Elasticsearch bucket aggregation using concatenated parameter - json

Question

I'm using Elasticsearch API and the schema of the document as follow
{
name: "",
born_year: "",
born_month: "",
born_day: "",
book_type: "",
price: <some number>,
country: ""
}
Now what I need is to get the document count per each name where born before 1995 (born_year + born_month + born_day < "20051220"). How can i achieve?
I tried this:
{
"query": {
"query_string": {
"query": "country:\"SL\""
}
},
"size": 0,
"aggs": {
"total": {
"terms": {
"field": "name"
}
}
}
}
But I have no idea how can I add filter for the birthday.

Answer 1

As mentioned by #val, you need to add a real date field that you can easily add by concatenating these three fields at creation time.
But how you filter based on date range, there are two ways and both of them will return different result sets
Now the level of filtering is your choice.
You mentioned querying on country field. But you have not mentioned at what level you want to filter on date range. I will give you queries for both the cases.
Mappings- assuming you create a date field.
{
name:"",
born_year:"",
born_month:"",
born_day:"",
book_type:"",
price:<some number>,
country:"",
date : ""
}
Case - 1) Filtering date range for name aggregations only, here documents count will not be effected by the date range filter
{
"query": {
"query_string": {
"query": "country:\"SL\""
}
},
"aggs": {
"total": {
"filter": {
"range": {
"date": {
"gte": "your_date_mx",
"lte": "your_date_min"
}
}
},
"aggs": {
"NAME": {
"terms": {
"field": "name",
"size": 10
}
}
}
}
}
}
Case 2) In this case both your documents count and aggregation will be filtered for date range as we add date range filter at query level.
{
"query": {
"query_string": {
"query": "country:\"SL\""
},
"bool": {
"must": [
{
"range": {
"date": {
"gte": "your_date_mx",
"lte": "your_date_mic"
}
}
}
]
}
},
"aggs": {
"toal": {
"terms": {
"field": "name",
"size": 10
}
}
}
}
So adding a filter to aggregation will effect only aggs count.
Edit -
Approach1) with groovy script try to concatinate the string and parse it to integer and then compare with your input date.
{
"query": {
"bool": {
"must": [
{}
],
"filter": {
"script": {
"script": {
"inline": "(doc['year'].value + doc['month'].value + doc['date'].value).toInteger() > 19910701",
"params": {
"param1": 19911122
}
}
}
}
}
}
}
Make sure when indexing index date(or month) with single digit like 6 as 06
2) Approach 2 - parse the string the exact date(preferred)
{
"query": {
"bool": {
"must": [
{}
],
"filter": {
"script": {
"script": {
"inline": "Date.parse('dd-MM-yyyy',doc['date'].value +'-'+ doc['month'].value +'-'+ doc['year'].value).format('dd-MM-yyyy') > param1",
"params": {
"param1": "04-05-1991"
}
}
}
}
}
}
}
Second approach is much better approach as you don't have to worry about the maintaing the string for each field(date, month, day) to later parse to proper int for comparing.