Your challenge 30Advanced

Conditional metrics within groups

Restrict the entire search to status active or preorder. Return no hits (size: 0). Build brands with terms on brand.keyword and size 20. Inside each brand create eligible, a filter aggregation requiring in_stock: true AND (rating at least 4 OR no indexed rating). Inside eligible calculate average_price (avg), min_price (min) and max_price (max) on price. Use these exact aggregation names; preserve parent brand counts before eligibility filtering.

The idea

A query filter changes all buckets; a filter aggregation changes only its own bucket and descendants. Keep the status restriction at the top and eligibility inside each brand. Missing and null ratings have no indexed value here: detect them with must_not exists. Group the rating alternatives so an unrated out-of-stock product cannot qualify. Empty eligible buckets have count zero and null metrics.

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Index schemaproducts

id: integer
name: text
brand: text
brand.keyword: keyword
category: keyword
description: text
price: double
rating: float (optional)
in_stock: boolean
status: keyword
created_at: date

query.jsonJSON

{
  "query": {
    "match_all": {}
  }
}

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