Querying with Facets

Go to the Atlas Search page for your cluster.

1. Click the cluster's name.

2. Click the Atlas Search tab.

   The Atlas Search page displays.

Click Create Index.

Select the Visual Editor configuration method, then click Next.

For the Index Name, type facets.

For the Database and Collection, select the sample_supplies database and the sales collection. Then, click Next.

Click Refine Your Index. In the Index Configuration pane, toggle off Dynamic Mapping.

In the Field Mappings pane, click Add Field Mapping. In the modal window, select purchaseMethod from the Field Name dropdown menu.

From the Data Type dropdown menu, select String. Click Add at the bottom of the modal window. Leave the Index Configurations values unchanged, and click Add at the bottom of the modal window.

In the Field Mappings pane, click Add Field Mapping. In the modal window, select storeLocation from the Field Name dropdown menu.

From the Data Type dropdown, select StringFacet. Click Add at the bottom of the modal window.

Click the Aggregation tab.

Click + Add Stage to begin creating your aggregation pipeline.

In the stage window, click on the dropdown menu labeled Select... and select the $searchMeta stage.

Replace the placeholder code with the following query.

{
   "facet": {
      "operator": {
         "text": {
         "query": ["In store"],
         "path": "purchaseMethod"
         }
      },
      "facets": {
         "locationFacet": {
         "type": "string",
         "path": "storeLocation",
         }
      }
   }
}

This query uses the facet collector with:

• The text operator to count only documents with a purchaseMethod value of In store.

• The facet named locationFacet that creates a bucket for each different storeLocation value.

Review the results of the faceted query.

Your results should resemble the following sample document, which is shown partially expanded:

count: Object
lowerBound: 2819
facet: Object
locationFacet: Object
   buckets: Array
      0: Object
         id: "Denver"
         count: 864
      1: Object
         id: "Seattle"
         count: 648
      2: Object
      3: Object
      4: Object
      5: Object

You can expand Array and Object fields to view their contents by clicking on them.