github.com/iotaledger/trie.go

trie.go

Go library for implementations of sparse tries (sparse radix trees), state commitments and proof of inclusion for large mutable data sets with variable size keys.

The mutable state model is assumed as a main use case, but not limited to it. By mutable state we assume a large key/value data set which is frequently updated by adding, modifying and deleting key/value pairs. The application is only interested in the latest (current) state of the mutable state and the commitment to it.

The trie.go package allows efficient and deterministic recalculation of the commitment tree of the data set upon each batch of mutations with minimum overhead, in a logarithmic time.

The trie update and proof retrieval operations are highly optimized via caching access to the database. It buffers trie updates up until the trie is committed (recalculated). It saves a lot of DB interactions and a lot of cryptographic operations (hashing or curve arithmetics).

This mutable commitment tree model extends append only commitment tree model often used in blockchains, where commitment tree is augmented each time by linearly appending new block with its Merkle tree to the branch of block headers. The former is much less redundant and more efficient in high throughput systems when state is mutated with large blocks (batches of state mutations) each few seconds.

Note that variable size keys implies terminal value can be stored in a key which is a prefix of another key. This trait makes the state hierarchical, i.e. with sub-states of key/value collection where all keys share same prefix.

trie.go implements a generic 256+ trie for several particular cryptographic commitment schemes with rich set of optimization options.

The library supports both variable and fixed-sized keys as well as a number optimization options:

• 256-ary trie is best for fixed-sized commitment models like KZG (Kate and verkle tries
• 16-ary (hexary) trie is similar to Patricia trees. It is close to optimal when it comes to hash-based commitment models
• 2-ary (binary) trie gives the smallest proof size with hash-based commitment. However, much longer proof path and bytes-to-bits packing/unpacking overhead is noticeable
• library also supports key commitments, a trie optimization when key and value are equal. This makes it optimal for ledger-state commitments, because in ledger state commitments the committed values are commitments itself (UTXO IDs or transaction ID) and the trie stores committed terminal value only once. This option is ideal for commitment to the ledger state.
• terminal values can be committed to any node of the tree, not only leafs of it, in optimal way.

The trie implementation has minimal dependencies on other projects.

It is used as a dependency in the IOTA Smart Contracts (the Wasp node) as the engine for the state commitment.

The blake2b-based trie implementation is ready for the use in other projects.

Package trie

Contains:

• an implementation of the (extended) radix trie.
• data types and interfaces shared between different implementations of trie:
  • interfaces VCommitment and TCommitment abstracts implementation from serialization details
  • KVReader, KVWriter, KVIterator interfaces abstracts implementation from details of a particular key/value store
  • the CommitmentModel interface abstracts trie implementation from particularities of specific commitments schemes
  • various utility functions used in the code and in tests

It essentially follows the formal definition provided in 256+ trie. Definition.

The implementation is optimized performance and storage-wise. It provides O(log_256(N)) complexity of the trie updates.

The trie itself is stored as a collection of key/value pairs. Updating of the trie is cached in memory. It makes trie update a very fast operation.

Packages models/trie_blake2b

Contains implementation of the CommitmentModel as a sparse Merkle tree on the trie with data commitment via blake2b hash function.

The binary (2-ary) trie is essentially the same as well known Sparse Merkle Tree.

The implementation takes particular hash size used in the commitments as a parameter.

The usage of hashing function as a commitment function results in proofs of inclusion up to 5-6 times bigger than with (1-2Kbytes) polynomial KZG (aka Kate) commitments.

Package models/trie_kzg_bn256

Contains implementation of the CommitmentModel as the verkle tree which uses KZG (Kate) commitments as a scheme for vectors commitments and bn256 curve from Dedis Kyber library. For related math and other references see the writeup.

The underlying KZG cryptography in this specific implementation is rather slow and suboptimal. The speed of update of the 256+ trie is some 1-2 orders of magnitude slower than implementation with blake2b hash function. The proofs of inclusion, however, are very short, up to 5-6 times shorter, ~200 bytes only.

The models/trie_kzg_bn256 implementation is more a proof of concept and verification of the 256+ trie concept. It should not be use in practical project, unless bn256 is replaced with other, faster curves.

Package models/tests

Contains number of tests of the trie implementation. Same tests run for trie_blak2b 256 and 160 bit hashing and trie_kzg_bn256 implementations of the CommitmentModel and different combinations of other parameters such as arity of the trie. It also makes sure trie implementation is agnostic about the specific commitment model and optimization parameters.

Package hive_adaptor

Contains useful adaptors to key/value interface of hive.go. It makes trie.go compatible with any key/value storages implemented in the github.com/iotaledger/hive.go.

Package examples/trie_bench

Contains trie_bench program made for testing and benchmarking of different functions of trie with tre_blake2b commitment model. The trie_bench uses Badger key/value database via hive_adaptor.

In the directory of the package run go install and run the program with options and commands.

Commands:

• trie_bench [flags] gen <name> generates a binary file <name>.bin of <size> random keys and values.
• trie_bench [flags] mkdbmem <name> loads file <name>.bin into the in-memory k/v database, both values and the trie. Outputs statistics.
• trie_bench [flags] mkdbbadger <name> loads file <name>.bin into the Badger k/v database on directory <name>.dbdir, both values and the trie. Outputs statistics.
• trie_bench [flags] scandbbadger <name> scans database and outputs statistics. Then it iterates over all keys and value in the database and for each key/value pair:
  • retrieves proof of inclusion for the key from the trie
  • runs validation of the proof
  • collects statistics
• trie_bench mkdbbadgernotrie <name> just loads key/value pairs to DB

Flags:

• -n=<num> number of key value pairs to generate. Default is 1000.
• -arity=2|16|32 default is 16
• -blake2b=20|32 default is 20
• -hashkv if present, keys and values will be hashed to 32 bytes while generating random file. Defaults to false
• -optkey if present, key commitment optimization will be enabled. Default is false

Benchmark results I

Statistics on the 2.8 GhZ 32 GB RAM SDD laptop. trie_bench run over the key/value database of 1 mil key/value pairs and trie_blake2b commitment model:

• Commitment model trie_blake2b 160 bit
• 1 million key/value pairs
• maximum key size: 100 bytes
• maximum value size: 32 bytes
• all terminal values are stored in the trie nodes (no optimization)
• 1 mil key/value pairs in file: 69 MB
• 1 mil key/value pairs in Badger DB (no trie): 162 MB

Note: retrieval speed very much depends on caching parameters. Benchmark results (caching turned off) would be much faster with caching turned on.

Benchmark for 256-ary trie

Parameter	blake2b 160 bit model
Load 1 mil records into the DB with trie generation (cached trie)	30000 kv pairs/sec
Badger DB size	408 MB
Retrieve proof + validation (not-cached trie )	3340 proofs/sec
Average length of the proof path	4.04
Average size of serialized proof	10.6 kB

Benchmark for 16-ary trie hexary)

Parameter	blake2b 160 bit model
Load 1 mil records into the DB with trie generation (cached trie)	32000 kv pairs/sec
Badger DB size	424 MB
Retrieve proof + validation (not-cached trie)	14400 proofs/sec
Average length of the proof path	6.6
Average size of serialized proof	1.75 kB

Benchmarks for 2-ary trie (binary)

Parameter	blake2b 160 bit model
Load 1 mil records into the DB with trie generation (cached trie)	13800 kv pairs/sec
Badger DB size	540 MB
Retrieve proof + validation (not-cached trie)	7580 proofs/sec
Average length of the proof path	21.1
Average size of serialized proof	1.3 kB

We can see that optimal choice with blake2b 160-bit model is between hexary and binary trie. Note that binary trie is using more runtime memory for key packing/unpacking.

The KZG (Kate) model would give the shortest proofs (~200 bytes) with 1-2 orders of magnitude slower trie update.

Benchmark results II: compare storage optimization

Statistics on the 2.8 GhZ 32 GB RAM SDD laptop.

• • Commitment model trie_blake2b 160 bit
• 1 million key/value pairs
• maximum key size: 100 bytes
• maximum value size: 40 Kbytes
• 1 mil key/value pairs in file: 18.6 GB

Benchmark for 16-ary (hexary) trie, terminal commitments NOT STORED in the trie

Parameter	blake2b 160 bit model
Load 1 mil records into the DB with trie generation (cached trie)	5100 kv pairs/sec
Badger DB size	18.8 GB
Retrieve proof + validation (not-cached trie )	4700 proofs/sec
Average length of the proof path	6.62
Average size of serialized proof	1.77 kB

Benchmark for 16-ary (hexary) trie, approx 25% of terminal commitments are STORED in the trie

(terminal commitments for values longer than 10000 bytes are stored in the trie)

Parameter	blake2b 160 bit model
Load 1 mil records into the DB with trie generation (cached trie)	7000 kv pairs/sec
Badger DB size	18.8 GB
Retrieve proof + validation (not-cached trie )	8600 proofs/sec
Average length of the proof path	6.62
Average size of serialized proof	1.77 kB

We can see that big average values does not inflate trie at some expense of proof performance speed. This is expected because big value must be fetched from the DB and hashed every time when terminal commitment is needed.

However, with terminal value threshold parameter performance can be optimized without noticeable increase in the DB size.

Package examples/trie_example

Contains a simple example with the in memory key/value store. Run go install and the run the program trie_example.

package main

import (
	"fmt"

	"github.com/iotaledger/trie.go/common"
	"github.com/iotaledger/trie.go/models/trie_blake2b"
	"github.com/iotaledger/trie.go/models/trie_blake2b/trie_blake2b_verify"
	"github.com/iotaledger/trie.go/mutable"
)

var data = []string{"a", "abc", "abcd", "b", "abd", "klmn", "oprst", "ab", "bcd"}

func main() {
	// create store where trie nodes will be stored
	store := common.NewInMemoryKVStore()

	// create blake2b 20 bytes (160 bit) commitment common for binary trie
	model := trie_blake2b.New(common.PathArity2, trie_blake2b.HashSize160)

	// create the trie with binary keys
	tr := mutable.New(model, store, nil)
	fmt.Printf("\nExample of trie.\n%s\n", tr.Info())

	// add data key/value pairs to the trie
	for _, s := range data {
		fmt.Printf("add key '%s' into the trie\n", s)
		tr.UpdateStr(s, s+"$")
	}
	// recalculate commitments in the trie
	tr.Commit()
	rootCommitment := mutable.RootCommitment(tr)
	fmt.Printf("root commitment: %s\n", rootCommitment)
	// remove some keys from the trie
	for _, i := range []int{1, 5, 6} {
		fmt.Printf("remove key '%s' from the trie\n", data[i])
		tr.DeleteStr(data[i])
	}
	// recalc trie again
	tr.Commit()
	rootCommitment = mutable.RootCommitment(tr)
	fmt.Printf("root commitment: %s\n", rootCommitment)

	// check PoI for all data
	for _, s := range data {
		// retrieve proof
		proof := model.Proof([]byte(s), tr)
		fmt.Printf("PoI of the key '%s': length %d, serialized size %d bytes\n",
			s, len(proof.Path), model.MustSize(proof))
		// validate proof
		err := trie_blake2b_verify.Validate(proof, rootCommitment.Bytes())
		errstr := "OK"
		if err != nil {
			errstr = err.Error()
		}
		if err != nil {
			fmt.Printf("validating PoI for '%s': %s\n", s, errstr)
			continue
		}
		if trie_blake2b_verify.IsProofOfAbsence(proof) {
			fmt.Printf("key '%s' is NOT IN THE STATE\n", s)
		} else {
			fmt.Printf("key '%s' is IN THE STATE\n", s)
		}
	}
}