Implementing Pagination and Multi‑Condition Fuzzy Query in Redis

Redis is an in‑memory key‑value store that supports data types such as String, List, Set, SortedSet and Hash. Because Redis lacks native fuzzy query capabilities, the article presents a solution for combining pagination and conditional fuzzy search.

Redis Pagination Implementation

Pagination is achieved with the Sorted Set (ZSet) data structure. The relevant commands are:

ZADD ZADD key score member [[score,member]…] – adds members with a score used for ordering.

ZREVRANGE ZREVRANGE key start stop – returns members in a given range, enabling page retrieval.

ZREM ZREM key member – removes a member, useful for deleting comments.

Sorted Sets are well‑suited for pagination because they maintain order and allow score‑based filtering.

Redis Multi‑Condition Fuzzy Query Implementation

Fuzzy queries are built on Hashes. Fields are constructed as <id>:<name>:<gender> and the value stores the full JSON record. The HSCAN command scans all fields with pattern matching, e.g., *:*:male to find all male users or 100*:*:* to match IDs starting with 100.

Matching keys are collected into a Set or List for subsequent data retrieval.

Combination of Pagination and Fuzzy Query

When a query with both pagination and fuzzy conditions is needed, the process is:

Check if a ZSet keyed by the fuzzy pattern already exists.

If not, use HSCAN to collect matching fields, insert them into a new ZSet, and set the pattern as the ZSet key.

If the ZSet exists, perform pagination directly with ZREVRANGE .

This approach avoids scanning the entire dataset on every request.

Performance Optimization

To prevent unlimited ZSet creation, each generated set is given an expiration time based on the principle of temporal locality; accessed sets have their TTL refreshed.

Two strategies keep the sets up‑to‑date:

Insert new Hash entries into all relevant ZSets at write time (requires a naming convention to identify affected sets).

Periodically rebuild ZSets, which is simpler but may lag behind real‑time data.

Summary

The article outlines practical techniques for implementing pagination, multi‑condition fuzzy search, and their combination in Redis, along with suggestions for caching and expiration to maintain performance.

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