- package merkle
-
- import (
- "math/bits"
- )
-
- // HashFromByteSlices computes a Merkle tree where the leaves are the byte slice,
- // in the provided order.
- func HashFromByteSlices(items [][]byte) []byte {
- switch len(items) {
- case 0:
- return nil
- case 1:
- return leafHash(items[0])
- default:
- k := getSplitPoint(int64(len(items)))
- left := HashFromByteSlices(items[:k])
- right := HashFromByteSlices(items[k:])
- return innerHash(left, right)
- }
- }
-
- // HashFromByteSliceIterative is an iterative alternative to
- // HashFromByteSlice motivated by potential performance improvements.
- // (#2611) had suggested that an iterative version of
- // HashFromByteSlice would be faster, presumably because
- // we can envision some overhead accumulating from stack
- // frames and function calls. Additionally, a recursive algorithm risks
- // hitting the stack limit and causing a stack overflow should the tree
- // be too large.
- //
- // Provided here is an iterative alternative, a test to assert
- // correctness and a benchmark. On the performance side, there appears to
- // be no overall difference:
- //
- // BenchmarkHashAlternatives/recursive-4 20000 77677 ns/op
- // BenchmarkHashAlternatives/iterative-4 20000 76802 ns/op
- //
- // On the surface it might seem that the additional overhead is due to
- // the different allocation patterns of the implementations. The recursive
- // version uses a single [][]byte slices which it then re-slices at each level of the tree.
- // The iterative version reproduces [][]byte once within the function and
- // then rewrites sub-slices of that array at each level of the tree.
- //
- // Experimenting by modifying the code to simply calculate the
- // hash and not store the result show little to no difference in performance.
- //
- // These preliminary results suggest:
- //
- // 1. The performance of the HashFromByteSlice is pretty good
- // 2. Go has low overhead for recursive functions
- // 3. The performance of the HashFromByteSlice routine is dominated
- // by the actual hashing of data
- //
- // Although this work is in no way exhaustive, point #3 suggests that
- // optimization of this routine would need to take an alternative
- // approach to make significant improvements on the current performance.
- //
- // Finally, considering that the recursive implementation is easier to
- // read, it might not be worthwhile to switch to a less intuitive
- // implementation for so little benefit.
- func HashFromByteSlicesIterative(input [][]byte) []byte {
- items := make([][]byte, len(input))
-
- for i, leaf := range input {
- items[i] = leafHash(leaf)
- }
-
- size := len(items)
- for {
- switch size {
- case 0:
- return nil
- case 1:
- return items[0]
- default:
- rp := 0 // read position
- wp := 0 // write position
- for rp < size {
- if rp+1 < size {
- items[wp] = innerHash(items[rp], items[rp+1])
- rp += 2
- } else {
- items[wp] = items[rp]
- rp++
- }
- wp++
- }
- size = wp
- }
- }
- }
-
- // getSplitPoint returns the largest power of 2 less than length
- func getSplitPoint(length int64) int64 {
- if length < 1 {
- panic("Trying to split a tree with size < 1")
- }
- uLength := uint(length)
- bitlen := bits.Len(uLength)
- k := int64(1 << uint(bitlen-1))
- if k == length {
- k >>= 1
- }
- return k
- }
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