bloom-filter

I Read this: http://spyced.blogspot.com/2009/01/all-you-ever-wanted-to-know-about.html My Questions: 1.) Is it correct, that Cassandra only uses the bloom filter, to find out the SST (Sorted String Table) which most likely contains the key? As there might be several SSTs and Cassandra does not know in Which SST a key might be? So to speed this up looking in all SSTs bloomfilters are used. Is this correct? (I am trying to understand how cassandra works...) 2.) Why are (as explained in the link above) keys hashed several times? Is it correct that the keys need to be hashed with different Hash

Using Bloom filter, we will be getting space optimization. The cassandra framework also has an implementation of Bloom Filter. But in detail, how is this space optimization achieved? A bloom filter isn't a "framework". It's really more like simply an algorithm. The implementation ain't very long. Here's one in Java I've tried ( .jar , source code and JavaDoc being all available): "Stand alone Java implementations of Cuckoo Hashing and Bloom Filters" (you may want to Google for this in case the following link ain't working anymore): http://lmonson.com/blog/?page_id=99 You can understand how it

Can anyone help me by providing an outline on how the hash function output is mapped to bloom filter indices? Here is an overview on bloomfilters . an outline on how the hash function output is mapped to a bloom filter indices For each of the k hash functions in use, they map onto a bit in the bloom filter just as hashes map onto hash buckets in a hash table. So, very commonly you might have say a hash function generating 32 bit integers, then use the modulus % operator to get a bit index 0 << i < n where n is the number of bits in your bloom filter. To make this very concrete, let's say a

I am struggling to understand the usefulness of the bloom filter. I get its underlying logic, space compaction, fast lookups, false positives etc. I just cannot put that concept into a real-life situation as being beneficial. One frequent application is use of bloom filters in web caching. We use bloom filter to determine whether a given URL is in the cache or not. Why don't we simply access the cache to determine that? If we get a yes, we still need to go to cache to retrieve the webpage (which might not be there), but in case of a no, we could have got the same answer using the cache (which

I'm designing a bloom filter and I'm wondering what the most performant bit array implementation is in Python. The nice thing about Python is that it can handle arbitrary length integers out of the box and that's what I use now, but I don't know enough about Python internals to know if that's the most performant way to do it in Python. I found bitarray but it handles a lot of other things like slicing, which I don't need. I only need the & and | and << operations. The built-in int is pretty nicely optimized, and it already supports & , | , and << . There's at least one alternative