My documents in Elasticsearch index have following format:
{
timestamp: "123456789",
tags: [
{ key:"tag1", "value": "val1" }, ...
]
}
I want get all documents which contain for example { key:"tag1" } and { key:"tag2", "value": "val2" } in their tags field.
How can I do this?
You can try with a bool query, where you specify how many nested query you need in the must section:
GET test_nested/test/_search
{
"query": {
"bool": {
"must": [
{"nested" : {
"path" : "tags",
"query" : {
"bool" : {
"must" : [
{ "match" : {"tags.key" : "tag1"} }
]
}
}
}},
{"nested" : {
"path" : "tags",
"query" : {
"bool" : {
"must" : [
{ "match" : {"tags.key" : "tag2"} },
{ "match" : {"tags.value" : "val2"} }
]
}
}
}}
]
}
}
}
In this case i have one nested query for selecting all documents with key "tag1" and the second nested query to select all documents with the "tag2" and "value2".
Related
I've got an index similar to the example index shown in the elasticsearch doc multi-level nested query example:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-nested-query.html#multi-level-nested-query-ex
Given these example docs:
{
"driver" : {
"last_name" : "McQueen",
"vehicle" : [
{
"make" : "Powell Motors",
"model" : "Canyonero"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
{
"driver" : {
"last_name" : "Hudson",
"vehicle" : [
{
"make" : "Mifune",
"model" : "Mach Five"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
I need to be able to find documents where the driver.vehicle.make matches two values, i.e. the driver who has both vehicle makes "Powell Motors" and "Miller-meteor" should match McQueen but not Hudson.
I've tried a query similar to the doc example's make and model query, but it returns 0 docs:
{
"query": {
"nested": {
"path": "driver",
"query": {
"nested": {
"path": "driver.vehicle",
"query": {
"bool": {
"must": [
{ "match": { "driver.vehicle.make": "Powell Motors" } },
{ "match": { "driver.vehicle.make": "Miller-Meteor" } }
]
}
}
}
}
}
}
}
Changing the "must" to a "should" returns both docs. I can't seem to find a query that will query the vehicle array for multiple value matches in the same doc.
The above query returns 0 documents, as there is no single document (inside driver.vehicle) in your example that has driver.vehicle.make value as "Powell Motors" and "Miller-meteor".
Note: Here single documents refer to each individual documents (or objects) inside driver.vehicle.
Therefore, when you are changing the must clause to should clause it returns those documents (in this case both the doc), that have driver.vehicle.make value as "Powell Motors" OR "Miller-meteor". must works as logical AND operator, and should works as logical OR operator.
According to your requirement, I believe you want those documents where driver who has vehicle makes "Powell Motors" OR "Miller-meteor" should match McQueen but not Hudson.
In this case, you need to combine a nested query with a normal query, which can be done using a bool query.
Your modified query will be
{
"query": {
"nested": {
"path": "driver",
"query": {
"bool": {
"must": [
{
"match": {
"driver.last_name": "McQueen"
}
},
{
"nested": {
"path": "driver.vehicle",
"query": {
"bool": {
"should": [
{
"match": {
"driver.vehicle.make": "Powell Motors"
}
},
{
"match": {
"driver.vehicle.make": "Miller-Meteor"
}
}
]
}
}
}
}
]
}
}
}
}
}
And the search result will be
"hits" : [
{
"_index" : "soidx1",
"_type" : "_doc",
"_id" : "1",
"_score" : 3.105637,
"_source" : {
"driver" : {
"last_name" : "McQueen",
"vehicle" : [
{
"make" : "Powell Motors",
"model" : "Canyonero"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
}
]
I have the following data index in Elasticsearch with the following syntax:
PUT /try1
{
"mappings" : {
"product" : {
"properties" : {
"name": { "type" : "text" },
"categories": {
"type": "nested",
"properties": {
"range":{"type":"text"}
}
}
}
}
}
}
The range type has an array of words:["high","medium","low"]
I need to access the range element inside the nested category. I tried using the following syntax:
GET /try1/product/_search
{
"query": {
"nested" : {
"path" : "categories",
"query" : {
"bool" : {
"must" : [
{ "match" : {"categories.range": "low"} }
]
}
}
}
}
}
However, I am getting an error with the message:
"reason": """failed to create query:...
Can someone please offer a solution to this?
#KGB can you try to make your query slightly differently like this:
{
"query": {
"bool": {
"must": [
{
"match": {
"categories.range": "low"
}
}
]
}
}
}
{
"query": {
"nested" : {
"path" : "categories",
"query" : {
"bool" : {
"must" : [
{ categories.range": "low"}
]
}
}
}
}
}
This worked perfectly
How can I search for documents that have all of the specified tags in the following query? I tried minimum_should_match and "execution": "and", but none of them is supported in my query.
GET products/fashion/_search
{
"query": {
"constant_score": {
"filter" : {
"bool" : {
"must" : [
{"terms" : {
"tags" : ["gucci", "dresses"]
}},
{"range" : {
"price.value" : {
"gte" : 100,
"lt" : 1000
}
}}
]
}
}
}
},
"sort": { "date": { "order": "desc" }}
}
====== UPDATE
I found a way to build my queries. The task was to reproduce the following mongodb query in the elasticsearch:
{
"tags": {
"$all":["gucci","dresses"]
},
"price.value":{"$gte":100,"$lte":1000}
}
And here is my elasticsearch query
GET products/fashion/_search
{
"query": {
"bool" : {
"filter" : [
{"term" : {
"tags" : "gucci"
}},
{"term" : {
"tags" : "dresses"
}},
{"range" : {
"price.value" : {
"gte" : 100,
"lt" : 1000
}
}}
]
}
}
}
Do you have a mapping defined for your index? By default, Elasticsearch will analyze string fields. If you want to find exact terms like you are above, you need to specify them as not_analyzed in the mapping.
https://www.elastic.co/guide/en/elasticsearch/guide/current/_finding_exact_values.html#_term_filter_with_text
Hi I want to achieve this in Elasticsearch.
select * from products where brandName = Accu or brandName = Perfor AND cat=lube(any where in any filed of an elastic search ).
I am using this query in Elasticsearch.
{
"bool": {
"must": {
"query_string": {
"query": "oil"
}
},
"should": [
{
"term": {
"BrandName": "Accu"
}
},
{
"term": {
"BrandName": "Perfor"
}
}
]
}
}
By this query m not getting the combination exact results.
You need to add minimum_should_match: 1 to your query and probably use match instead of term if your BrandName field is an analyzed string.
{
"bool" : {
"must" : {
"query_string" : {
"query" : "oil OR lube OR lubricate"
}
},
"minimum_should_match": 1, <---- add this
"should" : [ {
"match" : {
"BrandName" : "Accu"
}
}, {
"match" : {
"BrandName" : "Perfor"
}
} ]
}
}
This query satisfy your condition.
{
"bool" : {
"must" : { "term" : { "cat" : "lube" } },
"should" : [
{ "term" : { "BrandName" : "Accu" } },
{ "term" : { "BrandName" : "Perfor" } }
],
"minimum_should_match" : 1
}
}
I need to modify this query so that elastic search does not give it a score. I want my custom filter score to be the only thing giving any result a score. How do I accomplish this?
Each record should only every have a score of 0, 100, or 1000.
{
"size":50,
"from":0,
"query" : {
"custom_filters_score" : {
"query" : {
"filtered" : {
"query" : {
"bool" : {
"must" : [
{"term":{"type":"alpha"}},
{"field":{"sector":"exists"}},
{"field":{"sector.sub":"exists"}},
{"field":{"alpha_sector.sub.categories":"second"}},
{"field":{"beta_sector.sub.columns":"first"}},
{"term":{"beta_type":"beta"}},
{"term":{"area":"624"}}
]
}
},
"filter" : {
"or" : [
{
"and" : [
{"term":{"area":"624"}},
{"term":{"start":"07242013"}}
]
},
{
"and" : [
{"term":{"area":"624"}},
{"term":{"start":"blank"}}
]
}
]
}
}
},
"filters" : [
{"filter":{"term":{"resource":5726}}, "boost":"1000"},
{"filter":{"term":{"alpha_resource":5726}}, "boost":"100"}
],
"score_mode":"sum"
}
}
}
I am not quite sure what you are trying to achieve here
{"field":{"sector":"exists"}},
{"field":{"sector.sub":"exists"}},
but in general, if you don't want part of your query to affect the score, just make it a filter. It's also will be better to use "bool" with "term" filters instead of "and"/"or"/"not"
{
"size":50,
"from":0,
"query" : {
"custom_filters_score" : {
"query" : {
"filtered" : {
"query" : {
"match_all": {}
},
"filter" : {
"bool" : {
"must" : [
{"term":{"type":"alpha"}},
{"query":{"field":{"sector":"exists"}}},
{"query":{"field":{"sector.sub":"exists"}}},
{"query":{"field":{"alpha_sector.sub.categories":"second"}}},
{"query":{"field":{"beta_sector.sub.columns":"first"}}},
{"term":{"beta_type":"beta"}},
{"term":{"area":"624"}}
],
"should" : [
{
"bool" : {
"must" : [
{"term":{"area":"624"}},
{"term":{"start":"07242013"}}
]
}
},
{
"bool" : {
"must": [
{"term":{"area":"624"}},
{"term":{"start":"blank"}}
]
}
}
]
}
}
}
},
"filters" : [
{"filter":{"term":{"resource":5726}}, "boost":"1000"},
{"filter":{"term":{"alpha_resource":5726}}, "boost":"100"}
],
"score_mode":"total"
}
}
}