A memoizer using redis as a shared cache, with TTL.
An asynchronous function memoizer for node.js, using redis as the memo store. Memos expire after a specified timeout. Great as a drop-in performance optimization / caching layer for heavy asynchronous functions.
Wikipedia explains it best:
...memoization is an optimization technique used primarily to speed up computer programs by having function calls avoid repeating the calculation of results for previously processed inputs.
var memoize = require"redis-memoizer";// later...done;var memoized = memoizesomeExpensiveOperation;
Now, calls to
memoized will have the same effect as calling
someExpensiveOperation, except it will be much faster. The results of the first call are stored in redis and then looked up for subsequent calls.
Redis effectively serves as a shared network-available cache for function calls. Thus, the memoization cache is available across processes, so that if the same function call is made from different processes they will reuse the cache.
Lets say you are making a DB call that's rather expensive. Let's say you've wrapped the call into a
getUserProfile function that looks as follows:
// Go over to the DB, perform expensive call, get user's profiledoneerr userProfile;
Let's say this call takes 500ms, which is unacceptably high, and you want to make it faster, and don't care about the fact that the value of
userProfile might be slightly outdated (until the cache timeout is hit in redis). You could simply do the following:
var getMemoizedUserProfile = memoizegetUserProfile;getMemoizedUserProfile"user1"// First call. This will take some time.getMemoizedUserProfile"user1"// Second call. This will be blazingly fast.;;
This can similarly be used for any network or disk bound async calls where you are tolerant of slightly outdated values.
var memoize = require"redis-memoizer"redisPort redisHost redisOptions;
Initializes the module with redis' connection parameters. The params are passed along as-is to the node-redis module for connecting to redis.
Memoizes an async function and returns it.
asyncFunctionmust be an asynchronous function that needs to be memoized. The last argument that the asyncFunction takes should be a callback in the usual node style.
timeout(Optional) (Default: 120) is the amount of time in seconds for which the result of the function call should be cached in redis. Once the timeout is hit, the value is deleted from redis automatically. This is done using the redis
setexcommand. The timeout is only set the first time, so the value expires after the timeout time has expired since the first call. The timeout is not reset with every call to the memoized function. Once the value has expired in redis, this module will treat the function call as though it's called the first time again.
timeoutcan alternatively be a function, if you want to dynamically determine the cache time based on the data returned. The returned data will be passed into the timeout function.var httpCallMemoized = memoizemakeHttpCall// return a number based on say response's expires header;httpCallMemoized ;
This module makes some effort to minimize the effect of a cache stampede. If multiple calls are made in quick succession before the first (async) call has completed, only the first call is actually really made. Note that redis will not have been populated at this time yet. Subsequent calls are queued up and are responded to as soon as the result of the first call is available.
Once all the calls have been responded to and the result of the computation is stored in redis, the module then switches to using the computed values from redis.
Note, cache stampedes can still happen if the same function is called from different processes, since the queueing logic described above happens in-memory. For the same set of arguments, you are likely to make as many calls as you have processes.
Use npm to install redis-memoizer:
npm install redis-memoizer
To run the tests, install the dev-dependencies by
node_modules/redis-memoizer and running
npm install once, and then
(The MIT License)
Copyright (c) 2012 Rakesh Pai firstname.lastname@example.org
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