Weighted Avg Aggregationedit
A singlevalue
metrics aggregation that computes the weighted average of numeric values that are extracted from the aggregated documents.
These values can be extracted either from specific numeric fields in the documents.
When calculating a regular average, each datapoint has an equal "weight" … it contributes equally to the final value. Weighted averages, on the other hand, weight each datapoint differently. The amount that each datapoint contributes to the final value is extracted from the document, or provided by a script.
As a formula, a weighted average is the ∑(value * weight) / ∑(weight)
A regular average can be thought of as a weighted average where every value has an implicit weight of 1
.
Table 3. weighted_avg
Parameters
Parameter Name  Description  Required  Default Value 


The configuration for the field or script that provides the values 
Required 


The configuration for the field or script that provides the weights 
Required 


The numeric response formatter 
Optional 


A hint about the values for pure scripts or unmapped fields 
Optional 
The value
and weight
objects have perfield specific configuration:
Table 4. value
Parameters
Parameter Name  Description  Required  Default Value 


The field that values should be extracted from 
Required 


A value to use if the field is missing entirely 
Optional 
Table 5. weight
Parameters
Parameter Name  Description  Required  Default Value 


The field that weights should be extracted from 
Required 


A weight to use if the field is missing entirely 
Optional 
Examplesedit
If our documents have a "grade"
field that holds a 0100 numeric score, and a "weight"
field which holds an arbitrary numeric weight,
we can calculate the weighted average using:
POST /exams/_search { "size": 0, "aggs": { "weighted_grade": { "weighted_avg": { "value": { "field": "grade" }, "weight": { "field": "weight" } } } } }
Which yields a response like:
{ ... "aggregations": { "weighted_grade": { "value": 70.0 } } }
While multiple valuesperfield are allowed, only one weight is allowed. If the aggregation encounters
a document that has more than one weight (e.g. the weight field is a multivalued field) it will throw an exception.
If you have this situation, you will need to specify a script
for the weight field, and use the script
to combine the multiple values into a single value to be used.
This single weight will be applied independently to each value extracted from the value
field.
This example show how a single document with multiple values will be averaged with a single weight:
POST /exams/_doc?refresh { "grade": [1, 2, 3], "weight": 2 } POST /exams/_search { "size": 0, "aggs": { "weighted_grade": { "weighted_avg": { "value": { "field": "grade" }, "weight": { "field": "weight" } } } } }
The three values (1
, 2
, and 3
) will be included as independent values, all with the weight of 2
:
{ ... "aggregations": { "weighted_grade": { "value": 2.0 } } }
The aggregation returns 2.0
as the result, which matches what we would expect when calculating by hand:
((1*2) + (2*2) + (3*2)) / (2+2+2) == 2
Scriptedit
Both the value and the weight can be derived from a script, instead of a field. As a simple example, the following will add one to the grade and weight in the document using a script:
POST /exams/_search { "size": 0, "aggs": { "weighted_grade": { "weighted_avg": { "value": { "script": "doc.grade.value + 1" }, "weight": { "script": "doc.weight.value + 1" } } } } }
Missing valuesedit
The missing
parameter defines how documents that are missing a value should be treated.
The default behavior is different for value
and weight
:
By default, if the value
field is missing the document is ignored and the aggregation moves on to the next document.
If the weight
field is missing, it is assumed to have a weight of 1
(like a normal average).
Both of these defaults can be overridden with the missing
parameter:
POST /exams/_search { "size": 0, "aggs": { "weighted_grade": { "weighted_avg": { "value": { "field": "grade", "missing": 2 }, "weight": { "field": "weight", "missing": 3 } } } } }