Matrix stats aggregation
editMatrix stats aggregation
editThe matrix_stats aggregation is a numeric aggregation that computes the following statistics over a set of document fields:
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Number of per field samples included in the calculation. |
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The average value for each field. |
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Per field Measurement for how spread out the samples are from the mean. |
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Per field measurement quantifying the asymmetric distribution around the mean. |
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Per field measurement quantifying the shape of the distribution. |
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A matrix that quantitatively describes how changes in one field are associated with another. |
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The covariance matrix scaled to a range of -1 to 1, inclusive. Describes the relationship between field distributions. |
Unlike other metric aggregations, the matrix_stats aggregation does
not support scripting.
The following example demonstrates the use of matrix stats to describe the relationship between income and poverty.
GET /_search
{
"aggs": {
"statistics": {
"matrix_stats": {
"fields": [ "poverty", "income" ]
}
}
}
}
The aggregation type is matrix_stats and the fields setting defines the set of fields (as an array) for computing
the statistics. The above request returns the following response:
{
...
"aggregations": {
"statistics": {
"doc_count": 50,
"fields": [ {
"name": "income",
"count": 50,
"mean": 51985.1,
"variance": 7.383377037755103E7,
"skewness": 0.5595114003506483,
"kurtosis": 2.5692365287787124,
"covariance": {
"income": 7.383377037755103E7,
"poverty": -21093.65836734694
},
"correlation": {
"income": 1.0,
"poverty": -0.8352655256272504
}
}, {
"name": "poverty",
"count": 50,
"mean": 12.732000000000001,
"variance": 8.637730612244896,
"skewness": 0.4516049811903419,
"kurtosis": 2.8615929677997767,
"covariance": {
"income": -21093.65836734694,
"poverty": 8.637730612244896
},
"correlation": {
"income": -0.8352655256272504,
"poverty": 1.0
}
} ]
}
}
}
The doc_count field indicates the number of documents involved in the computation of the statistics.
Multi Value Fields
editThe matrix_stats aggregation treats each document field as an independent sample. The mode parameter controls what
array value the aggregation will use for array or multi-valued fields. This parameter can take one of the following:
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(default) Use the average of all values. |
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Pick the lowest value. |
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Pick the highest value. |
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Use the sum of all values. |
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Use the median of all values. |
Missing Values
editThe missing parameter defines how documents that are missing a value should be treated.
By default they will be ignored but it is also possible to treat them as if they had a value.
This is done by adding a set of fieldname : value mappings to specify default values per field.