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Cache::Memcached::Turnstile - Thundering Herd Protection for Memcached Clients


  use Cache::Memcached::Turnstile qw(:all);
  my $memd_client = Cache::Memcached::Fast->new(...);
  my $value = cache_get_or_compute(
    key          => "foo", # key to fetch
    expiration   => 60,    # [s] expiration to set if need to compute the value
    compute_cb   => sub { ... expensive computation... return $result },
    compute_time => 1,
    wait         => 0.1,
  my $value_hash = multi_cache_get_or_compute(
    key          => [["foo", 60], ["bar", 120]], # key/expiration pairs
    compute_cb   => sub {
      my ($memd_client, $args, $keys_ary) = @_;
      ... expensive computation...
      return \@values;
    compute_time => 1, # approx computation time per key (see below)


This is a prototype of a Thundering-Herd prevention algorithm for memcached. As most such systems, it doesn't play entirely nicely with incompatible modes of access to the same keys, but that's not so much surprise, one would hope. Access to different keys in the same memcached instance through different means is perfectly safe and compatible.

The logic in this module should be compatible with any Memcached client library that has the same API as the Cache::Memcached::Fast module at least for the following methods: get, set, add, gets, cas. It has only been tested with the aforementioned client library.

The Problem Statement

The algorithm described and implemented here attempts to provide means of dealing with two kinds of situations. Most similar systems appear to be targeted at the first and more common situation only:

  1. A hot cached value expires. Between the point in time when it expired and the time when the first user has recomputed the value and successfully filled the cache, all users of the cache will, in a naive cache client implementation, attempt to recalculate the value to store in the cache. This can bring down back-end systems that are not designed to handle the load of all front-ends that rely on the cache[1].

  2. A normal web environment has rather friendly, randomized access patterns. But if your cache has a number of near-synchronized clients that all attempt to access a new cache key in unison (such as when a second or a minute roll around), then some of the mechanisms that can help in situation 1 break down.

The Solution

A very effective approach to deal with most causes of situation 1) is described in [2]. In a nutshell, it's a trade-off in that we accept that for a small amount of time, we will serve data from a stale cache. This small amount of time is the minimum of either: the time it takes for a single process to regenerate a fresh cache value, or a configured safety threshold. This has the effect that when a cache entry has expired, the first to request the cache entry will start reprocessing, and all subsequent accesses (until the reprocessing is done) will use the old, slightly outdated cached data. This is a perfectly valid strategy in many use cases and where extreme accuracy of the cached values is required, it's usually possible to address that either by active invalidation (deleting from memcached) or by simply setting a more stringent expire time.

That approach does not handle situation 2), in which many clients attempt to access a cache entry that didn't previously exist. To my knowledge, there is no generic solution for handling that situation. It will always require application specific knowledge to handle. For this situation, there is a configurable back-off time, or a custom hook interface to intercept such cases and handle them with custom logic.

The Algorithm

Situation 1 from above is handled by always storing a tuple in the cache that includes the real, user-supplied expiration time of the cached value. The expiration time that is set on the cache entry is the sum of the user-supplied expiration time and an upper-bound estimate of the time it takes to recalculate the cached value.

On retrieval of the cache entry (tuple), the client checks whether the real, user-supplied expiration time has passed and if so, it will recalculate the value. Before doing so, it attempts to obtain a lock on the cache entry to prevent others from concurrently also recalculating the same cache entry.

The locking is implemented by setting a flag on the tuple structure in the cache that indicates that the value is already being reprocessed. This can be done race-condition free by using the add, gets, and cas commands supplied by Memcached. With the command that sets the being-reprocessed flag on a tuple, the client always sets an expiration time of the upper-bound of the expected calculation time, thus protecting against indefinitely invalidating the cache when a re-calculation fails, slows, or locks up.

On retrieval of a cache entry that is being reprocessed, other clients than the one doing the reprocessing will continue to return the old cached value. The time this stale value is in use is bounded by the reprocessing time set as expiration above.

There are a number of conditions under which there is no such stale value to use, however, including the first-use of the cache entry and a cache entry that is used rarely enough to expire altogether before a client finds it to be outdated. The pathological variant is one in which a large number of clients concurrently request a cache value that is not available at all (stale or not). In this situation, the remedy is application dependent. By default, all clients but one wait for up to the upper-bound on the time it takes to calculate the cached value. This may result in a slow-down, but no Thundering Herd effect on back-end systems. If a complete failure to provide the cached value is preferrable to a slow-down, then that can be achieved by providing a corresponding custom callback, see below.



I am of the firm (and learned) opinion that when you're in such a situation, your cache is no longer strictly a cache and memcached is no longer the appropriate technology to use.


See and for examples of prior art.



Optionally exports the cache_get_or_compute and multi_cache_get_or_compute functions which are the main API of the module. Also recognizes the standard Exporter semantics, including the :all tag.


This function is the single-key implementation of the Thundering Herd protection. cache_get_or_compute will attempt to fetch or compute the cached value for the given key, and will try really hard to avoid more than one user recomputing the cached value at any given time.

The first argument to cache_get_or_compute needs to be a Memcached client object, typically a Cache::Memcached::Fast object. It's followed by named parameters. The key parameter is required and indicates the Memcached key to retrieve and/or store. The compute_cb parameter needs to be a function reference that will, on cache miss, compute the value to store in the cache and return it. It is invoked as $callback->($memd_client, $parameter_hashref) where $parameter_hashref is a hash reference of all other parameters provided to the cache_get_or_compute call.

The compute_time parameter (in integer seconds) indicates a high estimate of the time it might take to compute the value on cache miss. You can generally be a tad generous on this. It defaults to 2 seconds.

The expiration parameter indicates the desired expiration time for the computed value. It defaults to 0, which is unbounded retention. That is not usually a good idea, so make sure to provide a better value. The unit is seconds from "now" or, if more than 30 days, it's considered a Unix epoch (Memcached rules, not ours).

Finally, the wait parameter can either be a function reference, a number (may be fractional, in unit of seconds), or it may be omitted altogether. If omitted, wait will be set to the compute_time parameter if one was explicitly provided. Otherwise, it defaults to 0.1 seconds to avoid blocking clients too long.

If wait is a number (or it was set to a number as per the aforementioned defaults), and if the running process has a cache miss, but there is another process already updating the cached value, then we will wait for wait number of seconds and retry to fetch (once).

If wait is a function reference, then that function will be called under the conditions we'd otherwise wait & retry. The function is invoked as $wait->($memd_client, $parameter_hashref). Its return value is directly returned from cache_get_or_compute, so if you want logic similar to the wait, then retry logic that is the default, then you could use a callback like the following:

  wait => sub {
    my ($memd_client, $args) = @_;
    # ... custom logic here ...
    # Retry. But don't go into infinite loop, thus the empty callback:
    return cache_get_or_compute($memd_client, %$args, "wait" => sub {return()});


This function is the multi-key implementation of the Thundering Herd protection, that is, it attempts to minimize the number of client-server roundtrips as much as it can and reaches for Memcached's batch interface throughout.

multi_cache_get_or_compute will attempt to fetch or compute the cached value for the each of the keys, and will try really hard to avoid more than one user recomputing any given cached value at any given time. Most of the interface mimicks that of the single-key version as much as possible, but there are some important differences highlighted below. As

keys needs to be a reference to an array containing array references of key/expiration pairs. compute_cb receives an extra, third, parameter as compared to the single-key implementation: A references to an array containing the keys for which values need to be computed. (This list of keys is possibly only a subset of the original set of keys.) The callback needs to return a reference to an array of values which correspond to the computed values for each input key in turn.

The wait parameter works fundamentally the same as in the single-key function, but the callback variant also receives a third parameter: The list of keys whose values weren't available from the cache and couldn't be locked for computation. The callback is expected to return a hash reference of keys and values. This is different from the compute_cb interface to allow for easy calling back into multi_cache_get_or_compute for retries (see the wait example for the single-key implementation above).

As with the single-key variant, compute_time is the additional cached-value life time for a single value, so should at least be an upper bound (or slightly more) on the computation-time for a single key. Alas, there is a trade-off here: Since the implementation seeks to limit the number of roundtrips as much as possible, it will pass all keys-to-be-computed to one run of the compute_cb. This means that the computation time can add up to be significantly more than the single-key compute_time value, so the compute_time parameter may have to be adjusted upwards depending on the situation and relative cost. Failing to do so will result in seeing more hard cache misses on concurrent use as well as an increase in the number of cache entries being recomputed multiple times in parallel, which this module aims to avoid in the first place.

In other words, the rule of thumb for the multi-key interface is: Be somewhat generous on the compute_time setting and provide a separate and appropriate wait time or implementation.


Cache::Memcached::Fast and for examples of prior art.


Steffen Mueller, <>

Rafaël Garcia-Suarez, <<gt>


This module was originally developed for With approval from, this module was generalized and put on CPAN, for which the authors would like to express their gratitude.


 (C) 2013 Steffen Mueller. All rights reserved.
 This code is available under the same license as Perl version
 5.10.1 or higher.
 This program is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of

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