Yet another Bloom filter implementation for node.js. Everybody has to write one, as you know. Backed by Xxhash via node-xxhash. Xxhash is a fast general-purpose hash, which is all a bloom filter needs. Three variations are provided: a straight Bloom filter, a counting filter (from which items can be removed), and a straight Bloom filter backed by redis. The first two have synchronous APIs. The redis one perforce requires callbacks.
To install: npm install bloomxx
To create a filter, pass an options hash to the constructor:
var options =
{
bits: 1024,
hashes: 7,
seeds: [1, 2, 3, 4, 5, 6, 7]
};
filter = new BloomFilter(options);
You can pass in seeds for the hash functions if you like, or they'll be randomly generated. Seeds must be integers.
To create a filter optimized for the number of items you'll be storing and a desired error rate:
filter = BloomFilter.createOptimal(estimatedItemCount, errorRate);
The error rate parameter is optional. It defaults to 0.005, or a 0.5% rate.
filter.add('cat');
Adds the given item to the filter. Can also accept buffers and arrays containing strings or buffers:
filter.add(['cat', 'dog', 'coati', 'red panda']);
To test for membership:
filter.has('dog');
To clear the filter:
filter.clear();
Uses about 8 times as much space as the regular filter. Basic usage is exactly the same as the plain Bloom filter:
filter = new CountingFilter({ hashes: 8, bits: 1024 });`
filter2 = CountingFilter.createOptimal(estimatedItemCount, optionalErrorRate);
Add a list, test for membership, then remove:
filter.add(['cat', 'dog', 'coati', 'red panda']);
filter.has('cat'); // returns true
filter.remove('cat');
filter.has('cat'); // returns false most of the time
The counting filter tracks its overflow count in filter.overflow
. Overflow will be non-zero if any bit has been set more than 255 times. Once the filter has overflowed, removing items is no longer reliable.
Check for overflow:
filter.hasOverflowed(); // returns boolean
filter.overflow; // integer count of number of times overflow occurred
This is a plain vanilla bloom filter backed by redis. Its api is asychronous.
RedisFilter.createOrRead({
key: 'cats', // the key used to store data in redis; will also set 'cats:meta'
bits: 1024, // filter size in bits
hashes: 8, // number of hash functions
redis: redis.createClient(port, host) // redis client to use
}, function(err, filter)
{
filter.add(['cat', 'jaguar', 'lion', 'tiger', 'leopard'], function(err)
{
filter.has('caracal', function(err, result)
{
assert(result === false);
});
});
});
The options hash can also specify host
and port
, which will be used to create a redis client. createOrRead()
will attempt to find a filter saved at the given key and create one if it isn't found.
Returns a filter sized for the given item count and desired error rate, with other options as specified in the options
hash.
Clear all bits.
Delete the filter from redis.
MIT.