In Redis, the ZINTER command returns the intersection of the specified sorted sets. In other words, it returns only those members that are present in all sorted sets.

Syntax

The syntax goes like this:

ZINTER numkeys key [key ...] [WEIGHTS weight [weight ...]]
  [AGGREGATE <SUM | MIN | MAX>] [WITHSCORES]

The following examples demonstrate how the arguments are used.

Example

Suppose we create the following sorted sets:

ZADD cats 1 meow 2 fluffy 3 scratch

And:

ZADD dogs 1 bark 2 woof 3 fluffy 4 scratch

Let’s use the ZINTER command to return the intersection of those two sorted sets:

ZINTER 2 cats dogs

Result:

1) "fluffy"
2) "scratch"

As expected, only those members that are in both sorted sets are returned.

Include the Scores

We can use the WITHSCORES argument to include the scores:

ZINTER 2 cats dogs WITHSCORES

Result:

1) "fluffy"
2) "5"
3) "scratch"
4) "7"

By default, the scores for each member are added together from their respective sorted sets. In this example, fluffy has a score of 5 (2 from cats plus 3 from dogs) and scratch has a score of 7 (3 from cats and 4 from dogs)..

The AGGREGATE Argument

In the previous example we saw how the scores were added together to produce an aggregate score. We can change this with the AGGREGATE argument so that it returns either the minimum or maximum score from the original sorted set.

To do this we use the AGGREGATE keyword followed by the option we want to use.

We can use MIN for “minimum”:

ZINTER 2 cats dogs AGGREGATE MIN WITHSCORES

Result:

1) "fluffy"
2) "2"
3) "scratch"
4) "3"

And MAX for “maximum”:

ZINTER 2 cats dogs AGGREGATE MAX WITHSCORES

Result:

1) "fluffy"
2) "3"
3) "scratch"
4) "4"

We can also explicitly state SUM for the default behaviour of adding the scores:

ZINTER 2 cats dogs AGGREGATE SUM WITHSCORES

Result:

1) "fluffy"
2) "5"
3) "scratch"
4) "7"

The WEIGHTS Argument

We can use the WEIGHTS argument to specify a multiplication factor for each input sorted set. This means that the score of every element in the input sorted set is multiplied by this factor before being passed to the aggregation function.

We can apply a different weighting to each sorted set.

Example:

ZINTER 2 cats dogs WEIGHTS 100 100 WITHSCORES

Result:

1) "fluffy"
2) "500"
3) "scratch"
4) "700"

In this example, I specified that the members of both sets should be multiplied by 100 and the result reflects this.

Here’s an example of applying a different weighting to each set:

ZINTER 2 cats dogs WEIGHTS 100 200 WITHSCORES

Result:

1) "fluffy"
2) "800"
3) "scratch"
4) "1100"

This time each element in the cats sorted set was multiplied by 100, while each element in the dogs sorted set was multiplied by 200.

The default multiplication factor is 1.

Wrong Data Type

If any of the keys don’t contain a sorted set, an error occurs:

ZINTER 2 cats country

Result:

(error) WRONGTYPE Operation against a key holding the wrong kind of value

However, non-sorted sets are fine:

ZINTER 2 cats users

Result:

1) "fluffy"
2) "scratch"

In this example, the users key contains a non-sorted set.