Aggregations - Upstash Documentation

Aggregations let you compute analytics over your indexed data — metrics like averages, sums, and statistics, as well as bucket-based groupings like terms, ranges, and histograms. They are useful when you want to answer questions like:

“What is the average price?”
“How many unique users do we have?”
“How many orders fall into each price range?”
“How does traffic change per hour/day?”

TypeScript
Python
Redis CLI

const result = await index.aggregate({
  aggregations: {
    avg_price: { $avg: { field: "price" } },
  },
});

result = index.aggregate(
    aggregations={"avg_price": {"$avg": {"field": "price"}}},
)

SEARCH.AGGREGATE products '{}' '{"avg_price": {"$avg": {"field": "price"}}}'

Aggregation requests have two phases:

Document selection: Optional filter selects which documents participate.
Aggregation computation: the selected set is reduced into metric values and/or buckets.

Each aggregation is defined with an alias (the key you choose for the result) and an operator that specifies what to compute.

Response Format

TypeScript
Python
Redis CLI

const result = await index.aggregate({
  aggregations: {
    avg_price: { $avg: { field: "price" } },
    by_category: { $terms: { field: "category", size: 5 } },
  },
});

// result is an object keyed by alias:
// {
//   avg_price: { value: 49.99 },
//   by_category: {
//     buckets: [
//       { key: "electronics", docCount: 42 },
//       { key: "clothing", docCount: 31 },
//     ],
//   },
// }

result = index.aggregate(
    aggregations={
        "avg_price": {"$avg": {"field": "price"}},
        "by_category": {"$terms": {"field": "category", "size": 5}},
    },
)

# result is a dict keyed by alias:
# {
#   "avg_price": {"value": 49.99},
#   "by_category": {
#     "buckets": [
#       {"key": "electronics", "docCount": 42},
#       {"key": "clothing", "docCount": 31},
#     ],
#   },
# }

SEARCH.AGGREGATE products '{}' '{"avg_price": {"$avg": {"field": "price"}}, "by_category": {"$terms": {"field": "category", "size": 5}}}'

# Response (`redis-cli --json`) is an object keyed by alias:
# {"avg_price":{"value":49.99},"by_category":{"buckets":[{"key":"electronics","docCount":42},{"key":"clothing","docCount":31}]}}

Filtering

Use filter to restrict which documents participate in the aggregation. Filtering uses the same query syntax as queries.

TypeScript
Python
Redis CLI

const result = await index.aggregate({
  filter: { inStock: true },
  aggregations: {
    avg_price: { $avg: { field: "price" } },
  },
});

result = index.aggregate(
    filter={"inStock": True},
    aggregations={
        "avg_price": {"$avg": {"field": "price"}},
    },
)

SEARCH.AGGREGATE products '{"inStock": true}' '{"avg_price": {"$avg": {"field": "price"}}}'

Multiple Aggregations in One Request

You can compute multiple top-level aggregations in one call by defining multiple aliases under aggregations. Each alias is computed against the same filtered document set.

TypeScript
Python
Redis CLI

const result = await index.aggregate({
  aggregations: {
    avg_price: { $avg: { field: "price" } },
    price_stats: { $stats: { field: "price" } },
    by_category: { $terms: { field: "category", size: 5 } },
    price_ranges: {
      $range: {
        field: "price",
        ranges: [{ to: 50 }, { from: 50 }],
      },
    },
  },
});

result = index.aggregate(
    aggregations={
        "avg_price": {"$avg": {"field": "price"}},
        "price_stats": {"$stats": {"field": "price"}},
        "by_category": {"$terms": {"field": "category", "size": 5}},
        "price_ranges": {
            "$range": {
                "field": "price",
                "ranges": [{"to": 50}, {"from": 50}],
            }
        },
    },
)

SEARCH.AGGREGATE products '{}' '{"avg_price": {"$avg": {"field": "price"}}, "price_stats": {"$stats": {"field": "price"}}, "by_category": {"$terms": {"field": "category", "size": 5}}, "price_ranges": {"$range": {"field": "price", "ranges": [{"to": 50}, {"from": 50}]}}}'

Nested Aggregations

Bucket operators can include sub-aggregations via $aggs, so you can compute per-bucket metrics.

$terms, $range, $histogram, and $dateHistogram support nested $aggs.
$facet does not support nested $aggs.
Metric operators do not support nested $aggs.

TypeScript
Python
Redis CLI

const result = await index.aggregate({
  aggregations: {
    by_category: {
      $terms: { field: "category" },
      $aggs: {
        avg_price: { $avg: { field: "price" } },
        min_price: { $min: { field: "price" } },
      },
    },
  },
});

result = index.aggregate(
    aggregations={
        "by_category": {
            "$terms": {"field": "category"},
            "$aggs": {
                "avg_price": {"$avg": {"field": "price"}},
                "min_price": {"$min": {"field": "price"}},
            },
        },
    },
)

SEARCH.AGGREGATE products '{}' '{"by_category": {"$terms": {"field": "category"}, "$aggs": {"avg_price": {"$avg": {"field": "price"}}, "min_price": {"$min": {"field": "price"}}}}}'

Operator Families

Metric Aggregations

Metric aggregations return numeric summaries.

Operator	Typical use
`$avg`	Mean value
`$sum`	Total
`$min`	Smallest value
`$max`	Largest value
`$count`	Number of values
`$cardinality`	Number of distinct values
`$stats`	Basic summary stats
`$extendedStats`	Stats + variance/std deviation
`$percentiles`	Distribution cut points

See the metric overview.

Bucket Aggregations

Bucket aggregations partition documents into groups.

Operator	Typical use
`$terms`	Top values by field
`$range`	Custom ranges
`$histogram`	Fixed numeric bins
`$dateHistogram`	Fixed time bins
`$facet`	Hierarchical facets

See the bucket overview.

Redis

Documentation Index

​Response Format

​Filtering

​Multiple Aggregations in One Request

​Nested Aggregations

​Operator Families

​Metric Aggregations

​Bucket Aggregations