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[DOCS] Restructure Aggs documentation
2015-05-01 16:04:55 -04:00
[[search-aggregations-metrics]]
== Metrics Aggregations
The aggregations in this family compute metrics based on values extracted in one way or another from the documents that
are being aggregated. The values are typically extracted from the fields of the document (using the field data), but
can also be generated using scripts.
Numeric metrics aggregations are a special type of metrics aggregation which output numeric values. Some aggregations output
a single numeric metric (e.g. `avg`) and are called `single-value numeric metrics aggregation`, others generate multiple
metrics (e.g. `stats`) and are called `multi-value numeric metrics aggregation`. The distinction between single-value and
multi-value numeric metrics aggregations plays a role when these aggregations serve as direct sub-aggregations of some
bucket aggregations (some bucket aggregations enable you to sort the returned buckets based on the numeric metrics in each bucket).
include::metrics/avg-aggregation.asciidoc[]
Add WeightedAvg metric aggregation (#31037) Adds a new single-value metrics aggregation that computes the weighted average of numeric values that are extracted from the aggregated documents. These values can be extracted 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. In contrast, weighted averages scale 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`. Closes #15731
2018-07-23 18:33:15 -04:00
include::metrics/weighted-avg-aggregation.asciidoc[]
[DOCS] Restructure Aggs documentation
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include::metrics/cardinality-aggregation.asciidoc[]
include::metrics/extendedstats-aggregation.asciidoc[]
include::metrics/geobounds-aggregation.asciidoc[]
Adds geo_centroid metric aggregator This commit adds a new metric aggregator for computing the geo_centroid over a set of geo_point fields. This can be combined with other aggregators (e.g., geohash_grid, significant_terms) for computing the geospatial centroid based on the document sets from other aggregation results.
2015-09-16 17:54:54 -04:00
include::metrics/geocentroid-aggregation.asciidoc[]
[DOCS] Restructure Aggs documentation
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include::metrics/max-aggregation.asciidoc[]
include::metrics/min-aggregation.asciidoc[]
include::metrics/percentile-aggregation.asciidoc[]
include::metrics/percentile-rank-aggregation.asciidoc[]
include::metrics/scripted-metric-aggregation.asciidoc[]
include::metrics/stats-aggregation.asciidoc[]
[7.x] Implement stats aggregation for string terms (#49097) Backport of #47468 to 7.x This PR adds a new metric aggregation called string_stats that operates on string terms of a document and returns the following: min_length: The length of the shortest term max_length: The length of the longest term avg_length: The average length of all terms distribution: The probability distribution of all characters appearing in all terms entropy: The total Shannon entropy value calculated for all terms This aggregation has been implemented as an analytics plugin.
2019-11-15 07:36:21 -05:00
include::metrics/string-stats-aggregation.asciidoc[]
[DOCS] Restructure Aggs documentation
2015-05-01 16:04:55 -04:00
include::metrics/sum-aggregation.asciidoc[]
include::metrics/tophits-aggregation.asciidoc[]
Implement top_metrics agg (#51155) (#52366) The `top_metrics` agg is kind of like `top_hits` but it only works on doc values so it *should* be faster. At this point it is fairly limited in that it only supports a single, numeric sort and a single, numeric metric. And it only fetches the "very topest" document worth of metric. We plan to support returning a configurable number of top metrics, requesting more than one metric and more than one sort. And, eventually, non-numeric sorts and metrics. The trick is doing those things fairly efficiently. Co-Authored by: Zachary Tong <zach@elastic.co>
2020-02-14 11:19:11 -05:00
include::metrics/top-metrics-aggregation.asciidoc[]
[DOCS] Restructure Aggs documentation
2015-05-01 16:04:55 -04:00
include::metrics/valuecount-aggregation.asciidoc[]
median absolute deviation agg (#34482) This commit adds a new single value metric aggregation that calculates the statistic called median absolute deviation, which is a measure of variability that works on more types of data than standard deviation Our calculation of MAD is approximated using t-digests. In the collect phase, we collect each value visited into a t-digest. In the reduce phase, we merge all value t-digests, then create a t-digest of deviations using the first t-digest's median and centroids
2018-10-30 10:22:52 -04:00
include::metrics/median-absolute-deviation-aggregation.asciidoc[]
Add histogram field type support to boxplot aggs (#52265) Add support for the histogram field type to boxplot aggs. Closes #52233 Relates to #33112
2020-02-13 18:09:26 -05:00
include::metrics/boxplot-aggregation.asciidoc[]
[DOCS] Restructure Aggs documentation
2015-05-01 16:04:55 -04:00
[7.x] Add Student's t-test aggregation support (#54469) (#54737) Adds t_test metric aggregation that can perform paired and unpaired two-sample t-tests. In this PR support for filters in unpaired is still missing. It will be added in a follow-up PR. Relates to #53692
2020-04-06 11:36:47 -04:00
include::metrics/t-test-aggregation.asciidoc[]
[DOCS] Restructure Aggs documentation
2015-05-01 16:04:55 -04:00