Fuzziness allows for tokens to be considered a match even if they are not identical, allowing for typos in the query string.

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Overview

To add fuzziness to a query, cast it to the fuzzy(n) type, where n is the edit distance. Fuzziness is supported for match and term queries. 
-- Fuzzy match disjunction
SELECT id, description
FROM mock_items
WHERE description ||| 'runing shose'::fuzzy(2)
LIMIT 5;

-- Fuzzy match conjunction
SELECT id, description
FROM mock_items
WHERE description &&& 'runing shose'::fuzzy(2)
LIMIT 5;

-- Fuzzy Term
SELECT id, description
FROM mock_items
WHERE description === 'shose'::fuzzy(2)
LIMIT 5;

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How It Works

By default, the match and term queries require exact token matches between the query and indexed text. When a query is cast to fuzzy(n), this requirement is relaxed — tokens are matched if their Levenshtein distance, or edit distance, is less than or equal to n. Edit distance is a measure of how many single-character operations are needed to turn one string into another. The allowed operations are:
  • Insertion adds a character e.g., “shoe” → “shoes” (insert “s”) has an edit distance of 1
  • Deletion removes a character e.g. “runnning” → “running” (delete one “n”) has an edit distance of 1
  • Transposition replaces on character with another e.g., “shose” → “shoes” (transpose “s” → “e”) has an edit distance of 2
For performance reasons, the maximum allowed edit distance is 2.
Casting a query to fuzzy(0) is the same as an exact token match.

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Fuzzy Prefix

fuzzy also supports prefix matching. For instance, “runn” is a prefix of “running” because it matches the beginning of the token exactly. “rann” is a fuzzy prefix of “running” because it matches the beginning within an edit distance of 1. To treat the query string as a prefix, set the second argument of fuzzy to either t or "true": 
SELECT id, description
FROM mock_items
WHERE description === 'rann'::fuzzy(1, t)
LIMIT 5;
Postgres requires that true be double-quoted, i.e. fuzzy(1, "true").
When used with match queries, fuzzy prefix treats all tokens in the query string as prefixes. For instance, the following query means “find all documents containing the fuzzy prefix rann AND the fuzzy prefix slee”: 
SELECT id, description
FROM mock_items
WHERE description &&& 'slee rann'::fuzzy(1, t)
LIMIT 5;

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Transposition Cost

By default, the cost of a transposition (i.e. “shose” → “shoes”) is 2. Setting the third argument of fuzzy to t lowers the cost of a transposition to 1: 
SELECT id, description
FROM mock_items
WHERE description === 'shose'::fuzzy(1, f, t)
LIMIT 5;
The default value for the second and third arguments of fuzzy is f, which means fuzzy(1) is equivalent to fuzzy(1, f, f).