87 lines
2.7 KiB
Plaintext
87 lines
2.7 KiB
Plaintext
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[[search-aggregations-metrics-percentile-rank-aggregation]]
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=== Percentile Ranks Aggregation
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A `multi-value` metrics aggregation that calculates one or more percentile ranks
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over numeric values extracted from the aggregated documents. These values
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can be extracted either from specific numeric fields in the documents, or
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be generated by a provided script.
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[NOTE]
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==================================================
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Please see <<search-aggregations-metrics-percentile-aggregation-approximation>>
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and <<search-aggregations-metrics-percentile-aggregation-compression>> for advice
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regarding approximation and memory use of the percentile ranks aggregation
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==================================================
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Percentile rank show the percentage of observed values which are below certain
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value. For example, if a value is greater than or equal to 95% of the observed values
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it is said to be at the 95th percentile rank.
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Assume your data consists of website load times. You may have a service agreement that
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95% of page loads completely within 15ms and 99% of page loads complete within 30ms.
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Let's look at a range of percentiles representing load time:
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[source,js]
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--------------------------------------------------
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{
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"aggs" : {
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"load_time_outlier" : {
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"percentile_ranks" : {
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"field" : "load_time" <1>
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"values" : [15, 30]
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}
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}
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}
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}
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--------------------------------------------------
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<1> The field `load_time` must be a numeric field
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The response will look like this:
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[source,js]
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--------------------------------------------------
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{
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...
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"aggregations": {
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"load_time_outlier": {
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"values" : {
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"15": 92,
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"30": 100
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}
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}
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}
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}
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--------------------------------------------------
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From this information you can determine you are hitting the 99% load time target but not quite
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hitting the 95% load time target
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==== Script
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The percentile rank metric supports scripting. For example, if our load times
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are in milliseconds but we want to specify values in seconds, we could use
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a script to convert them on-the-fly:
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[source,js]
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--------------------------------------------------
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{
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"aggs" : {
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"load_time_outlier" : {
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"percentile_ranks" : {
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"values" : [3, 5],
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"script" : "doc['load_time'].value / timeUnit", <1>
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"params" : {
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"timeUnit" : 1000 <2>
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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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<1> The `field` parameter is replaced with a `script` parameter, which uses the
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script to generate values which percentile ranks are calculated on
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<2> Scripting supports parameterized input just like any other script
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