee.employeeId": {
"value":334
}
}
},
{
"nested": {
"inner_hits": {
"name":"workingHours"
},
"path": "company.ward.employee.workingHours",
"query": {
"range": {
"company.ward.employee.workingHours.date": {
"gte": "2021-01-01",
"lte": "2021-01-01"
}
}
}
}
}
]
}
}
}
}
]
}
}
}
}
}
Result
{
"hits" : {
"hits" : [
{
"inner_hits" : {
"ward" : {
"hits" : {
"hits" : [
{
"inner_hits" : {
"employee" : {
"hits" : {
"hits" : [
{
"inner_hits" : {
"workingHours" : {
"hits" : {
"hits" : [
{
"_source" : {
"date" : "2021-01-01",
"numOfHours" : 4
}
}
]
}
}
}
}
]
}
}
}
}
]
}
}
}
}
]
}
}
Update:
Query with company ID
GET index123/_search?filter_path=hits.hits.inner_hits.company.hits.hits.inner_hits.ward.hits.hits.inner_hits.employee.hits.hits.inner_hits.workingHours.hits.hits._source
{
"query": {
"nested": {
"path": "company",
"inner_hits": {
"name": "company"
},
"query": {
"bool": {
"must": [
{
"term": {
"company.companyId": {
"value": 112
}
}
},
{
"nested": {
"inner_hits": {
"name": "ward"
},
"path": "company.ward",
"query": {
"bool": {
"must": [
{
"term": {
"company.ward.wardId": {
"value": 223
}
}
},
{
"nested": {
"inner_hits": {
"name": "employee"
},
"path": "company.ward.employee",
"query": {
"bool": {
"must": [
{
"term": {
"company.ward.employee.employeeId": {
"value": 334
}
}
},
{
"nested": {
"inner_hits": {
"name": "workingHours"
},
"path": "company.ward.employee.workingHours",
"query": {
"range": {
"company.ward.employee.workingHours.date": {
"gte": "2021-01-01",
"lte": "2021-01-01"
}
}
}
}
}
]
}
}
}
}
]
}
}
}
}
]
}
}
}
}
}
In https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-filter-aggregation.html we learn:
{
"aggs" : {
"t_shirts" : {
"filter" : { "term": { "type": "t-shirt" } }
}
}
}
The above code show how we can aggs for t-shirt, but how do we do:
{
"aggs" : {
"t_shirts_or_shorts" : {
"filter" : { "term": { "type": "t-shirt" } OR "term": { "type": "shorts" } }
}
}
}
and
{
"aggs" : {
"black_t_shirts" : {
"filter" : { "term": { "type": "t-shirt" } AND "term": { "color": "black" } }
}
}
}
You can use "must" and should clause in filter aggregation same as in query.
Query1:
{
"size": 0,
"aggs": {
"t_shirts": {
"filter": {
"bool": {
"should": [
{
"term": {
"type.keyword": "t-shirt"
}
},
{
"term": {
"type.keyword": "shorts"
}
}
]
}
}
}
}
}
Query2:
{
"size": 0,
"aggs": {
"t_shirts": {
"filter": {
"bool": {
"must": [
{
"term": {
"type.keyword": "t-shirt"
}
},
{
"term": {
"color.keyword": "black"
}
}
]
}
}
}
}
}
You can combine filter criteria using the bool tag, much like you can query clauses.
You can also check this: Multiple filters and an aggregate in elasticsearch
I need little help with transfering mysql query to ES. The query looks like this
SELECT * FROM `xyz` WHERE visibility IN (1,2) AND (active=0 OR (active=1 AND finished=1)
It's easy, to make only AND conditions, but how to mix AND with OR in term?
"query" : {
"bool" : {
"must" : [{
"terms" : { "visibility" : ["1", "2"] }
}, {
"term" : { "active" : "1" }
}, {
"term" : { "active" : "0", "finished" : "1" } // OR
},]
}
}
Try like this by nesting a bool/should and bool/filter query inside the main bool/filter query:
{
"query": {
"bool": {
"filter": [
{
"terms": {
"visibility": [
"1",
"2"
]
}
},
{
"bool": {
"should": [
{
"term": {
"active": "0"
}
},
{
"bool": {
"filter": [
{
"term": {
"active": "1"
}
},
{
"term": {
"finished": "1"
}
}
]
}
}
]
}
}
]
}
}
}
I have a list, array or whichever language you are familiar. E.g. names : ["John","Bas","Peter"] and I want to query the name field if it matches one of those names.
One way is with OR Filter. e.g.
{
"filtered" : {
"query" : {
"match_all": {}
},
"filter" : {
"or" : [
{
"term" : { "name" : "John" }
},
{
"term" : { "name" : "Bas" }
},
{
"term" : { "name" : "Peter" }
}
]
}
}
}
Any fancier way? Better if it's a query than a filter.
{
"query": {
"filtered" : {
"filter" : {
"terms": {
"name": ["John","Bas","Peter"]
}
}
}
}
}
Which Elasticsearch rewrites as if you hat used this one
{
"query": {
"filtered" : {
"filter" : {
"bool": {
"should": [
{
"term": {
"name": "John"
}
},
{
"term": {
"name": "Bas"
}
},
{
"term": {
"name": "Peter"
}
}
]
}
}
}
}
}
When using a boolean filter, most of the time, it is better to use the bool filter than and or or. The reason is explained on the Elasticsearch blog: http://www.elasticsearch.org/blog/all-about-elasticsearch-filter-bitsets/
As I tried the filtered query I got no [query] registered for [filtered], based on answer here it seems the filtered query has been deprecated and removed in ES 5.0. So I provide using:
{
"query": {
"bool": {
"filter": {
"terms": {
"name": ["John","Bas","Peter"]
}
}
}
}
}
example query = filter by keyword and a list of values
{
"query": {
"bool": {
"must": [
{
"term": {
"fguid": "9bbfe844-44ad-4626-a6a5-ea4bad3a7bfb.pdf"
}
}
],
"filter": {
"terms": {
"page": [
"1",
"2",
"3"
]
}
}
}
}
}