https://github.com/bwnetflow/ip_prefix_trie

A Binary Prefix Trie Implementation for looking up objects using an associated IP Address
https://github.com/bwnetflow/ip_prefix_trie

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A Binary Prefix Trie Implementation for looking up objects using an associated IP Address

• Host: GitHub
• URL: https://github.com/bwnetflow/ip_prefix_trie
• Owner: bwNetFlow
• Created: 2019-07-17T11:24:00.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2021-08-30T11:20:23.000Z (over 3 years ago)
• Last Synced: 2025-01-02T22:20:48.794Z (22 days ago)
• Language: Go
• Size: 11.7 KB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## IP Prefix Trie

This module is intended for matching IP addresses to arbitrary prefix networks.

This is done using a classic prefix tree (or trie) which stores data at all

nodes within an existing IP network prefix. This module supports both, IPv6 and

legacy IPv4. Separate trees have to be kept for each protocol, of course. See

the following example using an integer, which might represent a customer ID:

```

v6_trie.Insert(123, []string{"2001:db8:1234::/48"})

ip, _, _ := net.ParseCIDR("2001:db8:1234::7/64")

matched_id := v6_trie.Lookup(ip)

```

More examples can be seen in the test cases. This is currently in use to match

Netflow data to customer IDs which are used for billing on a specific upstream

link.

## Internal workings

This module implements a standard trie, which operates on 0 and 1 for

branching. Some care is taken to implement longest prefix matching (i.e.

matching the most specific network) correctly. The Lookup method remembers the

current most specific prefix while descending. The code is thoroughly

commented, go take a look.

Wikipedia has some more [details](https://en.wikipedia.org/wiki/Trie) on tries

in general.

## Benchmark Results

Benchmark results from my Laptop, so you don't have to run them yourself:

```

> go test -bench=. -test.benchtime=10s

goos: linux

goarch: amd64

pkg: ip_prefix_trie

BenchmarkIPv4LookupHit-8            	200000000	        81.1 ns/op

BenchmarkIPv6LookupHit-8            	100000000	       140 ns/op

BenchmarkIPv4LookupProbableMiss-8   	200000000	        65.1 ns/op

BenchmarkIPv6LookupProbableMiss-8   	100000000	       107 ns/op

PASS

ok  	ip_prefix_trie	68.719s

```

In a real environment looking up customer IDs, you can expect lookups within

1us (99th percentile) at about 10k lookups per second using two trees (v6 and

v4) simultaneously. They'll take 600ns on average. Perhaps above benchmark

setup is not very realistic.

## TODO

 * implement payloads as pointer to reduce memory footprint

 * do more realistic benchmarking (and testing)