Available since: 1.0.5
Time complexity: O(log(N)+M) with N being the number of elements in the sorted set and M the number of elements being returned. If M is constant (e.g. always asking for the first 10 elements with LIMIT), you can consider it O(log(N)).
As of Redis version 6.2.0, this command is regarded as deprecated.
It can be replaced by
ZRANGE with the
BYSCORE argument when migrating or writing new code.
Returns all the elements in the sorted set at
key with a score between
max (including elements with score equal to
The elements are considered to be ordered from low to high scores.
The elements having the same score are returned in lexicographical order (this follows from a property of the sorted set implementation in Redis and does not involve further computation).
LIMIT argument can be used to only get a range of the matching
elements (similar to SELECT LIMIT offset, count in SQL). A negative
returns all elements from the
Keep in mind that if
offset is large, the sorted set needs to be traversed for
offset elements before getting to the elements to return, which can add up to
O(N) time complexity.
WITHSCORES argument makes the command return both the element and
its score, instead of the element alone.
This option is available since Redis 2.0.
max can be
+inf, so that you are not required to know
the highest or lowest score in the sorted set to get all elements from or up to
a certain score.
By default, the interval specified by
max is closed (inclusive).
It is possible to specify an open interval (exclusive) by prefixing the score
with the character
ZRANGEBYSCORE zset (1 5
Will return all elements with
1 < score <= 5 while:
ZRANGEBYSCORE zset (5 (10
Will return all the elements with
5 < score < 10 (5 and 10 excluded).
Array reply: list of elements in the specified score range (optionally with their scores).
ZRANGEBYSCORE is simply used in order to get range of items
where the score is the indexed integer key, however it is possible to do less
obvious things with the command.
For example a common problem when implementing Markov chains and other algorithms is to select an element at random from a set, but different elements may have different weights that change how likely it is they are picked.
This is how we use this command in order to mount such an algorithm:
Imagine you have elements A, B and C with weights 1, 2 and 3. You compute the sum of the weights, which is 1+2+3 = 6
At this point you add all the elements into a sorted set using this algorithm:
SUM = ELEMENTS.TOTAL_WEIGHT // 6 in this case. SCORE = 0 FOREACH ELE in ELEMENTS SCORE += ELE.weight / SUM ZADD KEY SCORE ELE END
This means that you set:
A to score 0.16 B to score .5 C to score 1
Since this involves approximations, in order to avoid C is set to, like, 0.998 instead of 1, we just modify the above algorithm to make sure the last score is 1 (left as an exercise for the reader...).
At this point, each time you want to get a weighted random element,
just compute a random number between 0 and 1 (which is like calling
rand() in most languages), so you can just do:
RANDOM_ELE = ZRANGEBYSCORE key RAND() +inf LIMIT 0 1