Question 1

How to serialize a Bloom filter to a file in Go using bits-and-blooms/bloom?

Accepted Answer

Use the WriteTo and ReadFrom methods with a bytes.Buffer, and wrap file streams with bufio for better performance, as shown in the README's serialization examples. This ensures efficient I/O handling for persistence.

Question 2

bits-and-blooms/bloom vs willf/bloom for Go, which is better?

Accepted Answer

bits-and-blooms/bloom focuses on performance with murmurhash and includes serialization support, while willf/bloom may offer different trade-offs like alternative hash functions. Choose based on your need for speed and features like parameter estimation.

Question 3

What is the actual false positive rate for a given capacity in bits-and-blooms/bloom?

Accepted Answer

Use the EstimateFalsePositiveRate function to compute the actual rate based on m bits and k hash functions, but note it's expensive and clears the filter, so it's best for validation during setup rather than runtime.

Question 4

How to make bits-and-blooms/bloom thread-safe for concurrent access?

Accepted Answer

Implement manual synchronization using sync.Mutex or channels, as the library is unsynchronized by default. The README advises this for goroutine safety when multiple goroutines modify the filter.

Question 5

Can I resize a Bloom filter after creating it with bits-and-blooms/bloom?

Accepted Answer

No, resizing isn't supported; Bloom filters have fixed capacity. You must create a new filter with the desired parameters and migrate data, which can be inefficient for dynamic datasets.

Question 6

How to estimate parameters m and k for a Bloom filter in Go?

Accepted Answer

Use the EstimateParameters function provided by the library, which takes the desired number of elements and false-positive rate to compute optimal m and k values for construction.

bloom

What is bloom?

Overview

Use Cases

Best For

Related Projects

Found a gem we're missing?

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions