Percentile Ranks Aggregationedit

Added in 1.3.0.

A multi-value metrics aggregation that calculates one or more percentile ranks over numeric values extracted from the aggregated documents. These values can be extracted either from specific numeric fields in the documents, or be generated by a provided script.

Experimental!

This feature is marked as experimental, and may be subject to change in the future. If you use this feature, please let us know your experience with it!

Please see Percentiles are (usually) approximate and Compression for advice regarding approximation and memory use of the percentile ranks aggregation

Percentile rank show the percentage of observed values which are below certain value. For example, if a value is greater than or equal to 95% of the observed values it is said to be at the 95th percentile rank.

Assume your data consists of website load times. You may have a service agreement that 95% of page loads completely within 15ms and 99% of page loads complete within 30ms.

Let’s look at a range of percentiles representing load time:

{
    "aggs" : {
        "load_time_outlier" : {
            "percentile_ranks" : {
                "field" : "load_time", 
                "values" : [15, 30]
            }
        }
    }
}

The field load_time must be a numeric field

The response will look like this:

{
    ...

   "aggregations": {
      "load_time_outlier": {
         "values" : {
            "15": 92,
            "30": 100
         }
      }
   }
}

From this information you can determine you are hitting the 99% load time target but not quite hitting the 95% load time target

Scriptedit

The percentile rank metric supports scripting. For example, if our load times are in milliseconds but we want to specify values in seconds, we could use a script to convert them on-the-fly:

{
    "aggs" : {
        "load_time_outlier" : {
            "percentile_ranks" : {
                "values" : [3, 5],
                "script" : "doc['load_time'].value / timeUnit", 
                "params" : {
                    "timeUnit" : 1000   
                }
            }
        }
    }
}

The field parameter is replaced with a script parameter, which uses the script to generate values which percentile ranks are calculated on

Scripting supports parameterized input just like any other script