Elasticsearch Aggregation most common list of integers - elasticsearch

I am looking for elastic search aggregation + mapping
that will return the most common list for a certain field.
For example for docs:
{"ToneCurvePV2012": [1,2,3]}
{"ToneCurvePV2012": [1,5,6]}
{"ToneCurvePV2012": [1,7,8]}
{"ToneCurvePV2012": [1,2,3]}
I wish for the aggregation result:
[1,2,3] (since it appears twice).
so far any aggregation that i made would return: 1

This is not possible with default terms aggregation. You need to use terms aggregation with script. Please note that this might impact your cluster performance.
Here, i have used script which will create string from array and used it for aggregation. so if you have array value like [1,2,3] then it will create string representation of it like '[1,2,3]' and that key will be used for aggregation.
Below is sample query you can use to generate aggregation as you expected:
POST index1/_search
{
"size": 0,
"aggs": {
"tone_s": {
"terms": {
"script": {
"source": "def value='['; for(int i=0;i<doc['ToneCurvePV2012'].length;i++){value= value + doc['ToneCurvePV2012'][i] + ',';} value+= ']'; value = value.replace(',]', ']'); return value;"
}
}
}
}
}
Output:
{
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"tone_s" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "[1,2,3]",
"doc_count" : 2
},
{
"key" : "[1,5,6]",
"doc_count" : 1
},
{
"key" : "[1,7,8]",
"doc_count" : 1
}
]
}
}
}
PS: key will be come as string and not as array in aggregation response.

Related

Elasic Existed Query Not working About Empty String

According to Official 7.x document Link
While a field is deemed non-existent if the JSON value is null or [],
these values will indicate the field does exist:
Empty strings, such as "" or "-" Arrays containing null and another
value, such as [null, "foo"] A custom null-value, defined in field
mapping
However, My es not consider "" as not existed.
Here is my Data:
"_source" : {
"chat_msg" : {
"action" : "send",
"from" : "t",
"msgid" : "6505946507184390735_161_external",
"msgtime" : 1623396135015,
"msgtype" : "text",
"roomid" : "",
Now, When I do Query As :
GET enterprise_chat_data/_search
{
"query": {
"bool": {
"must_not": [
{
"exists": {
"field": "chat_msg.roomid"
}
}
]
}
}
}
Result:
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 0,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
}
}
It Hit Nothing. Am I Wrong About Something?
I think you have misunderstood the documentation. In the documentation, it is written that if a field have value as empty strings, such as "" or "-", then that field will be considered to be existing.
Due to this when you are querying for must_not exists query for "chat_msg.roomid" field, you are getting empty results, as in the data you have indexed the value of "chat_msg.roomid" field as ""
Update 1:
You can use term query to search for documents having field value of chat_msg.roomid as ""
{
"query": {
"term": {
"chat_msg.roomid.keyword": ""
}
}
}

Terms aggregation on an inner object and retrieving bucket metadata

We index the following products:
{
"id": "1",
"name": "the-name",
"categories": [
{
"id" : 10,
"name" : "cat-1"
},
{
"id" : 20,
"name" : "cat-2"
}
]
}
We are doing an aggregation on categories.id using :
REQUEST:
//...
"aggs": {
"by_cat": {
"terms": {
"field": "categories.id",
"size": 10
}
}
}
---
RESPONSE:
// ...
"by_cat" : {
"buckets" : [
{
"key" : 10,
"doc_count" : 804
},
{
"key" : 20,
"doc_count" : 327
},
It works well, however, each bucket contains only the categories.id in the key field. What we would like is to be able to have the name of the category in the bucket, for example :
// ...
"buckets" : [
{
"key" : 10,
"metadata": {
"name": "cat-1"
},
"doc_count" : 804
},
{
"key" : 20,
"metadata": {
"name": "cat-2"
},
"doc_count" : 327
},
What is the good way to do that ? We found two to get this information but they both looks "hackish" :
Using top_hits with size 1 and source limited to categories, it will retrieve one document per bucket containing the information we need. This first solution doesn't look performance-wise and the more aggregation we have, the more bloated is the response.
Adding a new column id_name which concatenate id and name and doing the term aggregation on it. It looks more like a hack, and may be complicated if many fields.
We also tried by mixing field and script in terms but it doesn't help.
metadata looked exactly what we wanted but it is global for all the buckets and not dynamic.
Do we have other way to retrieve this information ?

SQL aggregation query corresponding in elasticsearch

I studied elasticsearch aggregation queries but couldn't find if it supports multiple aggregate function. In an other word, I wanna know if elasticsearch can generate the equivalent of this Sql aggregation query:
SELECT account_no, transaction_type, count(account_no), sum(amount), max(amount) FROM index_name GROUP BY account_no, transaction_type Having count(account_no) > 10
If yes, how?
Thank you.
There are two possible ways to do what you are looking for in ES and I've mentioned them both below.
I've also added sample mapping and sample documents for your reference.
Mapping:
PUT index_name
{
"mappings": {
"mydocs":{
"properties":{
"account_no":{
"type": "keyword"
},
"transaction_type":{
"type": "keyword"
},
"amount":{
"type":"double"
}
}
}
}
}
Sample Documents:
Notice carefully, I'm only creating list of 4 transactions for 1 customer.
POST index_name/mydocs/1
{
"account_no": "1011",
"transaction_type":"credit",
"amount": 200
}
POST index_name/mydocs/2
{
"account_no": "1011",
"transaction_type":"credit",
"amount": 400
}
POST index_name/mydocs/3
{
"account_no": "1011",
"transaction_type":"cheque",
"amount": 100
}
POST index_name/mydocs/4
{
"account_no": "1011",
"transaction_type":"cheque",
"amount": 100
}
There are two ways to get what you are looking for:
Solution 1: Using Elasticsearch Query DSL
Aggregation Query:
For Aggregation Query DSL, I've made use of the below aggregation queries to solve what you are looking for.
Terms Aggregation
Sum Aggregation Query (Metric Aggregation)
Max Aggregation Query (Metric Aggregation)
Below is how query is summarised version of the query so that you get the clarity on which queries are sibling and which are parents.
- Terms Aggregation (For Every Account)
- Terms Aggregation (For Every Transaction_type)
- Sum Amount
- Max Amount
Below is the actual query:
POST index_name/_search
{
"size": 0,
"aggs": {
"account_no_agg": {
"terms": {
"field": "account_no"
},
"aggs": {
"transaction_type_agg": {
"terms": {
"field": "transaction_type",
"min_doc_count": 2
},
"aggs": {
"sum_amount": {
"sum": {
"field": "amount"
}
},
"max_amount":{
"max": {
"field": "amount"
}
}
}
}
}
}
}
}
Important thing to mention is min_doc_count which is nothing but the having count(account_no)>10, which in my query I'm filtering only those transactions with having count(account_no) > 2
Query Response
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : 4,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"account_no_agg" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "1011", <---- account_no
"doc_count" : 4, <---- count(account_no)
"transaction_type_agg" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "cheque", <---- transaction_type
"doc_count" : 2,
"sum_amount" : { <---- sum(amount)
"value" : 200.0
},
"max_amount" : { <---- max(amount)
"value" : 100.0
}
},
{
"key" : "credit", <---- another transaction_type
"doc_count" : 2,
"sum_amount" : { <---- sum(amount)
"value" : 600.0
},
"max_amount" : { <---- max(amount)
"value" : 400.0
}
}
]
}
}
]
}
}
}
Notice the above result carefully, I've added comments wherever required so that it helps what part of sql query you are looking for.
Solution 2: Using Elasticsearch SQL(_xpack solution)
If you are making use of xpack feature of Elasticsearch's SQL Access, you can simply copy paste the SELECT Query as below for the mapping and document as mentioned above:
Elasticsearch SQL:
POST /_xpack/sql?format=txt
{
"query": "SELECT account_no, transaction_type, sum(amount), max(amount), count(account_no) FROM index_name GROUP BY account_no, transaction_type HAVING count(account_no) > 1"
}
Elasticsearch SQL Result:
account_no |transaction_type| SUM(amount) | MAX(amount) |COUNT(account_no)
---------------+----------------+---------------+---------------+-----------------
1011 |cheque |200.0 |100.0 |2
1011 |credit |600.0 |400.0 |2
Note that I've tested the query in ES 6.5.4.
Hope this helps!

Elasticsearch plugin to classify documents

Is there an elasticsearch plugin out there that would allow me to classify the documents that I enter in an index?
The best solution for me would be a classifications of all the most recurrent terms (/ concepts) displayed in a sort of tags cloud that the user can navigate.
Is there a way to achieve this? Any suggestions?
Thanks
The basic idea is to use a terms aggregations, which will yield one bucket per term.
POST /_search
{
"aggs" : {
"genres" : {
"terms" : { "field" : "genre" }
}
}
}
The response you'll get will be ordered by decreasing amount of term occurrences:
{
...
"aggregations" : {
"genres" : {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets" : [
{
"key" : "jazz",
"doc_count" : 10
},
{
"key" : "rock",
"doc_count" : 5
},
{
"key" : "electronic",
"doc_count" : 2
},
]
}
}
}
If you're using Kibana, you can directly create a tag cloud visualization based on those terms.

Show all Elasticsearch aggregation results/buckets and not just 10

I'm trying to list all buckets on an aggregation, but it seems to be showing only the first 10.
My search:
curl -XPOST "http://localhost:9200/imoveis/_search?pretty=1" -d'
{
"size": 0,
"aggregations": {
"bairro_count": {
"terms": {
"field": "bairro.raw"
}
}
}
}'
Returns:
{
"took" : 2,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"hits" : {
"total" : 16920,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"bairro_count" : {
"buckets" : [ {
"key" : "Barra da Tijuca",
"doc_count" : 5812
}, {
"key" : "Centro",
"doc_count" : 1757
}, {
"key" : "Recreio dos Bandeirantes",
"doc_count" : 1027
}, {
"key" : "Ipanema",
"doc_count" : 927
}, {
"key" : "Copacabana",
"doc_count" : 842
}, {
"key" : "Leblon",
"doc_count" : 833
}, {
"key" : "Botafogo",
"doc_count" : 594
}, {
"key" : "Campo Grande",
"doc_count" : 456
}, {
"key" : "Tijuca",
"doc_count" : 361
}, {
"key" : "Flamengo",
"doc_count" : 328
} ]
}
}
}
I have much more than 10 keys for this aggregation. In this example I'd have 145 keys, and I want the count for each of them. Is there some pagination on buckets? Can I get all of them?
I'm using Elasticsearch 1.1.0
The size param should be a param for the terms query example:
curl -XPOST "http://localhost:9200/imoveis/_search?pretty=1" -d'
{
"size": 0,
"aggregations": {
"bairro_count": {
"terms": {
"field": "bairro.raw",
"size": 10000
}
}
}
}'
Use size: 0 for ES version 2 and prior.
Setting size:0 is deprecated in 2.x onwards, due to memory issues inflicted on your cluster with high-cardinality field values. You can read more about it in the github issue here .
It is recommended to explicitly set reasonable value for size a number between 1 to 2147483647.
How to show all buckets?
{
"size": 0,
"aggs": {
"aggregation_name": {
"terms": {
"field": "your_field",
"size": 10000
}
}
}
}
Note
"size":10000 Get at most 10000 buckets. Default is 10.
"size":0 In result, "hits" contains 10 documents by default. We don't need them.
By default, the buckets are ordered by the doc_count in decreasing order.
Why do I get Fielddata is disabled on text fields by default error?
Because fielddata is disabled on text fields by default. If you have not wxplicitly chosen a field type mapping, it has the default dynamic mappings for string fields.
So, instead of writing "field": "your_field" you need to have "field": "your_field.keyword".
If you want to get all unique values without setting a magic number (size: 10000), then use COMPOSITE AGGREGATION (ES 6.5+).
From official documentation:
"If you want to retrieve all terms or all combinations of terms in a nested terms aggregation you should use the COMPOSITE AGGREGATION which allows to paginate over all possible terms rather than setting a size greater than the cardinality of the field in the terms aggregation. The terms aggregation is meant to return the top terms and does not allow pagination."
Implementation example in JavaScript:
const ITEMS_PER_PAGE = 1000;
const body = {
"size": 0, // Returning only aggregation results: https://www.elastic.co/guide/en/elasticsearch/reference/current/returning-only-agg-results.html
"aggs" : {
"langs": {
"composite" : {
"size": ITEMS_PER_PAGE,
"sources" : [
{ "language": { "terms" : { "field": "language" } } }
]
}
}
}
};
const uniqueLanguages = [];
while (true) {
const result = await es.search(body);
const currentUniqueLangs = result.aggregations.langs.buckets.map(bucket => bucket.key);
uniqueLanguages.push(...currentUniqueLangs);
const after = result.aggregations.langs.after_key;
if (after) {
// continue paginating unique items
body.aggs.langs.composite.after = after;
} else {
break;
}
}
console.log(uniqueLanguages);
Increase the size(2nd size) to 10000 in your term aggregations and you will get the bucket of size 10000. By default it is set to 10.
Also if you want to see the search results just make the 1st size to 1, you can see 1 document, since ES does support both searching and aggregation.
curl -XPOST "http://localhost:9200/imoveis/_search?pretty=1" -d'
{
"size": 1,
"aggregations": {
"bairro_count": {
"terms": {
"field": "bairro.raw",
"size": 10000
}
}
}
}'

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