flru

A tiny (215B) and fast Least Recently Used (LRU) cache

Internally, two caches are kept. This is because it's far more performant to swap (and maintain) dictionaries than it is to delete/purge keys on every read/write interaction. Because of this, flru will store 2n items in memory, where n is the max limit. In practice, this means that with max=3 and items (a, b, c) already written, writing a d value will not automatically purge the a key. Instead, a can be retrieved, which would move it to the "active" cache. It's only when this "active" half exceeds the max that the "stale" half is purged.

See Usage for a visual explanation~!

This implementation is optimized for all-around performance – reads, writes, updates, and evictions.

This module is available in three formats:

• ES Module: dist/flru.mjs
• CommonJS: dist/flru.js
• UMD: dist/flru.min.js

Install

$ npm install --save flru

Usage

1// Legend:
2//    S => the stale cache
3//    A => the active cache
4
5const flru = require('flru');
6
7let cache = flru(3); // A=[]        S=[]
8
9cache.set('a', 1);   // A=[a]       S=[]
10cache.set('b', 2);   // A=[a,b]     S=[]
11cache.set('b', 9);   // A=[a,b]     S=[]
12cache.set('c', 3);   // A=[a,b,c]   S=[]
13
14cache.has('a'); //=> true
15
16cache.set('d', 4);   // A=[d]       S=[a,b,c]
17cache.get('a');      // A=[d,a]     S=[a,b,c]
18cache.set('e', 5);   // A=[d,a,e]   S=[a,b,c]
19cache.get('a');      // A=[d,a,e]   S=[a,b,c]
20cache.get('c');      // A=[c]       S=[d,a,e]
21
22cache.has('c'); //=> true
23cache.has('b'); //=> false
24cache.has('a'); //=> true
25
26cache.clear();       // A=[]      S=[]

API

flru(max)

return Object

Initialize a new flru cache instance.

max

Required: true
Type: Number
Default: 1

The maximum number of items to maintain – must be a positive, non-zero integer!

Important: The default value is pointless and will result in excessive computation. It's there only to avoid memory leak!

flru.has(key)

Return: Boolean

Check if the cache has the given key.

key

Type: String

The key name to check.

flru.get(key)

Return: Mixed

Get the assigned value for a given key. Will return undefined if the cache has evicted key or never contained it.

key

Type: String

The item's unique name / identifier.

flru.set(key, value)

Return: undefined

Persist an item to the cache by a given key name.

key

Type: String

The item's unique name / identifier.

value

Type: Mixed

The item's value to be cached.

flru.clear(keepOld)

Return: undefined

Reset the cache(s) and counter.

keepOld

Type: Boolean
Default: false

When true, preserves the stale/outgoing cache.

Important: This is used internally & generally should be ignored!

Benchmarks

You can find benchmarks in the bench directory. They are setup to run one library at a time so that there's no cross-contamination of memory management or Node's runtime caching.

• set – writing values into new keys
• update – updating values into existing keys
• evict – writing 2 * limit keys to the cache, forcing eviction

Results below are with Node v10.13.0

# set()
flru       x 45,261 ops/sec ±1.63% (94 runs sampled)
lru-cache  x 14,240 ops/sec ±5.70% (85 runs sampled)
tmp-cache  x  8,229 ops/sec ±3.06% (83 runs sampled)
tiny-lru   x 24,415 ops/sec ±2.48% (91 runs sampled)

# get()
flru       x 78,585 ops/sec ±1.70% (98 runs sampled)
lru-cache  x 27,409 ops/sec ±2.64% (93 runs sampled)
tmp-cache  x  6,229 ops/sec ±1.06% (87 runs sampled)
tiny-lru   x 20,313 ops/sec ±2.01% (96 runs sampled)

# has()
flru       x  79,843 ops/sec ±1.35% (97 runs sampled)
lru-cache  x  31,354 ops/sec ±2.87% (90 runs sampled)
tmp-cache  x 813,828 ops/sec ±64.67% (95 runs sampled)
tiny-lru   x 128,250 ops/sec ±3.73% (93 runs sampled)

# update()
flru       x 44,885 ops/sec ±1.86% (95 runs sampled)
lru-cache  x 15,616 ops/sec ±2.46% (94 runs sampled)
tmp-cache  x  8,529 ops/sec ±0.85% (87 runs sampled)
tiny-lru   x 23,060 ops/sec ±2.72% (93 runs sampled)

# evict()
flru       x 8,258 ops/sec ±1.48% (88 runs sampled)
lru-cache  x 1,492 ops/sec ±2.60% (77 runs sampled)
tmp-cache  x   836 ops/sec ±0.59% (95 runs sampled)
tiny-lru   x 2,626 ops/sec ±2.61% (81 runs sampled)

Related

• tmp-cache - Full-featured (but slower) alternative, supporting time-sensitive expirations.
• tiny-lru - Same as tmp-cache but significantly faster.

License

MIT © Luke Edwards