Redis ZINTERSTORE in Python (Detailed Guide w/ Code Examples)

Use Case(s)

The ZINTERSTORE command in Redis is used to compute the intersection of multiple sorted sets, and the resulting set is stored in a new sorted set. This feature is commonly used in scenarios where you need to find common elements across different datasets with their corresponding scores, such as:

  • Finding users with common interests or traits in social networking sites.
  • Combining ranked results from various features in recommendation engines.
  • Aggregating scores from different gaming levels or events.

Code Examples

Basic Example of ZINTERSTORE

In this example, we'll intersect two sorted sets for user rankings from different games and store the results in a new sorted set.

import redis # Establish a connection to Redis client = redis.Redis(host='localhost', port=6379, db=0) # Add some elements to the first sorted set client.zadd('game1_scores', {'Alice': 250, 'Bob': 150, 'Charlie': 300}) # Add some elements to the second sorted set client.zadd('game2_scores', {'Alice': 300, 'Bob': 200, 'David': 250}) # Intersect both sets and store the result in a new set client.zinterstore('combined_scores', ['game1_scores', 'game2_scores']) # Retrieve and print the combined scores print(client.zrange('combined_scores', 0, -1, withscores=True))

This script first creates two sorted sets with scores from two different games. It then uses ZINTERSTORE to find the intersection of these two sets and stores the result in combined_scores. Finally, it retrieves and prints the combined scores.

Weighted Intersection

You can also apply weights to the scores in the input sorted sets during intersection, which can be useful for prioritizing one set over another.

# Intersect both sets with different weights and store the result client.zinterstore('weighted_combined_scores', {'game1_scores': 1, 'game2_scores': 2}) # Retrieve and print the weighted combined scores print(client.zrange('weighted_combined_scores', 0, -1, withscores=True))

Here, the scores from game2_scores are considered twice as important as those from game1_scores because of the weight factor of 2.

Best Practices

  • Key Naming Convention: Use meaningful names for the keys that reflect their content and purpose to make the database easier to understand and maintain.
  • Memory Management: Be cautious about the size of the resulting sorted set, as Redis holds all its data in-memory. Regularly monitor and manage memory usage, especially when dealing with large sets.

Common Mistakes

  • Overwriting Existing Keys: Be aware that using ZINTERSTORE will overwrite any existing key with the same name without warning. Always check for key existence if overwrites are a concern.
  • Ignoring Return Values: ZINTERSTORE returns the number of elements in the resulting set. Ignoring this value can lead to missed opportunities for error handling or further processing based on the size of the output set.


Q: What happens if one of the input sorted sets doesn't exist?
A: If any of the input sorted sets do not exist, Redis assumes it as an empty set, and hence the resulting set will also be empty.

Q: Can I use ZINTERSTORE with regular sets?
A: No, ZINTERSTORE works only with sorted sets. Regular sets should use commands like SINTERSTORE for similar operations.

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