Elasticsearch aggregation over children document field values - elasticsearch

I'm facing the following problem of selecting and sorting parent documents based on an aggregated value over its children documents. The aggregation (e.g. sum) itself depends on a query string, i.e. which children documents are relevant for the aggregation.
Example: Given the documents basket A and basket B, for each basket document, I am looking to sum over the number field of its fruit children if the name field matches my query, e.g. apples.
PUT /baskets/_doc/0
{
"name": "basket A",
"fruit": [
{
"name": "apples",
"number": 2
},
{
"name": "oranges",
"number": 3
}
]
}
PUT /baskets/_doc/1
{
"name": "basket B",
"fruit": [
{
"name": "apples",
"number": 3
},
{
"name": "apples",
"number": 3
}
]
}
Mappings:
PUT /baskets
{
"mappings": {
"properties": {
"name": { "type": "text" },
"fruit": {
"type": "nested",
"properties": {
"name": { "type": "text" },
"number": { "type": "long" }
}
}
}
}
}
Use case 1: Which basket has (strictly) more than 5 apples? Would expect only basket B
Use case 2: Sort baskets by number of apples. Would expect basket B with a total of 6 apples, then basket A with a total of 2 apples.
How can one implement this using the Elasticsearch (7.8.0) query DSL?
I have tried so far with nested queries and aggregations without success.
Thanks!
Edit: Added mappings
Edit: Updated the numbers to better reflect the problem
*Edit: Added possible answer to Use case 2 (see comments to the answer from #joe):
GET /profiles/_search
{
"aggs": {
"aggs_baskets": {
"terms": {
"field": "name",
"order": {"nest > fruit_filter > fruit_sum": "desc"}
},
"aggs": {
"nest":{
"nested":{
"path": "fruit"
},
"aggs":{
"fruit_filter":{
"filter": {
"term": {"fruit.name": "apple"}
},
"aggs":{
"fruit_sum":{
"sum": {"field": "fruit.number"}
}
}
}
}
}
}
}
}
}

Use case 1:
GET baskets/_search
{
"query": {
"nested": {
"path": "fruit",
"inner_hits": {},
"query": {
"bool": {
"must": [
{
"term": {
"fruit.name": {
"value": "apples"
}
}
},
{
"range": {
"fruit.number": {
"gte": 5
}
}
}
]
}
}
}
}
}
Strictly more than 5 --> gt; >=5 --> gte.
Also notice the inner_hits part -- this gives you the actual nested subdocument which caused this particular basket to match the query. It's not required but good-to-know.
Use case 2:
GET baskets/_search
{
"sort": [
{
"fruit.number": {
"nested_path": "fruit",
"order": "desc"
}
}
]
}
Use case 2 Edit:
There are probably cleaner ways of doing this but I'd go with the following:
GET baskets/_search
{
"size": 0,
"aggs": {
"multiply_and_add": {
"scripted_metric": {
"params": {
"only_fruit_name": "apples"
},
"init_script": "state.by_basket_name = [:]",
"map_script": """
def basket_name = params._source['name'];
def fruits = params._source['fruit'].findAll(group -> group.name == params.only_fruit_name);
for (def fruit_group : fruits) {
def number = fruit_group.number;
if (state.by_basket_name.containsKey(basket_name)) {
state.by_basket_name[basket_name] += number;
} else {
state.by_basket_name[basket_name] = number;
}
}
""",
"combine_script": "return state.by_basket_name",
"reduce_script": "return states"
}
}
}
}
yielding a hash map along the lines of
{
...
"aggregations":{
"multiply_and_add":{
"value":[
{
"basket A":2,
"basket B":6
}
]
}
}
}
Sorting can either be done in the reduce_script or within your ES response post-processing pipeline. You could of course choose to go w/ (sorted) lists and lambdas...
Notice the required nested_path.

After a while of searching and testing, here are (in addition to #joe's answer to use case 2) possible queries for both use cases. Note that both use cases require to change the mapping for the field name to be of type keyword.
Use case 1: Which basket has (strictly) more than 5 apples? Would expect only basket B
For more information on filtering results by their aggregation value see Bucket Selectors
GET /baskets/_search
{
"aggs": {
"aggs_baskets": {
"terms": {
"field": "name"
},
"aggs": {
"nest":{
"nested":{
"path": "fruit"
},
"aggs":{
"fruit_filter":{
"filter": {
"match": {"fruit.name": "apples"}
},
"aggs":{
"fruit_sum":{
"sum": {"field": "fruit.number"}
}
}
}
}
},
"basket_sum_filter":{
"bucket_selector":{
"buckets_path":{
"fruitSum":"nest > fruit_filter > fruit_sum"
},
"script":"params.fruitSum > 5"
}
}
}
}
}
}
... yielding
...,
"buckets": [
{
"key": "basket B",
"doc_count": 1,
"nest": {
"doc_count": 2,
"fruit_filter": {
"doc_count": 2,
"fruit_sum": {
"value": 6
}
}
}
}
]
Use case 2: Sort baskets by number of apples. Would expect basket B with a total of 6 apples, then basket A with a total of 2 apples.
GET /baskets/_search
{
"aggs": {
"aggs_baskets": {
"terms": {
"field": "name",
"order": {"nest > fruit_filter > fruit_sum": "desc"}
},
"aggs": {
"nest":{
"nested":{
"path": "fruit"
},
"aggs":{
"fruit_filter":{
"filter": {
"term": {"fruit.name": "apple"}
},
"aggs":{
"fruit_sum":{
"sum": {"field": "fruit.number"}
}
}
}
}
}
}
}
}
}
... yielding
...,
"buckets": [
{
"key": "basket B",
"doc_count": 1,
"nest": {
"doc_count": 2,
"fruit_filter": {
"doc_count": 2,
"fruit_sum": {
"value": 6
}
}
}
},
{
"key": "basket A",
"doc_count": 1,
"nest": {
"doc_count": 2,
"fruit_filter": {
"doc_count": 1,
"fruit_sum": {
"value": 2
}
}
}
}
]

Related

Nested array of objects aggregation in Elasticsearch

Documents in the Elasticsearch are indexed as such
Document 1
{
"task_completed": 10
"tagged_object": [
{
"category": "cat",
"count": 10
},
{
"category": "cars",
"count": 20
}
]
}
Document 2
{
"task_completed": 50
"tagged_object": [
{
"category": "cars",
"count": 100
},
{
"category": "dog",
"count": 5
}
]
}
As you can see that the value of the category key is dynamic in nature. I want to perform a similar aggregation like in SQL with the group by category and return the sum of the count of each category.
In the above example, the aggregation should return
cat: 10,
cars: 120 and
dog: 5
Wanted to know how to write this aggregation query in Elasticsearch if it is possible. Thanks in advance.
You can achieve your required result, using nested, terms, and sum aggregation.
Adding a working example with index mapping, search query and search result
Index Mapping:
{
"mappings": {
"properties": {
"tagged_object": {
"type": "nested"
}
}
}
}
Search Query:
{
"size": 0,
"aggs": {
"resellers": {
"nested": {
"path": "tagged_object"
},
"aggs": {
"books": {
"terms": {
"field": "tagged_object.category.keyword"
},
"aggs":{
"sum_of_count":{
"sum":{
"field":"tagged_object.count"
}
}
}
}
}
}
}
}
Search Result:
"aggregations": {
"resellers": {
"doc_count": 4,
"books": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "cars",
"doc_count": 2,
"sum_of_count": {
"value": 120.0
}
},
{
"key": "cat",
"doc_count": 1,
"sum_of_count": {
"value": 10.0
}
},
{
"key": "dog",
"doc_count": 1,
"sum_of_count": {
"value": 5.0
}
}
]
}
}
}

Stats Aggregation with Min Mode in ElasticSearch

I have the below mapping in ElasticSearch
{
"properties":{
"Costs":{
"type":"nested",
"properties":{
"price":{
"type":"integer"
}
}
}
}
}
So every document has an Array field Costs, which contains many elements and each element has price in it. I want to find the min and max price with the condition being - that from each array the element with the minimum price should be considered. So it is basically min/max among the minimum value of each array.
Lets say I have 2 documents with the Costs field as
Costs: [
{
"price": 100,
},
{
"price": 200,
}
]
and
Costs: [
{
"price": 300,
},
{
"price": 400,
}
]
So I need to find the stats
This is the query I am currently using
{
"costs_stats":{
"nested":{
"path":"Costs"
},
"aggs":{
"price_stats_new":{
"stats":{
"field":"Costs.price"
}
}
}
}
}
And it gives me this:
"min" : 100,
"max" : 400
But I need to find stats after taking minimum elements of each array for consideration.
So this is what i need:
"min" : 100,
"max" : 300
Like we have a "mode" option in sort, is there something similar in stats aggregation also, or any other way of achieving this, maybe using a script or something. Please suggest. I am really stuck here.
Let me know if anything is required
Update 1:
Query for finding min/max among minimums
{
"_source":false,
"timeout":"5s",
"from":0,
"size":0,
"aggs":{
"price_1":{
"terms":{
"field":"id"
},
"aggs":{
"price_2":{
"nested":{
"path":"Costs"
},
"aggs":{
"filtered":{
"aggs":{
"price_3":{
"min":{
"field":"Costs.price"
}
}
},
"filter":{
"bool":{
"filter":{
"range":{
"Costs.price":{
"gte":100
}
}
}
}
}
}
}
}
}
},
"minValue":{
"min_bucket":{
"buckets_path":"price_1>price_2>filtered>price_3"
}
}
}
}
Only few buckets are coming and hence the min/max is coming among those, which is not correct. Is there any size limit.
One way to achieve your use case is to add one more field id, in each document. With the help of id field terms aggregation can be performed, and so buckets will be dynamically built - one per unique value.
Then, we can apply min aggregation, which will return the minimum value among numeric values extracted from the aggregated documents.
Adding a working example with index data, mapping, search query, and search result
Index Mapping:
{
"mappings": {
"properties": {
"Costs": {
"type": "nested"
}
}
}
}
Index Data:
{
"id":1,
"Costs": [
{
"price": 100
},
{
"price": 200
}
]
}
{
"id":2,
"Costs": [
{
"price": 300
},
{
"price": 400
}
]
}
Search Query:
{
"size": 0,
"aggs": {
"id_terms": {
"terms": {
"field": "id",
"size": 15 <-- note this
},
"aggs": {
"nested_entries": {
"nested": {
"path": "Costs"
},
"aggs": {
"min_position": {
"min": {
"field": "Costs.price"
}
}
}
}
}
}
}
}
Search Result:
"aggregations": {
"id_terms": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 1,
"doc_count": 1,
"nested_entries": {
"doc_count": 2,
"min_position": {
"value": 100.0
}
}
},
{
"key": 2,
"doc_count": 1,
"nested_entries": {
"doc_count": 2,
"min_position": {
"value": 300.0
}
}
}
]
}
Using stats aggregation also, it can be achieved (if you add one more field id that uniquely identifies your document)
{
"size": 0,
"aggs": {
"id_terms": {
"terms": {
"field": "id",
"size": 15 <-- note this
},
"aggs": {
"costs_stats": {
"nested": {
"path": "Costs"
},
"aggs": {
"price_stats_new": {
"stats": {
"field": "Costs.price"
}
}
}
}
}
}
}
}
Update 1:
To find the maximum value among those minimums (as seen in the above query), you can use max bucket aggregation
{
"size": 0,
"aggs": {
"id_terms": {
"terms": {
"field": "id",
"size": 15 <-- note this
},
"aggs": {
"nested_entries": {
"nested": {
"path": "Costs"
},
"aggs": {
"min_position": {
"min": {
"field": "Costs.price"
}
}
}
}
}
},
"maxValue": {
"max_bucket": {
"buckets_path": "id_terms>nested_entries>min_position"
}
}
}
}
Search Result:
"aggregations": {
"id_terms": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": 1,
"doc_count": 1,
"nested_entries": {
"doc_count": 2,
"min_position": {
"value": 100.0
}
}
},
{
"key": 2,
"doc_count": 1,
"nested_entries": {
"doc_count": 2,
"min_position": {
"value": 300.0
}
}
}
]
},
"maxValue": {
"value": 300.0,
"keys": [
"2"
]
}
}

ElasticSearch aggregation query with List in documents

I have following records of car sales of different brands in different cities.
Document -1
{
"city": "Delhi",
"cars":[{
"name":"Toyota",
"purchase":100,
"sold":80
},{
"name":"Honda",
"purchase":200,
"sold":150
}]
}
Document -2
{
"city": "Delhi",
"cars":[{
"name":"Toyota",
"purchase":50,
"sold":40
},{
"name":"Honda",
"purchase":150,
"sold":120
}]
}
I am trying to come up with query to aggregate car statistics for a given city but not getting the right query.
Required result:
{
"city": "Delhi",
"cars":[{
"name":"Toyota",
"purchase":150,
"sold":120
},{
"name":"Honda",
"purchase":350,
"sold":270
}]
}
First you need to map your array as a nested field (script would be complicated and not performant). Nested field are indexed, aggregation will be pretty fast.
remove your index / or create a new one. Please note i use test as type.
{
"mappings": {
"test": {
"properties": {
"city": {
"type": "keyword"
},
"cars": {
"type": "nested",
"properties": {
"name": {
"type": "keyword"
},
"purchase": {
"type": "integer"
},
"sold": {
"type": "integer"
}
}
}
}
}
}
}
Index your document (same way you did)
For the aggregation:
{
"size": 0,
"aggs": {
"avg_grade": {
"terms": {
"field": "city"
},
"aggs": {
"resellers": {
"nested": {
"path": "cars"
},
"aggs": {
"agg_name": {
"terms": {
"field": "cars.name"
},
"aggs": {
"avg_pur": {
"sum": {
"field": "cars.purchase"
}
},
"avg_sold": {
"sum": {
"field": "cars.sold"
}
}
}
}
}
}
}
}
}
}
result:
buckets": [
{
"key": "Honda",
"doc_count": 2,
"avg_pur": {
"value": 350
},
"avg_sold": {
"value": 270
}
}
,
{
"key": "Toyota",
"doc_count": 2,
"avg_pur": {
"value": 150
},
"avg_sold": {
"value": 120
}
}
]
if you have index the name / city field as a text (you have to ask first if this is necessary), use .keyword in the term aggregation ("cars.name.keyword").

Filter elasticsearch bucket aggregation based on term field

I have a list of products (deal entities) and I'm attempting to create a bucket aggregation by categories, ordered by the sum of available_stock.
This all works fine, but I want to exclude such categories from the resulting aggregation that don't have level set to 1 (In other words, I only want to keep aggregations on category where level IS 1).
I am aware that elasticsearch provides "exclude" and "include" parameters, but these only work on the same field I'm aggregating on (deal.category.id in this case)
This is my sample deal document:
{
"_source": {
"id": 392745,
"category": [
{
"id": 17575,
"level": 2
},
{
"id": 17574,
"level": 1
},
{
"id": 17572,
"level": 0
}
],
"stats": {
"available_stock": 500
}
}
}
And this would be the query:
{
"query": {
"filtered": {
"query": {
"match_all": {}
},
}
},
"aggs": {
"mainAggregation": {
"terms": {
"field": "deal.category.id",
"order": {
"available_stock": "desc"
},
"size": 3
},
"aggs": {
"available_stock": {
"sum": {
"field": "deal.stats.available_stock"
}
}
}
}
},
"size": 0
}
And my resulting aggregation, sadly including category 17572 with level 0.
{
"aggregations": {
"mainAggregation": {
"buckets": [
{
"key": 17572,
"doc_count": 30,
"available_stock": {
"value": 24000
}
},
{
"key": 17598,
"doc_count": 10,
"available_stock": {
"value": 12000
}
},
{
"key": 17602,
"doc_count": 8,
"available_stock": {
"value": 6000
}
}
]
}
}
}
P.S.: Currently on ElasticSearch 1.6
Update 1: Still stuck on the problem after various experiments with various combimation of subaggregations.
I have found this impossible to solve and decided to go with two separate queries.

Elastic Search query return terms within array of a specific type

I've a mapping of an index as following:
{"tagged_index":{"mappings":{"tagged":{"properties":{"tags":{"properties":{"resources":{"properties":{"tagName":{"type":"string"},"type":{"type":"string"}}}}},"content":{"type":"string"}}}}}}
Where Resources is an array which can have multiple tags. For example
{"_id":"82906194","_source":{"tags":{"resources":[{"type":"Person","tagName":"Kim_Kardashian",},{"type":"Person","tagName":"Kanye_West",},{"type":"City","tagName":"New_York",},...},"content":" Popular NEWS ..."}}
,
{"_id":"82906195","_source":{"tags":{"resources":[{"type":"City","tagName":"London",},{"type":"Country","tagName":"USA",},{"type":"Music","tagName":"Hello",},...},"content":" Adele's Hello..."}},
...
I do know how to extract important terms[tagName] with the below query, but I do not want terms[tagName] of all types.
How can I extract only the terms which are for example Cities only [type:City]? (I would like to get a list of tagName where the type is City i.e. London, New_York, Berlin,...)
{"size":0,"query":{"filtered":{"query":{"query_string":{"query":"*","analyze_wildcard":true}}}},"aggs":{"Cities":{"terms":{"field":"tags.resources.tagName","size":10,"order":{"_count":"desc"}}}}}
Following is how the required output should look like:
{"took":1200,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":5179261,"max_score":0.0,"hits":[]},"aggregations":{"Cities":{"doc_count_error_upper_bound":46737,"sum_other_doc_count":36037440,"buckets":[{"key":"London","doc_count":332820},{"key":"New_York","doc_count":211274},{"key":"Berlin","doc_count":156954},{"key":"Amsterdam","doc_count":132173},...
Can you try this:
{
"_source" : ["tags.resources.tagName"]
"query": {
"term": {
"tags.resources.type": {
"value": "City"
}
}
}
}
Above query will fetch those resources which are of type city provided resources is of object type.
After Edit
Problem Group By Tag name which are Of city Type. That would not be achieved with the current mapping you have. You will have to change resources field to nested type.
Mapping would look like.
"mappings": {
"resource": {
"properties": {
"tags": {
"properties": {
"content": {
"type": "string"
},
"resources": {
"type": "nested",
"properties": {
"tagName": {
"type": "string"
},
"type": {
"type": "string"
}
}
}
}
}
}
}
}
Final query would be :
{
"size": 0,
"query": {
"nested": {
"path": "tags.resources",
"query": {
"match": {
"tags.resources.type": "city"
}
}
}
},
"aggs": {
"resources Nested path": {
"nested": {
"path": "tags.resources"
},
"aggs": {
"city type": {
"filter": {
"term": {
"tags.resources.type": "city"
}
},
"aggs": {
"group By tagName": {
"terms": {
"field": "tags.resources.tagName"
}
}
}
}
}
}
}
}
Output would be:
"aggregations": {
"resources Nested path": {
"doc_count": 6,
"city type": {
"doc_count": 2,
"group By tagName": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "london",
"doc_count": 1
},
{
"key": "new_york",
"doc_count": 1
}
]
}
}
}
}

Resources