- Available since:
- Time complexity:
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Increments the number stored at
key by one.
If the key does not exist, it is set to
0 before performing the operation.
An error is returned if the key contains a value of the wrong type or contains a
string that can not be represented as integer.
This operation is limited to 64 bit signed integers.
Note: this is a string operation because Redis does not have a dedicated integer type. The string stored at the key is interpreted as a base-10 64 bit signed integer to execute the operation.
Redis stores integers in their integer representation, so for string values that actually hold an integer, there is no overhead for storing the string representation of the integer.
Integer reply: the value of
key after the increment
The counter pattern is the most obvious thing you can do with Redis atomic
The idea is simply send an
INCR command to Redis every time an operation
For instance in a web application we may want to know how many page views this
user did every day of the year.
To do so the web application may simply increment a key every time the user performs a page view, creating the key name concatenating the User ID and a string representing the current date.
This simple pattern can be extended in many ways:
- It is possible to use
EXPIREtogether at every page view to have a counter counting only the latest N page views separated by less than the specified amount of seconds.
- A client may use GETSET in order to atomically get the current counter value and reset it to zero.
- Using other atomic increment/decrement commands like
INCRBYit is possible to handle values that may get bigger or smaller depending on the operations performed by the user. Imagine for instance the score of different users in an online game.
Pattern: Rate limiter
The rate limiter pattern is a special counter that is used to limit the rate at which an operation can be performed. The classical materialization of this pattern involves limiting the number of requests that can be performed against a public API.
We provide two implementations of this pattern using
INCR, where we assume
that the problem to solve is limiting the number of API calls to a maximum of
ten requests per second per IP address.
Pattern: Rate limiter 1
The more simple and direct implementation of this pattern is the following:
FUNCTION LIMIT_API_CALL(ip) ts = CURRENT_UNIX_TIME() keyname = ip+":"+ts MULTI INCR(keyname) EXPIRE(keyname,10) EXEC current = RESPONSE_OF_INCR_WITHIN_MULTI IF current > 10 THEN ERROR "too many requests per second" ELSE PERFORM_API_CALL() END
Basically we have a counter for every IP, for every different second. But this counters are always incremented setting an expire of 10 seconds so that they'll be removed by Redis automatically when the current second is a different one.
Note the used of
EXEC in order to make sure that we'll both
increment and set the expire at every API call.
Pattern: Rate limiter 2
An alternative implementation uses a single counter, but is a bit more complex to get it right without race conditions. We'll examine different variants.
FUNCTION LIMIT_API_CALL(ip): current = GET(ip) IF current != NULL AND current > 10 THEN ERROR "too many requests per second" ELSE value = INCR(ip) IF value == 1 THEN EXPIRE(ip,1) END PERFORM_API_CALL() END
The counter is created in a way that it only will survive one second, starting from the first request performed in the current second. If there are more than 10 requests in the same second the counter will reach a value greater than 10, otherwise it will expire and start again from 0.
In the above code there is a race condition.
If for some reason the client performs the
INCR command but does not perform
EXPIRE the key will be leaked until we'll see the same IP address again.
This can be fixed easily turning the
INCR with optional
EXPIRE into a Lua
script that is send using the
EVAL command (only available since Redis version
local current current = redis.call("incr",KEYS) if current == 1 then redis.call("expire",KEYS,1) end
There is a different way to fix this issue without using scripting, by using Redis lists instead of counters. The implementation is more complex and uses more advanced features but has the advantage of remembering the IP addresses of the clients currently performing an API call, that may be useful or not depending on the application.
FUNCTION LIMIT_API_CALL(ip) current = LLEN(ip) IF current > 10 THEN ERROR "too many requests per second" ELSE IF EXISTS(ip) == FALSE MULTI RPUSH(ip,ip) EXPIRE(ip,1) EXEC ELSE RPUSHX(ip,ip) END PERFORM_API_CALL() END
RPUSHX command only pushes the element if the key already exists.
Note that we have a race here, but it is not a problem:
EXISTS may return
false but the key may be created by another client before we create it inside
However this race will just miss an API call under rare conditions, so the rate
limiting will still work correctly.