143 lines
4.6 KiB
Plaintext
143 lines
4.6 KiB
Plaintext
[[search-aggregations-matrix-stats-aggregation]]
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=== Matrix Stats
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The `matrix_stats` aggregation is a numeric aggregation that computes the following statistics over a set of document fields:
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[horizontal]
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`count`:: Number of per field samples included in the calculation.
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`mean`:: The average value for each field.
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`variance`:: Per field Measurement for how spread out the samples are from the mean.
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`skewness`:: Per field measurement quantifying the asymmetric distribution around the mean.
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`kurtosis`:: Per field measurement quantifying the shape of the distribution.
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`covariance`:: A matrix that quantitatively describes how changes in one field are associated with another.
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`correlation`:: The covariance matrix scaled to a range of -1 to 1, inclusive. Describes the relationship between field
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distributions.
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//////////////////////////
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[source,js]
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--------------------------------------------------
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PUT /statistics/_doc/0
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{"poverty": 24.0, "income": 50000.0}
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PUT /statistics/_doc/1
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{"poverty": 13.0, "income": 95687.0}
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PUT /statistics/_doc/2
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{"poverty": 69.0, "income": 7890.0}
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POST /_refresh
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--------------------------------------------------
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// NOTCONSOLE
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// TESTSETUP
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//////////////////////////
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The following example demonstrates the use of matrix stats to describe the relationship between income and poverty.
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[source,js]
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--------------------------------------------------
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GET /_search
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{
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"aggs": {
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"statistics": {
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"matrix_stats": {
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"fields": ["poverty", "income"]
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[s/_search/_search\?filter_path=aggregations/]
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The aggregation type is `matrix_stats` and the `fields` setting defines the set of fields (as an array) for computing
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the statistics. The above request returns the following response:
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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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"statistics": {
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"doc_count": 50,
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"fields": [{
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"name": "income",
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"count": 50,
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"mean": 51985.1,
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"variance": 7.383377037755103E7,
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"skewness": 0.5595114003506483,
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"kurtosis": 2.5692365287787124,
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"covariance": {
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"income": 7.383377037755103E7,
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"poverty": -21093.65836734694
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},
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"correlation": {
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"income": 1.0,
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"poverty": -0.8352655256272504
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}
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}, {
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"name": "poverty",
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"count": 50,
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"mean": 12.732000000000001,
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"variance": 8.637730612244896,
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"skewness": 0.4516049811903419,
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"kurtosis": 2.8615929677997767,
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"covariance": {
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"income": -21093.65836734694,
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"poverty": 8.637730612244896
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},
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"correlation": {
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"income": -0.8352655256272504,
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"poverty": 1.0
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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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// TESTRESPONSE[s/\.\.\.//]
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// TESTRESPONSE[s/: (\-)?[0-9\.E]+/: $body.$_path/]
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The `doc_count` field indicates the number of documents involved in the computation of the statistics.
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==== Multi Value Fields
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The `matrix_stats` aggregation treats each document field as an independent sample. The `mode` parameter controls what
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array value the aggregation will use for array or multi-valued fields. This parameter can take one of the following:
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[horizontal]
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`avg`:: (default) Use the average of all values.
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`min`:: Pick the lowest value.
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`max`:: Pick the highest value.
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`sum`:: Use the sum of all values.
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`median`:: Use the median of all values.
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==== Missing Values
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The `missing` parameter defines how documents that are missing a value should be treated.
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By default they will be ignored but it is also possible to treat them as if they had a value.
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This is done by adding a set of fieldname : value mappings to specify default values per field.
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[source,js]
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--------------------------------------------------
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GET /_search
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{
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"aggs": {
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"matrixstats": {
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"matrix_stats": {
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"fields": ["poverty", "income"],
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"missing": {"income" : 50000} <1>
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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<1> Documents without a value in the `income` field will have the default value `50000`.
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==== Script
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This aggregation family does not yet support scripting.
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