Cardinality - Paradedb

The cardinality aggregation estimates the number of distinct values in a field.

<CodeGroup> ```sql SQL SELECT pdb.agg('{"cardinality": {"field": "rating"}}') FROM mock_items WHERE id @@@ pdb.all(); ```

import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    agg: search.agg({ cardinality: { field: "rating" } }),
  })
  .from(mockItems)
  .where(search.all(mockItems.id));

python

from paradedb import Agg, All, ParadeDB

MockItem.objects.filter(
    id=ParadeDB(All())
).aggregate(agg=Agg('{"cardinality": {"field": "rating"}}'))

python

from sqlalchemy import select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import pdb, search

stmt = (
    select(pdb.agg({"cardinality": {"field": "rating"}}))
    .select_from(MockItem)
    .where(search.all(MockItem.id))
)

with Session(engine) as session:
    session.execute(stmt).all()

ruby

MockItem.search(:id)
        .match_all
        .facets_agg(agg: { cardinality: { field: "rating" } })

await dbContext
    .MockItems.Where(item => EF.Functions.All(item.Id))
    .Select(item => EF.Functions.Agg(new { cardinality = new { field = "rating" } }))
    .ToListAsync();

</CodeGroup>

ini

      agg
----------------
 {"value": 5.0}
(1 row)

Unlike SQL's DISTINCT clause, which returns an exact value but is very computationally expensive, the cardinality aggregation uses the HyperLogLog++ algorithm to closely approximate the number of distinct values.

See the Tantivy documentation for all available options.