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Most aggregations (terms, histogram, stats, percentiles, geohash-grid) now support a new `missing` option which defines the value to consider when a field does not have a value. This can be handy if you eg. want a terms aggregation to handle the same way documents that have "N/A" or no value for a `tag` field. This works in a very similar way to the `missing` option on the `sort` element. One known issue is that this option sometimes cannot make the right decision in the unmapped case: it needs to replace all values with the `missing` value but might not know what kind of values source should be produced (numerics, strings, geo points?). For this reason, we might want to add an `unmapped_type` option in the future like we did for sorting. Related to #5324
142 lines
4.8 KiB
Plaintext
142 lines
4.8 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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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
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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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TIP: The `script` parameter expects an inline script. Use `script_id` for indexed scripts and `script_file` for scripts in the `config/scripts/` directory.
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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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--------------------------------------------------
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==== Missing value
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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
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had a value.
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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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"missing": 0 <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> Documents without a value in the `grade` field will fall into the same bucket as documents that have the value `0`.
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