本篇文章为你整理了Aggregations（aggregation数据集）的详细内容，包含有aggregations翻译 aggregation数据集 aggregations 托福 aggregation算法 Aggregations，希望能帮助你了解 Aggregations。
An aggregation summarizes your data as metrics, statistics, or other analytics.
Aggregations help you answer questions like:
Metric aggregations that calculate metrics,
such as a sum or average, from field values.
Bucket aggregations that
group documents into buckets, also called bins, based on field values, ranges,
or other criteria.
Pipeline aggregations that take input from
other aggregations instead of documents or fields.
Aggregation results are in the response s aggregations object:
{
"took": 78,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
"hits": {
"total": {
"value": 5,
"relation": "eq"
"max_score": 1.0,
"hits": [...]
"aggregations": {
"my-agg-name": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
Change an aggregation s scopeedit
Use the query parameter to limit the documents on which an aggregation runs:
GET /my-index-000001/_search
"query": {
"range": {
"@timestamp": {
"gte": "now-1d/d",
"lt": "now/d"
"aggs": {
"my-agg-name": {
"terms": {
"field": "my-field"
}
Return only aggregation resultsedit
By default, searches containing an aggregation return both search hits and
aggregation results. To return only aggregation results, set size to 0:
GET /my-index-000001/_search
"size": 0,
"aggs": {
"my-agg-name": {
"terms": {
"field": "my-field"
}
Run multiple aggregationsedit
You can specify multiple aggregations in the same request:
GET /my-index-000001/_search
"aggs": {
"my-first-agg-name": {
"terms": {
"field": "my-field"
"my-second-agg-name": {
"avg": {
"field": "my-other-field"
}
Run sub-aggregationsedit
Bucket aggregations support bucket or metric sub-aggregations. For example, a
terms aggregation with an avg
sub-aggregation calculates an average value for each bucket of documents. There
is no level or depth limit for nesting sub-aggregations.
GET /my-index-000001/_search
"aggs": {
"my-agg-name": {
"terms": {
"field": "my-field"
"aggs": {
"my-sub-agg-name": {
"avg": {
"field": "my-other-field"
}
The response nests sub-aggregation results under their parent aggregation:
{
"aggregations": {
"my-agg-name": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
"key": "foo",
"doc_count": 5,
"my-sub-agg-name": {
"value": 75.0
}
Add custom metadataedit
Use the meta object to associate custom metadata with an aggregation:
GET /my-index-000001/_search
"aggs": {
"my-agg-name": {
"terms": {
"field": "my-field"
"meta": {
"my-metadata-field": "foo"
}
The response returns the meta object in place:
{
"aggregations": {
"my-agg-name": {
"meta": {
"my-metadata-field": "foo"
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
Return the aggregation typeedit
By default, aggregation results include the aggregation s name but not its type.
To return the aggregation type, use the typed_keys query parameter.
GET /my-index-000001/_search?typed_keys
"aggs": {
"my-agg-name": {
"histogram": {
"field": "my-field",
"interval": 1000
}
The response returns the aggregation type as a prefix to the aggregation s name.
Some aggregations return a different aggregation type from the
type in the request. For example, the terms,
significant terms,
and percentiles
aggregations return different aggregations types depending on the data type of
the aggregated field.
The aggregation type, histogram, followed by a # separator and the aggregation s name, my-agg-name.
Use scripts in an aggregationedit
When a field doesn t exactly match the aggregation you need, you
should aggregate on a runtime field:
GET /my-index-000001/_search?size=0
"runtime_mappings": {
"message.length": {
"type": "long",
"script": "emit(doc[message.keyword].value.length())"
"aggs": {
"message_length": {
"histogram": {
"interval": 10,
"field": "message.length"
}
Scripts calculate field values dynamically, which adds a little
overhead to the aggregation. In addition to the time spent calculating,
some aggregations like terms
and filters can t use
some of their optimizations with runtime fields. In total, performance costs
for using a runtime field varies from aggregation to aggregation.
Aggregation cachesedit
For faster responses, Elasticsearch caches the results of frequently run aggregations in
the shard request cache. To get cached results, use the
same preference string for each search. If you
don t need search hits, set size to 0 to avoid
filling the cache.
Elasticsearch routes searches with the same preference string to the same shards. If the
shards data doesn’t change between searches, the shards return cached
aggregation results.
Limits for long valuesedit
When running aggregations, Elasticsearch uses double values to hold and
represent numeric data. As a result, aggregations on long numbers
greater than 253 are approximate.
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