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Add moving percentiles pipeline aggregation (#55441)
Similar to what the moving function aggregation does, except merging windows of percentiles sketches together instead of cumulatively merging final metrics
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docs/reference/aggregations/pipeline/moving-percentiles-aggregation.asciidoc
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[role="xpack"] | ||
[testenv="basic"] | ||
[[search-aggregations-pipeline-moving-percentiles-aggregation]] | ||
=== Moving Percentiles Aggregation | ||
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Given an ordered series of <<search-aggregations-metrics-percentile-aggregation, percentiles>>, the Moving Percentile aggregation | ||
will slide a window across those percentiles and allow the user to compute the cumulative percentile. | ||
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This is conceptually very similar to the <<search-aggregations-pipeline-movfn-aggregation, Moving Function>> pipeline aggregation, | ||
except it works on the percentiles sketches instead of the actual buckets values. | ||
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==== Syntax | ||
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A `moving_percentiles` aggregation looks like this in isolation: | ||
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[source,js] | ||
-------------------------------------------------- | ||
{ | ||
"moving_percentiles": { | ||
"buckets_path": "the_percentile", | ||
"window": 10 | ||
} | ||
} | ||
-------------------------------------------------- | ||
// NOTCONSOLE | ||
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[[moving-percentiles-params]] | ||
.`moving_percentiles` Parameters | ||
[options="header"] | ||
|=== | ||
|Parameter Name |Description |Required |Default Value | ||
|`buckets_path` |Path to the percentile of interest (see <<buckets-path-syntax, `buckets_path` Syntax>> for more details |Required | | ||
|`window` |The size of window to "slide" across the histogram. |Required | | ||
|`shift` |<<shift-parameter, Shift>> of window position. |Optional | 0 | ||
|=== | ||
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`moving_percentiles` aggregations must be embedded inside of a `histogram` or `date_histogram` aggregation. They can be | ||
embedded like any other metric aggregation: | ||
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[source,console] | ||
-------------------------------------------------- | ||
POST /_search | ||
{ | ||
"size": 0, | ||
"aggs": { | ||
"my_date_histo":{ <1> | ||
"date_histogram":{ | ||
"field":"date", | ||
"calendar_interval":"1M" | ||
}, | ||
"aggs":{ | ||
"the_percentile":{ <2> | ||
"percentiles":{ | ||
"field": "price", | ||
"percents": [ 1.0, 99.0 ] | ||
} | ||
}, | ||
"the_movperc": { | ||
"moving_percentiles": { | ||
"buckets_path": "the_percentile", <3> | ||
"window": 10 | ||
} | ||
} | ||
} | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// TEST[setup:sales] | ||
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<1> A `date_histogram` named "my_date_histo" is constructed on the "timestamp" field, with one-day intervals | ||
<2> A `percentile` metric is used to calculate the percentiles of a field. | ||
<3> Finally, we specify a `moving_percentiles` aggregation which uses "the_percentile" sketch as its input. | ||
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Moving percentiles are built by first specifying a `histogram` or `date_histogram` over a field. You then add | ||
a percentile metric inside of that histogram. Finally, the `moving_percentiles` is embedded inside the histogram. | ||
The `buckets_path` parameter is then used to "point" at the percentiles aggregation inside of the histogram (see | ||
<<buckets-path-syntax>> for a description of the syntax for `buckets_path`). | ||
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And the following may be the response: | ||
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[source,console-result] | ||
-------------------------------------------------- | ||
{ | ||
"took": 11, | ||
"timed_out": false, | ||
"_shards": ..., | ||
"hits": ..., | ||
"aggregations": { | ||
"my_date_histo": { | ||
"buckets": [ | ||
{ | ||
"key_as_string": "2015/01/01 00:00:00", | ||
"key": 1420070400000, | ||
"doc_count": 3, | ||
"the_percentile": { | ||
"values": { | ||
"1.0": 150.0, | ||
"99.0": 200.0 | ||
} | ||
} | ||
}, | ||
{ | ||
"key_as_string": "2015/02/01 00:00:00", | ||
"key": 1422748800000, | ||
"doc_count": 2, | ||
"the_percentile": { | ||
"values": { | ||
"1.0": 10.0, | ||
"99.0": 50.0 | ||
} | ||
}, | ||
"the_movperc": { | ||
"values": { | ||
"1.0": 150.0, | ||
"99.0": 200.0 | ||
} | ||
} | ||
}, | ||
{ | ||
"key_as_string": "2015/03/01 00:00:00", | ||
"key": 1425168000000, | ||
"doc_count": 2, | ||
"the_percentile": { | ||
"values": { | ||
"1.0": 175.0, | ||
"99.0": 200.0 | ||
} | ||
}, | ||
"the_movperc": { | ||
"values": { | ||
"1.0": 10.0, | ||
"99.0": 200.0 | ||
} | ||
} | ||
} | ||
] | ||
} | ||
} | ||
} | ||
-------------------------------------------------- | ||
// TESTRESPONSE[s/"took": 11/"took": $body.took/] | ||
// TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/] | ||
// TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/] | ||
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The output format of the `moving_percentiles` aggregation is inherited from the format of the referenced | ||
<<search-aggregations-metrics-percentile-aggregation,`percentiles`>> aggregation. | ||
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Moving percentiles pipeline aggregations always run with `skip` gap policy. | ||
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[[moving-percentiles-shift-parameter]] | ||
==== shift parameter | ||
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By default (with `shift = 0`), the window that is offered for calculation is the last `n` values excluding the current bucket. | ||
Increasing `shift` by 1 moves starting window position by `1` to the right. | ||
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- To include current bucket to the window, use `shift = 1`. | ||
- For center alignment (`n / 2` values before and after the current bucket), use `shift = window / 2`. | ||
- For right alignment (`n` values after the current bucket), use `shift = window`. | ||
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If either of window edges moves outside the borders of data series, the window shrinks to include available values only. |
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