Value count aggregation
editValue count aggregation
editA single-value metrics aggregation that counts the number of values that are extracted from the aggregated documents.
These values can be extracted either from specific fields in the documents, or be generated by a provided script. Typically,
this aggregator will be used in conjunction with other single-value aggregations. For example, when computing the avg
one might be interested in the number of values the average is computed over.
value_count does not de-duplicate values, so even if a field has duplicates each value will be counted individually.
response = client.search(
index: 'sales',
size: 0,
body: {
aggregations: {
types_count: {
value_count: {
field: 'type'
}
}
}
}
)
puts response
res, err := es.Search(
es.Search.WithIndex("sales"),
es.Search.WithBody(strings.NewReader(`{
"aggs": {
"types_count": {
"value_count": {
"field": "type"
}
}
}
}`)),
es.Search.WithSize(0),
es.Search.WithPretty(),
)
fmt.Println(res, err)
POST /sales/_search?size=0
{
"aggs" : {
"types_count" : { "value_count" : { "field" : "type" } }
}
}
Response:
{
...
"aggregations": {
"types_count": {
"value": 7
}
}
}
The name of the aggregation (types_count above) also serves as the key by which the aggregation result can be
retrieved from the returned response.
Script
editIf you need to count something more complex than the values in a single field you should run the aggregation on a runtime field.
POST /sales/_search
{
"size": 0,
"runtime_mappings": {
"tags": {
"type": "keyword",
"script": """
emit(doc['type'].value);
if (doc['promoted'].value) {
emit('hot');
}
"""
}
},
"aggs": {
"tags_count": {
"value_count": {
"field": "tags"
}
}
}
}
Histogram fields
editWhen the value_count aggregation is computed on histogram fields, the result of the aggregation is the sum of all numbers
in the counts array of the histogram.
For example, for the following index that stores pre-aggregated histograms with latency metrics for different networks:
response = client.index(
index: 'metrics_index',
id: 1,
body: {
"network.name": 'net-1',
latency_histo: {
values: [
0.1,
0.2,
0.3,
0.4,
0.5
],
counts: [
3,
7,
23,
12,
6
]
}
}
)
puts response
response = client.index(
index: 'metrics_index',
id: 2,
body: {
"network.name": 'net-2',
latency_histo: {
values: [
0.1,
0.2,
0.3,
0.4,
0.5
],
counts: [
8,
17,
8,
7,
6
]
}
}
)
puts response
response = client.index(
index: 'metrics_index',
size: 0,
body: {
aggregations: {
total_requests: {
value_count: {
field: 'latency_histo'
}
}
}
}
)
puts response
{
res, err := es.Index(
"metrics_index",
strings.NewReader(`{
"network.name": "net-1",
"latency_histo": {
"values": [
0.1,
0.2,
0.3,
0.4,
0.5
],
"counts": [
3,
7,
23,
12,
6
]
}
}`),
es.Index.WithDocumentID("1"),
es.Index.WithPretty(),
)
fmt.Println(res, err)
}
{
res, err := es.Index(
"metrics_index",
strings.NewReader(`{
"network.name": "net-2",
"latency_histo": {
"values": [
0.1,
0.2,
0.3,
0.4,
0.5
],
"counts": [
8,
17,
8,
7,
6
]
}
}`),
es.Index.WithDocumentID("2"),
es.Index.WithPretty(),
)
fmt.Println(res, err)
}
{
res, err := es.Search(
es.Search.WithIndex("metrics_index"),
es.Search.WithBody(strings.NewReader(`{
"aggs": {
"total_requests": {
"value_count": {
"field": "latency_histo"
}
}
}
}`)),
es.Search.WithSize(0),
es.Search.WithPretty(),
)
fmt.Println(res, err)
}
PUT metrics_index/_doc/1
{
"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
{
"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
{
"aggs": {
"total_requests": {
"value_count": { "field": "latency_histo" }
}
}
}
For each histogram field the value_count aggregation will sum all numbers in the counts array <1>.
Eventually, it will add all values for all histograms and return the following result:
{
...
"aggregations": {
"total_requests": {
"value": 97
}
}
}