119 lines
4.1 KiB
Plaintext
119 lines
4.1 KiB
Plaintext
[[search-aggregations-metrics-extendedstats-aggregation]]
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=== Extended Stats Aggregation
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A `multi-value` metrics aggregation that computes stats 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.
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The `extended_stats` aggregations is an extended version of the <<search-aggregations-metrics-stats-aggregation,`stats`>> aggregation, where additional metrics are added such as `sum_of_squares`, `variance`, `std_deviation` and `std_deviation_bounds`.
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Assuming the data consists of documents representing exams grades (between 0 and 100) of students
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[source,js]
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--------------------------------------------------
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{
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"aggs" : {
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"grades_stats" : { "extended_stats" : { "field" : "grade" } }
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}
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}
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--------------------------------------------------
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The above aggregation computes the grades statistics over all documents. The aggregation type is `extended_stats` and the `field` setting defines the numeric field of the documents the stats will be computed on. The above will return the following:
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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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"grade_stats": {
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"count": 9,
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"min": 72,
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"max": 99,
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"avg": 86,
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"sum": 774,
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"sum_of_squares": 67028,
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"variance": 51.55555555555556,
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"std_deviation": 7.180219742846005,
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"std_deviation_bounds": {
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"upper": 100.36043948569201,
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"lower": 71.63956051430799
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}
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}
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}
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}
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--------------------------------------------------
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The name of the aggregation (`grades_stats` above) also serves as the key by which the aggregation result can be retrieved from the returned response.
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==== Standard Deviation Bounds
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coming[1.4.3]
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By default, the `extended_stats` metric will return an object called `std_deviation_bounds`, which provides an interval of plus/minus two standard
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deviations from the mean. This can be a useful way to visualize variance of your data. If you want a different boundary, for example
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three standard deviations, you can set `sigma` in the request:
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[source,js]
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--------------------------------------------------
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{
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"aggs" : {
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"grades_stats" : {
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"extended_stats" : {
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"field" : "grade",
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"sigma" : 3 <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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<1> `sigma` controls how many standard deviations +/- from the mean should be displayed coming[1.4.3]
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`sigma` can be any non-negative double, meaning you can request non-integer values such as `1.5`. A value of `0` is valid, but will simply
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return the average for both `upper` and `lower` bounds.
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.Standard Deviation and Bounds require normality
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[NOTE]
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=====
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The standard deviation and its bounds are displayed by default, but they are not always applicable to all data-sets. Your data must
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be normally distributed for the metrics to make sense. The statistics behind standard deviations assumes normally distributed data, so
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if your data is skewed heavily left or right, the value returned will be misleading.
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=====
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==== Script
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Computing the grades stats based on a script:
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[source,js]
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--------------------------------------------------
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{
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...,
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"aggs" : {
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"grades_stats" : { "extended_stats" : { "script" : "doc['grade'].value" } }
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}
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}
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--------------------------------------------------
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===== Value Script
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It turned out that the exam was way above the level of the students and a grade correction needs to be applied. We can use value script to get the new stats:
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[source,js]
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--------------------------------------------------
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{
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"aggs" : {
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...
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"aggs" : {
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"grades_stats" : {
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"extended_stats" : {
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"field" : "grade",
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"script" : "_value * correction",
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"params" : {
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"correction" : 1.2
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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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-------------------------------------------------- |