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This is used when the `top_hits` output is passed to pipeline aggregators like bucket selectors. The logic retrieves the requested field from the source of the first SearchHit. This implies that (a) the spec of the wrapping aggregator (e.g. `bucket_path`) points to an appropriate field using a bracketed reference (e.g. `my_top_hits[my_metric]`) and (b) the `top_hits` contains a `size: 1` setting. This PR also includes extensions to YAML tests for `top_metrics` and `top_hits` to cover the cases where these are used in pipeline aggregations through `bucket_selector`, similar to a HAVING clause in SQL. Related to https://github.com/elastic/elasticsearch/issues/73429.
459 lines
10 KiB
Text
459 lines
10 KiB
Text
[role="xpack"]
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[[search-aggregations-metrics-top-metrics]]
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=== Top metrics aggregation
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++++
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<titleabbrev>Top metrics</titleabbrev>
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++++
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The `top_metrics` aggregation selects metrics from the document with the largest or smallest "sort"
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value. For example, this gets the value of the `m` field on the document with the largest value of `s`:
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[source,console,id=search-aggregations-metrics-top-metrics-simple]
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----
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POST /test/_bulk?refresh
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{"index": {}}
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{"s": 1, "m": 3.1415}
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{"index": {}}
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{"s": 2, "m": 1.0}
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{"index": {}}
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{"s": 3, "m": 2.71828}
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POST /test/_search?filter_path=aggregations
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{
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"s": "desc"}
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}
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}
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}
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}
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----
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Which returns:
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[source,js]
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----
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{
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"aggregations": {
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"tm": {
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"top": [ {"sort": [3], "metrics": {"m": 2.718280076980591 } } ]
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}
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}
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}
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----
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// TESTRESPONSE
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`top_metrics` is fairly similar to <<search-aggregations-metrics-top-hits-aggregation, `top_hits`>>
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in spirit but because it is more limited it is able to do its job using less memory and is often
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faster.
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==== `sort`
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The `sort` field in the metric request functions exactly the same as the `sort` field in the
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<<sort-search-results, search>> request except:
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* It can't be used on <<binary,binary>>, <<flattened,flattened>>, <<ip,ip>>,
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<<keyword,keyword>>, or <<text,text>> fields.
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* It only supports a single sort value so which document wins ties is not specified.
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The metrics that the aggregation returns is the first hit that would be returned by the search
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request. So,
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`"sort": {"s": "desc"}`:: gets metrics from the document with the highest `s`
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`"sort": {"s": "asc"}`:: gets the metrics from the document with the lowest `s`
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`"sort": {"_geo_distance": {"location": "POINT (-78.6382 35.7796)"}}`::
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gets metrics from the documents with `location` *closest* to `35.7796, -78.6382`
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`"sort": "_score"`:: gets metrics from the document with the highest score
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==== `metrics`
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`metrics` selects the fields of the "top" document to return. You can request
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a single metric with something like `"metrics": {"field": "m"}` or multiple
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metrics by requesting a list of metrics like `"metrics": [{"field": "m"}, {"field": "i"}`.
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`metrics.field` supports the following field types:
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* <<boolean,`boolean`>>
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* <<ip,`ip`>>
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* <<keyword,keywords>>
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* <<number,numbers>>
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Except for keywords, <<runtime,runtime fields>> for corresponding types are also
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supported. `metrics.field` doesn't support fields with <<array,array values>>. A
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`top_metric` aggregation on array values may return inconsistent results.
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The following example runs a `top_metrics` aggregation on several field types.
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[source,console,id=search-aggregations-metrics-top-metrics-list-of-metrics]
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----
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PUT /test
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{
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"mappings": {
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"properties": {
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"d": {"type": "date"}
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}
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}
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}
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POST /test/_bulk?refresh
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{"index": {}}
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{"s": 1, "m": 3.1415, "i": 1, "d": "2020-01-01T00:12:12Z", "t": "cat"}
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{"index": {}}
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{"s": 2, "m": 1.0, "i": 6, "d": "2020-01-02T00:12:12Z", "t": "dog"}
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{"index": {}}
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{"s": 3, "m": 2.71828, "i": -12, "d": "2019-12-31T00:12:12Z", "t": "chicken"}
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POST /test/_search?filter_path=aggregations
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{
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": [
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{"field": "m"},
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{"field": "i"},
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{"field": "d"},
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{"field": "t.keyword"}
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],
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"sort": {"s": "desc"}
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}
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}
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}
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}
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----
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Which returns:
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[source,js]
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----
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{
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"aggregations": {
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"tm": {
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"top": [ {
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"sort": [3],
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"metrics": {
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"m": 2.718280076980591,
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"i": -12,
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"d": "2019-12-31T00:12:12.000Z",
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"t.keyword": "chicken"
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}
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} ]
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}
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}
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}
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----
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// TESTRESPONSE
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==== `size`
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`top_metrics` can return the top few document's worth of metrics using the size parameter:
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[source,console,id=search-aggregations-metrics-top-metrics-size]
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----
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POST /test/_bulk?refresh
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{"index": {}}
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{"s": 1, "m": 3.1415}
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{"index": {}}
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{"s": 2, "m": 1.0}
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{"index": {}}
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{"s": 3, "m": 2.71828}
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POST /test/_search?filter_path=aggregations
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{
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"s": "desc"},
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"size": 3
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}
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}
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}
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}
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----
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Which returns:
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[source,js]
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----
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{
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"aggregations": {
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"tm": {
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"top": [
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{"sort": [3], "metrics": {"m": 2.718280076980591 } },
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{"sort": [2], "metrics": {"m": 1.0 } },
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{"sort": [1], "metrics": {"m": 3.1414999961853027 } }
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]
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}
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}
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}
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----
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// TESTRESPONSE
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The default `size` is 1. The maximum default size is `10` because the aggregation's
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working storage is "dense", meaning we allocate `size` slots for every bucket. `10`
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is a *very* conservative default maximum and you can raise it if you need to by
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changing the `top_metrics_max_size` index setting. But know that large sizes can
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take a fair bit of memory, especially if they are inside of an aggregation which
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makes many buckes like a large
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<<search-aggregations-metrics-top-metrics-example-terms, terms aggregation>>. If
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you till want to raise it, use something like:
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[source,console]
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----
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PUT /test/_settings
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{
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"top_metrics_max_size": 100
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}
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----
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// TEST[continued]
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NOTE: If `size` is more than `1` the `top_metrics` aggregation can't be the *target* of a sort.
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==== Examples
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[[search-aggregations-metrics-top-metrics-example-terms]]
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===== Use with terms
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This aggregation should be quite useful inside of <<search-aggregations-bucket-terms-aggregation, `terms`>>
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aggregation, to, say, find the last value reported by each server.
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[source,console,id=search-aggregations-metrics-top-metrics-terms]
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----
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PUT /node
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{
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"mappings": {
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"properties": {
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"ip": {"type": "ip"},
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"date": {"type": "date"}
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}
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}
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}
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POST /node/_bulk?refresh
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{"index": {}}
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{"ip": "192.168.0.1", "date": "2020-01-01T01:01:01", "m": 1}
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{"index": {}}
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{"ip": "192.168.0.1", "date": "2020-01-01T02:01:01", "m": 2}
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{"index": {}}
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{"ip": "192.168.0.2", "date": "2020-01-01T02:01:01", "m": 3}
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POST /node/_search?filter_path=aggregations
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{
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"aggs": {
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"ip": {
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"terms": {
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"field": "ip"
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},
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"date": "desc"}
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}
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}
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}
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}
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}
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}
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----
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Which returns:
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[source,js]
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----
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{
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"aggregations": {
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"ip": {
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"buckets": [
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{
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"key": "192.168.0.1",
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"doc_count": 2,
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"tm": {
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"top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 2 } } ]
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}
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},
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{
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"key": "192.168.0.2",
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"doc_count": 1,
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"tm": {
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"top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 3 } } ]
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}
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}
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],
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"doc_count_error_upper_bound": 0,
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"sum_other_doc_count": 0
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}
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}
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}
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----
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// TESTRESPONSE
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Unlike `top_hits`, you can sort buckets by the results of this metric:
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[source,console]
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----
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POST /node/_search?filter_path=aggregations
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{
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"aggs": {
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"ip": {
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"terms": {
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"field": "ip",
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"order": {"tm.m": "desc"}
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},
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"date": "desc"}
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}
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}
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}
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}
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}
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}
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----
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// TEST[continued]
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Which returns:
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[source,js]
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----
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{
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"aggregations": {
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"ip": {
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"buckets": [
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{
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"key": "192.168.0.2",
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"doc_count": 1,
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"tm": {
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"top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 3 } } ]
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}
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},
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{
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"key": "192.168.0.1",
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"doc_count": 2,
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"tm": {
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"top": [ {"sort": ["2020-01-01T02:01:01.000Z"], "metrics": {"m": 2 } } ]
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}
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}
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],
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"doc_count_error_upper_bound": 0,
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"sum_other_doc_count": 0
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}
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}
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}
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----
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// TESTRESPONSE
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===== Mixed sort types
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Sorting `top_metrics` by a field that has different types across different
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indices producs somewhat surprising results: floating point fields are
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always sorted independently of whole numbered fields.
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[source,console,id=search-aggregations-metrics-top-metrics-mixed-sort]
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----
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POST /test/_bulk?refresh
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{"index": {"_index": "test1"}}
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{"s": 1, "m": 3.1415}
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{"index": {"_index": "test1"}}
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{"s": 2, "m": 1}
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{"index": {"_index": "test2"}}
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{"s": 3.1, "m": 2.71828}
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POST /test*/_search?filter_path=aggregations
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{
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"s": "asc"}
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}
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}
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}
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}
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----
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Which returns:
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[source,js]
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----
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{
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"aggregations": {
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"tm": {
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"top": [ {"sort": [3.0999999046325684], "metrics": {"m": 2.718280076980591 } } ]
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}
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}
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}
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----
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// TESTRESPONSE
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While this is better than an error it *probably* isn't what you were going for.
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While it does lose some precision, you can explicitly cast the whole number
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fields to floating points with something like:
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[source,console]
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----
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POST /test*/_search?filter_path=aggregations
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{
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"s": {"order": "asc", "numeric_type": "double"}}
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}
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}
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}
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}
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----
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// TEST[continued]
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Which returns the much more expected:
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[source,js]
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----
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{
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"aggregations": {
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"tm": {
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"top": [ {"sort": [1.0], "metrics": {"m": 3.1414999961853027 } } ]
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}
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}
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}
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----
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// TESTRESPONSE
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===== Use in pipeline aggregations
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`top_metrics` can be used in pipeline aggregations that consume a single value per bucket, such as `bucket_selector`
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that applies per bucket filtering, similar to using a HAVING clause in SQL. This requires setting `size` to 1, and
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specifying the right path for the (single) metric to be passed to the wrapping aggregator. For example:
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[source,console]
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----
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POST /test*/_search?filter_path=aggregations
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{
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"aggs": {
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"ip": {
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"terms": {
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"field": "ip"
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},
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"aggs": {
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"tm": {
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"top_metrics": {
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"metrics": {"field": "m"},
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"sort": {"s": "desc"},
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"size": 1
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}
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},
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"having_tm": {
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"bucket_selector": {
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"buckets_path": {
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"top_m": "tm[m]"
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},
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"script": "params.top_m < 1000"
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}
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}
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}
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}
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}
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}
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----
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// TEST[continued]
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The `bucket_path` uses the `top_metrics` name `tm` and a keyword for the metric providing the aggregate value,
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namely `m`.
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