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"
}
}
}
}
}
}
}
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 Dashboards to represent this data with a network graph.