Range Aggregation
editRange Aggregation
editA multi-bucket value source based aggregation that enables the user to define a set of ranges - each representing a bucket. During the aggregation process, the values extracted from each document will be checked against each bucket range and "bucket" the relevant/matching document.
Note that this aggregation includes the from value and excludes the to value for each range.
Example:
GET /_search
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"ranges" : [
{ "to" : 100.0 },
{ "from" : 100.0, "to" : 200.0 },
{ "from" : 200.0 }
]
}
}
}
}
Response:
{
...
"aggregations": {
"price_ranges" : {
"buckets": [
{
"key": "*-100.0",
"to": 100.0,
"doc_count": 2
},
{
"key": "100.0-200.0",
"from": 100.0,
"to": 200.0,
"doc_count": 2
},
{
"key": "200.0-*",
"from": 200.0,
"doc_count": 3
}
]
}
}
}
Keyed Response
editSetting the keyed flag to true will associate a unique string key with each bucket and return the ranges as a hash rather than an array:
GET /_search
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"keyed" : true,
"ranges" : [
{ "to" : 100 },
{ "from" : 100, "to" : 200 },
{ "from" : 200 }
]
}
}
}
}
Response:
{
...
"aggregations": {
"price_ranges" : {
"buckets": {
"*-100.0": {
"to": 100.0,
"doc_count": 2
},
"100.0-200.0": {
"from": 100.0,
"to": 200.0,
"doc_count": 2
},
"200.0-*": {
"from": 200.0,
"doc_count": 3
}
}
}
}
}
It is also possible to customize the key for each range:
GET /_search
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"keyed" : true,
"ranges" : [
{ "key" : "cheap", "to" : 100 },
{ "key" : "average", "from" : 100, "to" : 200 },
{ "key" : "expensive", "from" : 200 }
]
}
}
}
}
Response:
{
...
"aggregations": {
"price_ranges" : {
"buckets": {
"cheap": {
"to": 100.0,
"doc_count": 2
},
"average": {
"from": 100.0,
"to": 200.0,
"doc_count": 2
},
"expensive": {
"from": 200.0,
"doc_count": 3
}
}
}
}
}
Script
editRange aggregation accepts a script parameter. This parameter allows to defined an inline script that
will be executed during aggregation execution.
The following example shows how to use an inline script with the painless script language and no script parameters:
GET /_search
{
"aggs" : {
"price_ranges" : {
"range" : {
"script" : {
"lang": "painless",
"source": "doc['price'].value"
},
"ranges" : [
{ "to" : 100 },
{ "from" : 100, "to" : 200 },
{ "from" : 200 }
]
}
}
}
}
It is also possible to use stored scripts. Here is a simple stored script:
POST /_scripts/convert_currency
{
"script": {
"lang": "painless",
"source": "doc[params.field].value * params.conversion_rate"
}
}
And this new stored script can be used in the range aggregation like this:
Value Script
editLets say the product prices are in USD but we would like to get the price ranges in EURO. We can use value script to convert the prices prior the aggregation (assuming conversion rate of 0.8)
GET /sales/_search
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"script" : {
"source": "_value * params.conversion_rate",
"params" : {
"conversion_rate" : 0.8
}
},
"ranges" : [
{ "to" : 35 },
{ "from" : 35, "to" : 70 },
{ "from" : 70 }
]
}
}
}
}
Sub Aggregations
editThe following example, not only "bucket" the documents to the different buckets but also computes statistics over the prices in each price range
GET /_search
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"ranges" : [
{ "to" : 100 },
{ "from" : 100, "to" : 200 },
{ "from" : 200 }
]
},
"aggs" : {
"price_stats" : {
"stats" : { "field" : "price" }
}
}
}
}
}
Response:
{
...
"aggregations": {
"price_ranges": {
"buckets": [
{
"key": "*-100.0",
"to": 100.0,
"doc_count": 2,
"price_stats": {
"count": 2,
"min": 10.0,
"max": 50.0,
"avg": 30.0,
"sum": 60.0
}
},
{
"key": "100.0-200.0",
"from": 100.0,
"to": 200.0,
"doc_count": 2,
"price_stats": {
"count": 2,
"min": 150.0,
"max": 175.0,
"avg": 162.5,
"sum": 325.0
}
},
{
"key": "200.0-*",
"from": 200.0,
"doc_count": 3,
"price_stats": {
"count": 3,
"min": 200.0,
"max": 200.0,
"avg": 200.0,
"sum": 600.0
}
}
]
}
}
}
If a sub aggregation is also based on the same value source as the range aggregation (like the stats aggregation in the example above) it is possible to leave out the value source definition for it. The following will return the same response as above: