A single-value metrics aggregation that keeps track and returns the maximum
value among the numeric values extracted from the aggregated documents.
The min and max aggregation operate on the double representation of
the data. As a consequence, the result may be approximate when running on longs
whose absolute value is greater than 2^53.
Computing the max price value across all documents
POST /sales/_search?size=0
{
"aggs": {
"max_price": { "max": { "field": "price" } }
}
}
Response:
{
...
"aggregations": {
"max_price": {
"value": 200.0
}
}
}
As can be seen, the name of the aggregation (max_price above) also serves as
the key by which the aggregation result can be retrieved from the returned
response.
If you need to get the max of something more complex than a single field,
run an aggregation on a runtime field.
POST /sales/_search
{
"size": 0,
"runtime_mappings": {
"price.adjusted": {
"type": "double",
"script": """
double price = doc['price'].value;
if (doc['promoted'].value) {
price *= 0.8;
}
emit(price);
"""
}
},
"aggs": {
"max_price": {
"max": { "field": "price.adjusted" }
}
}
}
The missing parameter defines how documents that are missing a value should
be treated. By default they will be ignored but it is also possible to treat
them as if they had a value.
When max is computed on histogram fields, the result of the aggregation is the maximum
of all elements in the values array. Note, that the counts array of the histogram is ignored.
For example, for the following index that stores pre-aggregated histograms with latency metrics for different networks:
PUT metrics_index
{
"mappings": {
"properties": {
"latency_histo": { "type": "histogram" }
}
}
}
PUT metrics_index/_doc/1?refresh
{
"network.name" : "net-1",
"latency_histo" : {
"values" : [0.1, 0.2, 0.3, 0.4, 0.5],
"counts" : [3, 7, 23, 12, 6]
}
}
PUT metrics_index/_doc/2?refresh
{
"network.name" : "net-2",
"latency_histo" : {
"values" : [0.1, 0.2, 0.3, 0.4, 0.5],
"counts" : [8, 17, 8, 7, 6]
}
}
POST /metrics_index/_search?size=0&filter_path=aggregations
{
"aggs" : {
"max_latency" : { "max" : { "field" : "latency_histo" } }
}
}
The max aggregation will return the maximum value of all histogram fields:
{
"aggregations": {
"max_latency": {
"value": 0.5
}
}
}