Filtering - ParadeDB

Adding filters to text search is as simple as using PostgreSQL’s built-in WHERE clauses and operators. For instance, the following query filters out results that do not meet rating > 2.

SELECT description, rating, category
FROM mock_items
WHERE description ||| 'running shoes' AND rating > 2;

import { and, gt } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    description: mockItems.description,
    rating: mockItems.rating,
    category: mockItems.category,
  })
  .from(mockItems)
  .where(
    and(
      search.matchAny(mockItems.description, "running shoes"),
      gt(mockItems.rating, 2),
    ),
  );

from paradedb import MatchAny, ParadeDB

MockItem.objects.filter(
    description=ParadeDB(MatchAny('running shoes')),
    rating__gt=2
).values('description', 'rating', 'category')

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

stmt = (
    select(MockItem.description, MockItem.rating, MockItem.category)
    .where(search.match_any(MockItem.description, "running shoes"), MockItem.rating > 2)
)

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

MockItem.search(:description)
        .match_any("running shoes")
        .where(rating: 3..)
        .select(:description, :rating, :category)

await dbContext
    .MockItems.Where(item =>
        EF.Functions.MatchAny(item.Description, "running shoes") && item.Rating > 2
    )
    .Select(item => new { item.Description, item.Rating, item.Category })
    .ToListAsync();

Filter Pushdown

Non-Text Fields

While not required, filtering performance over non-text columns can be improved by including them in the BM25 index. When these columns are part of the index, WHERE clauses that reference them can be pushed down into the index scan itself. This can result in faster query execution over large datasets. For example, if rating and created_at are frequently used in filters, they can be added to the BM25 index during index creation:

CREATE INDEX search_idx ON mock_items
USING bm25(id, description, rating, created_at)
WITH (key_field = 'id');

Filter pushdown is currently supported for the following combinations of types and operators:

Operator	Left Operand Type	Right Operand Type	Example
`=`, `<`, `>`, `<=`, `>=`, `<>`, `BETWEEN`	`int2`	`int2`	`WHERE rating = 2`
	`int4`	`int4`
	`int8`	`int8`
	`int2`	`int4`
	`int2`	`int8`
	`int4`	`int8`
	`float4`	`float4`
	`float8`	`float8`
	`float4`	`float8`
	`numeric`	`numeric`	`WHERE price = 99.99`
	`date`	`date`
	`time`	`time`
	`timetz`	`timetz`
	`timestamp`	`timestamp`
	`timestamptz`	`timestamptz`
	`uuid`	`uuid`
`=`	`bool`	`bool`	`WHERE in_stock = true`
`IN`, `ANY`, `ALL`	`bool`	`bool[]`	`WHERE rating IN (1,2,3)`
	`int2`	`int2[]`
	`int4`	`int4[]`
	`int8`	`int8[]`
	`int2`	`int4[]`
	`int2`	`int8[]`
	`int4`	`int8[]`
	`float4`	`float4[]`
	`float8`	`float8[]`
	`float4`	`float8[]`
	`date`	`date[]`
	`timetz`	`timetz[]`
	`timestamp`	`timestamp[]`
	`timestamptz`	`timestamptz[]`
	`uuid`	`uuid[]`
`IS`, `IS NOT`	`bool`	`bool`	`WHERE in_stock IS true`
`IS NULL`, `IS NOT NULL`	`bool`		`WHERE rating IS NOT NULL`
	`int2`
	`int4`
	`int8`
	`int2`
	`int2`
	`int4`
	`float4`
	`float8`
	`float4`
	`date`
	`time`
	`timetz`
	`timestamp`
	`timestamptz`
	`uuid`

Text Fields

Suppose we have a text filter that looks for an exact string match like category = 'Footwear':

SELECT description, rating, category
FROM mock_items
WHERE description @@@ 'shoes' AND category = 'Footwear';

import { and, eq } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    description: mockItems.description,
    rating: mockItems.rating,
    category: mockItems.category,
  })
  .from(mockItems)
  .where(
    and(
      search.term(mockItems.description, "shoes"),
      eq(mockItems.category, "Footwear"),
    ),
  );

from paradedb import ParadeDB, Term

MockItem.objects.filter(
    description=ParadeDB(Term('shoes')),
    category='Footwear'
).values('description', 'rating', 'category')

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

stmt = (
    select(MockItem.description, MockItem.rating, MockItem.category)
    .where(search.term(MockItem.description, "shoes"), MockItem.category == "Footwear")
)

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

MockItem.search(:description)
        .term("shoes")
        .where(category: "Footwear")
        .select(:description, :rating, :category)

await dbContext
    .MockItems.Where(item =>
        EF.Functions.Term(item.Description, "shoes") && item.Category == "Footwear"
    )
    .Select(item => new { item.Description, item.Rating, item.Category })
    .ToListAsync();

To push down the category = 'Footwear' filter, category must be indexed using the literal tokenizer:

CREATE INDEX search_idx ON mock_items
USING bm25(id, description, (category::pdb.literal))
WITH (key_field = 'id');

Pushdown of set filters over text fields also requires the literal tokenizer:

SELECT description, rating, category
FROM mock_items
WHERE description @@@ 'shoes' AND category IN ('Footwear', 'Apparel');

import { and, inArray } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    description: mockItems.description,
    rating: mockItems.rating,
    category: mockItems.category,
  })
  .from(mockItems)
  .where(
    and(
      search.term(mockItems.description, "shoes"),
      inArray(mockItems.category, ["Footwear", "Apparel"]),
    ),
  );

from paradedb import ParadeDB, Term

MockItem.objects.filter(
    description=ParadeDB(Term('shoes')),
    category__in=['Footwear', 'Apparel']
).values('description', 'rating', 'category')

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

stmt = (
    select(MockItem.description, MockItem.rating, MockItem.category)
    .where(search.term(MockItem.description, "shoes"), MockItem.category.in_(["Footwear", "Apparel"]))
)

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

MockItem.search(:description)
        .term("shoes")
        .where(category: ["Footwear", "Apparel"])
        .select(:description, :rating, :category)

await dbContext
    .MockItems.Where(item =>
        EF.Functions.Term(item.Description, "shoes")
        && new[] { "Footwear", "Apparel" }.Contains(item.Category)
    )
    .Select(item => new { item.Description, item.Rating, item.Category })
    .ToListAsync();

​Filter Pushdown

​Non-Text Fields

​Text Fields

Filter Pushdown

Non-Text Fields

Text Fields