IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Filter aggregation
editFilter aggregation
editA single bucket aggregation that narrows the set of documents to those that match a query.
Example:
resp = client.search(
index="sales",
size="0",
filter_path="aggregations",
aggs={
"avg_price": {
"avg": {
"field": "price"
}
},
"t_shirts": {
"filter": {
"term": {
"type": "t-shirt"
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
}
},
)
print(resp)
response = client.search(
index: 'sales',
size: 0,
filter_path: 'aggregations',
body: {
aggregations: {
avg_price: {
avg: {
field: 'price'
}
},
t_shirts: {
filter: {
term: {
type: 't-shirt'
}
},
aggregations: {
avg_price: {
avg: {
field: 'price'
}
}
}
}
}
}
)
puts response
const response = await client.search({
index: "sales",
size: 0,
filter_path: "aggregations",
aggs: {
avg_price: {
avg: {
field: "price",
},
},
t_shirts: {
filter: {
term: {
type: "t-shirt",
},
},
aggs: {
avg_price: {
avg: {
field: "price",
},
},
},
},
},
});
console.log(response);
POST /sales/_search?size=0&filter_path=aggregations
{
"aggs": {
"avg_price": { "avg": { "field": "price" } },
"t_shirts": {
"filter": { "term": { "type": "t-shirt" } },
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
}
}
The previous example calculates the average price of all sales as well as the average price of all T-shirt sales.
Response:
{
"aggregations": {
"avg_price": { "value": 140.71428571428572 },
"t_shirts": {
"doc_count": 3,
"avg_price": { "value": 128.33333333333334 }
}
}
}
Use a top-level query to limit all aggregations
editTo limit the documents on which all aggregations in a search run, use a
top-level query. This is faster than a single filter aggregation with
sub-aggregations.
For example, use this:
resp = client.search(
index="sales",
size="0",
filter_path="aggregations",
query={
"term": {
"type": "t-shirt"
}
},
aggs={
"avg_price": {
"avg": {
"field": "price"
}
}
},
)
print(resp)
response = client.search(
index: 'sales',
size: 0,
filter_path: 'aggregations',
body: {
query: {
term: {
type: 't-shirt'
}
},
aggregations: {
avg_price: {
avg: {
field: 'price'
}
}
}
}
)
puts response
const response = await client.search({
index: "sales",
size: 0,
filter_path: "aggregations",
query: {
term: {
type: "t-shirt",
},
},
aggs: {
avg_price: {
avg: {
field: "price",
},
},
},
});
console.log(response);
POST /sales/_search?size=0&filter_path=aggregations
{
"query": { "term": { "type": "t-shirt" } },
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
Instead of this:
resp = client.search(
index="sales",
size="0",
filter_path="aggregations",
aggs={
"t_shirts": {
"filter": {
"term": {
"type": "t-shirt"
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
}
},
)
print(resp)
response = client.search(
index: 'sales',
size: 0,
filter_path: 'aggregations',
body: {
aggregations: {
t_shirts: {
filter: {
term: {
type: 't-shirt'
}
},
aggregations: {
avg_price: {
avg: {
field: 'price'
}
}
}
}
}
}
)
puts response
const response = await client.search({
index: "sales",
size: 0,
filter_path: "aggregations",
aggs: {
t_shirts: {
filter: {
term: {
type: "t-shirt",
},
},
aggs: {
avg_price: {
avg: {
field: "price",
},
},
},
},
},
});
console.log(response);
POST /sales/_search?size=0&filter_path=aggregations
{
"aggs": {
"t_shirts": {
"filter": { "term": { "type": "t-shirt" } },
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
}
}
Use the filters aggregation for multiple filters
editTo group documents using multiple filters, use the
filters aggregation. This
is faster than multiple filter aggregations.
For example, use this:
resp = client.search(
index="sales",
size="0",
filter_path="aggregations",
aggs={
"f": {
"filters": {
"filters": {
"hats": {
"term": {
"type": "hat"
}
},
"t_shirts": {
"term": {
"type": "t-shirt"
}
}
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
}
},
)
print(resp)
response = client.search(
index: 'sales',
size: 0,
filter_path: 'aggregations',
body: {
aggregations: {
f: {
filters: {
filters: {
hats: {
term: {
type: 'hat'
}
},
t_shirts: {
term: {
type: 't-shirt'
}
}
}
},
aggregations: {
avg_price: {
avg: {
field: 'price'
}
}
}
}
}
}
)
puts response
const response = await client.search({
index: "sales",
size: 0,
filter_path: "aggregations",
aggs: {
f: {
filters: {
filters: {
hats: {
term: {
type: "hat",
},
},
t_shirts: {
term: {
type: "t-shirt",
},
},
},
},
aggs: {
avg_price: {
avg: {
field: "price",
},
},
},
},
},
});
console.log(response);
POST /sales/_search?size=0&filter_path=aggregations
{
"aggs": {
"f": {
"filters": {
"filters": {
"hats": { "term": { "type": "hat" } },
"t_shirts": { "term": { "type": "t-shirt" } }
}
},
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
}
}
Instead of this:
resp = client.search(
index="sales",
size="0",
filter_path="aggregations",
aggs={
"hats": {
"filter": {
"term": {
"type": "hat"
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
},
"t_shirts": {
"filter": {
"term": {
"type": "t-shirt"
}
},
"aggs": {
"avg_price": {
"avg": {
"field": "price"
}
}
}
}
},
)
print(resp)
response = client.search(
index: 'sales',
size: 0,
filter_path: 'aggregations',
body: {
aggregations: {
hats: {
filter: {
term: {
type: 'hat'
}
},
aggregations: {
avg_price: {
avg: {
field: 'price'
}
}
}
},
t_shirts: {
filter: {
term: {
type: 't-shirt'
}
},
aggregations: {
avg_price: {
avg: {
field: 'price'
}
}
}
}
}
}
)
puts response
const response = await client.search({
index: "sales",
size: 0,
filter_path: "aggregations",
aggs: {
hats: {
filter: {
term: {
type: "hat",
},
},
aggs: {
avg_price: {
avg: {
field: "price",
},
},
},
},
t_shirts: {
filter: {
term: {
type: "t-shirt",
},
},
aggs: {
avg_price: {
avg: {
field: "price",
},
},
},
},
},
});
console.log(response);
POST /sales/_search?size=0&filter_path=aggregations
{
"aggs": {
"hats": {
"filter": { "term": { "type": "hat" } },
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
},
"t_shirts": {
"filter": { "term": { "type": "t-shirt" } },
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
}
}