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127 lines
4.3 KiB
Markdown
127 lines
4.3 KiB
Markdown
---
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navigation_title: "Adjacency matrix"
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mapped_pages:
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- https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-adjacency-matrix-aggregation.html
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---
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# Adjacency matrix aggregation [search-aggregations-bucket-adjacency-matrix-aggregation]
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A bucket aggregation returning a form of [adjacency matrix](https://en.wikipedia.org/wiki/Adjacency_matrix). The request provides a collection of named filter expressions, similar to the `filters` aggregation request. Each bucket in the response represents a non-empty cell in the matrix of intersecting filters.
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Given filters named `A`, `B` and `C` the response would return buckets with the following names:
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| | A | B | C |
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| --- | --- | --- | --- |
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| A | A | A&B | A&C |
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| B | | B | B&C |
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| C | | | C |
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The intersecting buckets e.g `A&C` are labelled using a combination of the two filter names with a default separator of `&`. Note that the response does not also include a `C&A` bucket as this would be the same set of documents as `A&C`. The matrix is said to be *symmetric* so we only return half of it. To do this we sort the filter name strings and always use the lowest of a pair as the value to the left of the separator.
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## Example [adjacency-matrix-agg-ex]
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The following `interactions` aggregation uses `adjacency_matrix` to determine which groups of individuals exchanged emails.
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$$$adjacency-matrix-aggregation-example$$$
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```console
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PUT emails/_bulk?refresh
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{ "index" : { "_id" : 1 } }
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{ "accounts" : ["hillary", "sidney"]}
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{ "index" : { "_id" : 2 } }
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{ "accounts" : ["hillary", "donald"]}
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{ "index" : { "_id" : 3 } }
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{ "accounts" : ["vladimir", "donald"]}
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GET emails/_search
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{
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"size": 0,
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"aggs" : {
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"interactions" : {
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"adjacency_matrix" : {
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"filters" : {
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"grpA" : { "terms" : { "accounts" : ["hillary", "sidney"] }},
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"grpB" : { "terms" : { "accounts" : ["donald", "mitt"] }},
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"grpC" : { "terms" : { "accounts" : ["vladimir", "nigel"] }}
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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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The response contains buckets with document counts for each filter and combination of filters. Buckets with no matching documents are excluded from the response.
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```console-result
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{
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"took": 9,
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"timed_out": false,
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"_shards": ...,
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"hits": ...,
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"aggregations": {
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"interactions": {
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"buckets": [
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{
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"key":"grpA",
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"doc_count": 2
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},
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{
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"key":"grpA&grpB",
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"doc_count": 1
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},
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{
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"key":"grpB",
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"doc_count": 2
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},
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{
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"key":"grpB&grpC",
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"doc_count": 1
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},
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{
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"key":"grpC",
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"doc_count": 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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```
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## Parameters [adjacency-matrix-agg-params]
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`filters`
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: (Required, object) Filters used to create buckets.
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::::{dropdown} Properties of filters
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`<filter>`
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: (Required, [Query DSL object](/reference/query-languages/querydsl.md)) Query used to filter documents. The key is the filter name.
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At least one filter is required. The total number of filters cannot exceed the [`indices.query.bool.max_clause_count`](/reference/elasticsearch/configuration-reference/search-settings.md#indices-query-bool-max-clause-count) setting. See [Filter limits](#adjacency-matrix-agg-filter-limits).
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::::
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`separator`
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: (Optional, string) Separator used to concatenate filter names. Defaults to `&`.
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## Response body [adjacency-matrix-agg-response]
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`key`
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: (string) Filters for the bucket. If the bucket uses multiple filters, filter names are concatenated using a `separator`.
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`doc_count`
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: (integer) Number of documents matching the bucket’s filters.
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## Usage [adjacency-matrix-agg-usage]
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On its own this aggregation can provide all of the data required to create an undirected weighted graph. However, when used with child aggregations such as a `date_histogram` the results can provide the additional levels of data required to perform [dynamic network analysis](https://en.wikipedia.org/wiki/Dynamic_network_analysis) where examining interactions *over time* becomes important.
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## Filter limits [adjacency-matrix-agg-filter-limits]
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For N filters the matrix of buckets produced can be N²/2 which can be costly. The circuit breaker settings prevent results producing too many buckets and to avoid excessive disk seeks the `indices.query.bool.max_clause_count` setting is used to limit the number of filters.
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