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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 aggregration includes the from value and excludes the to value for each range.
Example:
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"ranges" : [
{ "to" : 50 },
{ "from" : 50, "to" : 100 },
{ "from" : 100 }
]
}
}
}
}
Response:
{
...
"aggregations": {
"price_ranges" : {
"buckets": [
{
"to": 50,
"doc_count": 2
},
{
"from": 50,
"to": 100,
"doc_count": 4
},
{
"from": 100,
"doc_count": 4
}
]
}
}
}
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:
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"keyed" : true,
"ranges" : [
{ "to" : 50 },
{ "from" : 50, "to" : 100 },
{ "from" : 100 }
]
}
}
}
}
Response:
{
...
"aggregations": {
"price_ranges" : {
"buckets": {
"*-50.0": {
"to": 50,
"doc_count": 2
},
"50.0-100.0": {
"from": 50,
"to": 100,
"doc_count": 4
},
"100.0-*": {
"from": 100,
"doc_count": 4
}
}
}
}
}
It is also possible to customize the key for each range:
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"keyed" : true,
"ranges" : [
{ "key" : "cheap", "to" : 50 },
{ "key" : "average", "from" : 50, "to" : 100 },
{ "key" : "expensive", "from" : 100 }
]
}
}
}
}
Script
editThe script parameter expects an inline script. Use script_id for indexed scripts and script_file for scripts in the config/scripts/ directory.
{
"aggs" : {
"price_ranges" : {
"range" : {
"script" : "doc['price'].value",
"ranges" : [
{ "to" : 50 },
{ "from" : 50, "to" : 100 },
{ "from" : 100 }
]
}
}
}
}
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)
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"script" : "_value * 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
{
"aggs" : {
"price_ranges" : {
"range" : {
"field" : "price",
"ranges" : [
{ "to" : 50 },
{ "from" : 50, "to" : 100 },
{ "from" : 100 }
]
},
"aggs" : {
"price_stats" : {
"stats" : { "field" : "price" }
}
}
}
}
}
Response:
{
"aggregations": {
"price_ranges" : {
"buckets": [
{
"to": 50,
"doc_count": 2,
"price_stats": {
"count": 2,
"min": 20,
"max": 47,
"avg": 33.5,
"sum": 67
}
},
{
"from": 50,
"to": 100,
"doc_count": 4,
"price_stats": {
"count": 4,
"min": 60,
"max": 98,
"avg": 82.5,
"sum": 330
}
},
{
"from": 100,
"doc_count": 4,
"price_stats": {
"count": 4,
"min": 134,
"max": 367,
"avg": 216,
"sum": 864
}
}
]
}
}
}
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: