Top metrics aggregation
editTop metrics aggregation
editThe top_metrics
aggregation selects metrics from the document with the largest or smallest "sort"
value. For example, this gets the value of the m
field on the document with the largest value of s
:
POST /test/_bulk?refresh {"index": {}} {"s": 1, "m": 3.1415} {"index": {}} {"s": 2, "m": 1.0} {"index": {}} {"s": 3, "m": 2.71828} POST /test/_search?filter_path=aggregations { "aggs": { "tm": { "top_metrics": { "metrics": {"field": "m"}, "sort": {"s": "desc"} } } } }
Which returns:
{ "aggregations": { "tm": { "top": [ {"sort": [3], "metrics": {"m": 2.718280076980591 } } ] } } }
top_metrics
is fairly similar to top_hits
in spirit but because it is more limited it is able to do its job using less memory and is often
faster.
sort
editThe sort
field in the metric request functions exactly the same as the sort
field in the
search request except:
The metrics that the aggregation returns is the first hit that would be returned by the search request. So,
-
"sort": {"s": "desc"}
-
gets metrics from the document with the highest
s
-
"sort": {"s": "asc"}
-
gets the metrics from the document with the lowest
s
-
"sort": {"_geo_distance": {"location": "35.7796, -78.6382"}}
-
gets metrics from the documents with
location
closest to35.7796, -78.6382
-
"sort": "_score"
- gets metrics from the document with the highest score
metrics
editmetrics
selects the fields of the "top" document to return. You can request
a single metric with something like "metric": {"field": "m"}
or multiple
metrics by requesting a list of metrics like "metric": [{"field": "m"}, {"field": "i"}
.
Here is a more complete example:
PUT /test { "mappings": { "properties": { "d": {"type": "date"} } } } POST /test/_bulk?refresh {"index": {}} {"s": 1, "m": 3.1415, "i": 1, "d": "2020-01-01T00:12:12Z"} {"index": {}} {"s": 2, "m": 1.0, "i": 6, "d": "2020-01-02T00:12:12Z"} {"index": {}} {"s": 3, "m": 2.71828, "i": -12, "d": "2019-12-31T00:12:12Z"} POST /test/_search?filter_path=aggregations { "aggs": { "tm": { "top_metrics": { "metrics": [ {"field": "m"}, {"field": "i"}, {"field": "d"} ], "sort": {"s": "desc"} } } } }
Which returns:
{ "aggregations": { "tm": { "top": [ { "sort": [3], "metrics": { "m": 2.718280076980591, "i": -12, "d": "2019-12-31T00:12:12.000Z" } } ] } } }
size
edittop_metrics
can return the top few document’s worth of metrics using the size parameter:
POST /test/_bulk?refresh {"index": {}} {"s": 1, "m": 3.1415} {"index": {}} {"s": 2, "m": 1.0} {"index": {}} {"s": 3, "m": 2.71828} POST /test/_search?filter_path=aggregations { "aggs": { "tm": { "top_metrics": { "metrics": {"field": "m"}, "sort": {"s": "desc"}, "size": 3 } } } }
Which returns:
{ "aggregations": { "tm": { "top": [ {"sort": [3], "metrics": {"m": 2.718280076980591 } }, {"sort": [2], "metrics": {"m": 1.0 } }, {"sort": [1], "metrics": {"m": 3.1414999961853027 } } ] } } }
The default size
is 1. The maximum default size is 10
because the aggregation’s
working storage is "dense", meaning we allocate size
slots for every bucket. 10
is a very conservative default maximum and you can raise it if you need to by
changing the top_metrics_max_size
index setting. But know that large sizes can
take a fair bit of memory, especially if they are inside of an aggregation which
makes many buckes like a large
terms aggregation. If
you till want to raise it, use something like:
PUT /test/_settings { "top_metrics_max_size": 100 }
If size
is more than 1
the top_metrics
aggregation can’t be the target of a sort.
Examples
editUse with terms
editThis aggregation should be quite useful inside of terms
aggregation, to, say, find the last value reported by each server.
PUT /node { "mappings": { "properties": { "ip": {"type": "ip"}, "date": {"type": "date"} } } } POST /node/_bulk?refresh {"index": {}} {"ip": "192.168.0.1", "date": "2020-01-01T01:01:01", "m": 1} {"index": {}} {"ip": "192.168.0.1", "date": "2020-01-01T02:01:01", "m": 2} {"index": {}} {"ip": "192.168.0.2", "date": "2020-01-01T02:01:01", "m": 3} POST /node/_search?filter_path=aggregations { "aggs": { "ip": { "terms": { "field": "ip" }, "aggs": { "tm": { "top_metrics": { "metrics": {"field": "m"}, "sort": {"date": "desc"} } } } } } }
Which returns:
{ "aggregations": { "ip": { "buckets": [ { "key": "192.168.0.1", "doc_count": 2, "tm": { "top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 2 } } ] } }, { "key": "192.168.0.2", "doc_count": 1, "tm": { "top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 3 } } ] } } ], "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0 } } }
Unlike top_hits
, you can sort buckets by the results of this metric:
POST /node/_search?filter_path=aggregations { "aggs": { "ip": { "terms": { "field": "ip", "order": {"tm.m": "desc"} }, "aggs": { "tm": { "top_metrics": { "metrics": {"field": "m"}, "sort": {"date": "desc"} } } } } } }
Which returns:
{ "aggregations": { "ip": { "buckets": [ { "key": "192.168.0.2", "doc_count": 1, "tm": { "top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 3 } } ] } }, { "key": "192.168.0.1", "doc_count": 2, "tm": { "top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 2 } } ] } } ], "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0 } } }
Mixed sort types
editSorting top_metrics
by a field that has different types across different
indices producs somewhat suprising results: floating point fields are
always sorted independantly of whole numbered fields.
POST /test/_bulk?refresh {"index": {"_index": "test1"}} {"s": 1, "m": 3.1415} {"index": {"_index": "test1"}} {"s": 2, "m": 1} {"index": {"_index": "test2"}} {"s": 3.1, "m": 2.71828} POST /test*/_search?filter_path=aggregations { "aggs": { "tm": { "top_metrics": { "metrics": {"field": "m"}, "sort": {"s": "asc"} } } } }
Which returns:
{ "aggregations": { "tm": { "top": [ {"sort": [3.0999999046325684], "metrics": {"m": 2.718280076980591 } } ] } } }
While this is better than an error it probably isn’t what you were going for. While it does lose some precision, you can explictly cast the whole number fields to floating points with something like:
POST /test*/_search?filter_path=aggregations { "aggs": { "tm": { "top_metrics": { "metrics": {"field": "m"}, "sort": {"s": {"order": "asc", "numeric_type": "double"}} } } } }
Which returns the much more expected:
{ "aggregations": { "tm": { "top": [ {"sort": [1.0], "metrics": {"m": 3.1414999961853027 } } ] } } }