Adjacency matrix aggregations

The adjacency_matrix aggregation lets you define filter expressions and returns a matrix of the intersecting filters where each non-empty cell in the matrix represents a bucket. You can find how many documents fall within any combination of filters.

Use the adjacency_matrix aggregation to discover how concepts are related by visualizing the data as graphs.

For example, in the sample eCommerce dataset, to analyze how the different manufacturing companies are related:

GET opensearch_dashboards_sample_data_ecommerce/_search
{
  "size": 0,
  "aggs": {
    "interactions": {
      "adjacency_matrix": {
        "filters": {
          "grpA": {
            "match": {
              "manufacturer.keyword": "Low Tide Media"
            }
          },
          "grpB": {
            "match": {
              "manufacturer.keyword": "Elitelligence"
            }
          },
          "grpC": {
            "match": {
              "manufacturer.keyword": "Oceanavigations"
            }
          }
        }
      }
    }
  }
}

{% include copy-curl.html %}

Example response

{
  ...
  "aggregations" : {
    "interactions" : {
      "buckets" : [
        {
          "key" : "grpA",
          "doc_count" : 1553
        },
        {
          "key" : "grpA&grpB",
          "doc_count" : 590
        },
        {
          "key" : "grpA&grpC",
          "doc_count" : 329
        },
        {
          "key" : "grpB",
          "doc_count" : 1370
        },
        {
          "key" : "grpB&grpC",
          "doc_count" : 299
        },
        {
          "key" : "grpC",
          "doc_count" : 1218
        }
      ]
    }
  }
}

Let’s take a closer look at the result:

{
   "key" : "grpA&grpB",
   "doc_count" : 590
}

grpA: Products manufactured by Low Tide Media.
grpB: Products manufactured by Elitelligence.
590: Number of products that are manufactured by both.

You can use OpenSearch Dashboards to represent this data with a network graph.

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Adjacency matrix aggregations

Example response

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