#ip #prefix #trie #collection


Prefix trie datastructure (both a set and a map) that provides exact and longest-prefix matches

5 releases

0.2.4 Jan 9, 2023
0.2.3 Jan 6, 2023
0.2.2 Jan 4, 2023
0.2.1 Jan 3, 2023
0.2.0 Dec 30, 2022

#6 in #prefix

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This crate provides a simple prefix tree for IP prefixes. Any lookup performs longest-prefix match.

ip_network_table-deps-treebitmap provides an IP lookup table, similar to PrefixMap.

The following compares the two approaches in case of dense or sparse maps. Each test case performs 100'000 modifications or lookups. However, the dense cases randomly pick any IPv4 address, while the sparse case only pick 20 different IPv4 addresses. See benches/benchmark.rs for more details.

Operation Mode PrefixMap treebitmap factor
Insert & Remove dense 31.78ms 47.52ms ~1.5x
Lookup dense 32.36ms 8.409ms ~0.25x
Insert & Remove sparse 6.645ms 7.329ms ~1.1x
Lookup sparse 8.394ms 12.30ms ~1.5x

In addition, prefix-trie includes a PrefixSet analogeous to std::collections::HashSet, including union, intersection and difference operations that are implemented as simultaneous tree traversals. Further, prefix-trie has an interface similar to std::collections, and includes methods for accessing all children of a node. Finally, it offers a general longest-prefix match that is not limited to individual addresses.

Description of the Tree

The tree is structured as follows: Each node consists of a prefix, a container for a potential value (Option), and two optional children. Adding a new child, or traversing into the tree is done as follows: we look at the most significant bit that is not part of the prefix itself. If it is not set, then we take the left branch, and otherwise, we take the right one.


Any iteration over all elements in the tree is implemented as a graph traversal that will yield elements in lexicographic order (with the exception of mutable iteration of the PrefixMap). This also includes the iteration over the union, intersection, or difference of two PrefixSets, which are implemented as simultaneous tree traversals. Further, calling retain will also traverse the tree only once, removing elements during the traversal.

Operations on the tree

There are several operations one can do on the tree. Regular inserts are handled using the Entry structure. An Entry is a pointer to a location in the tree to either insert a value or modify an existing one. Removals however are different.

The following are the computational complexities of the functions, where n is the number of elements in the tree.

Operation Complexity
entry, insert O(log n)
remove, remove_keep_tree O(log n)
remove_children (calling drop on T) O(n)
get, get_lpm, get_mut O(log n)
retain O(n)
clear (calling drop on T) O(n)
Operations on map::Entry O(1)

There are three kinds of removals you! can do:

  • PrefixMap::remove will remove an entry from the tree and modify the tree structure as if the value was never inserted before. PrefixMap::remove will always exactly revert the operation of PrefixMap::insert. When only calling this function to remove elements, you are guaranteed that the tree structure is indistinguishable to a different tree where you only inserted elements.
  • PrefixMap::remove_children will remove all entries that are contained within the given prefix. This operation will search for the node with the shortest prefix length that is contained within the given prefix and remove it, including all of its children.
  • PrefixMap::remove_keep_tree will not change anything in the tree structure. It will only remove a value from a node. As soon as you call remove_keep_tree once on a tree structure, the tree will no longer be optimal.


Migrate to a TreeBitMap, described by W. Eatherton, Z. Dittia, G. Varghes.