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diff --git a/Documentation/rbtree.txt b/Documentation/rbtree.txt new file mode 100644 index 00000000..19f8278c --- /dev/null +++ b/Documentation/rbtree.txt @@ -0,0 +1,250 @@ +Red-black Trees (rbtree) in Linux +January 18, 2007 +Rob Landley <rob@landley.net> +============================= + +What are red-black trees, and what are they for? +------------------------------------------------ + +Red-black trees are a type of self-balancing binary search tree, used for +storing sortable key/value data pairs. This differs from radix trees (which +are used to efficiently store sparse arrays and thus use long integer indexes +to insert/access/delete nodes) and hash tables (which are not kept sorted to +be easily traversed in order, and must be tuned for a specific size and +hash function where rbtrees scale gracefully storing arbitrary keys). + +Red-black trees are similar to AVL trees, but provide faster real-time bounded +worst case performance for insertion and deletion (at most two rotations and +three rotations, respectively, to balance the tree), with slightly slower +(but still O(log n)) lookup time. + +To quote Linux Weekly News: + + There are a number of red-black trees in use in the kernel. + The deadline and CFQ I/O schedulers employ rbtrees to + track requests; the packet CD/DVD driver does the same. + The high-resolution timer code uses an rbtree to organize outstanding + timer requests. The ext3 filesystem tracks directory entries in a + red-black tree. Virtual memory areas (VMAs) are tracked with red-black + trees, as are epoll file descriptors, cryptographic keys, and network + packets in the "hierarchical token bucket" scheduler. + +This document covers use of the Linux rbtree implementation. For more +information on the nature and implementation of Red Black Trees, see: + + Linux Weekly News article on red-black trees + http://lwn.net/Articles/184495/ + + Wikipedia entry on red-black trees + http://en.wikipedia.org/wiki/Red-black_tree + +Linux implementation of red-black trees +--------------------------------------- + +Linux's rbtree implementation lives in the file "lib/rbtree.c". To use it, +"#include <linux/rbtree.h>". + +The Linux rbtree implementation is optimized for speed, and thus has one +less layer of indirection (and better cache locality) than more traditional +tree implementations. Instead of using pointers to separate rb_node and data +structures, each instance of struct rb_node is embedded in the data structure +it organizes. And instead of using a comparison callback function pointer, +users are expected to write their own tree search and insert functions +which call the provided rbtree functions. Locking is also left up to the +user of the rbtree code. + +Creating a new rbtree +--------------------- + +Data nodes in an rbtree tree are structures containing a struct rb_node member: + + struct mytype { + struct rb_node node; + char *keystring; + }; + +When dealing with a pointer to the embedded struct rb_node, the containing data +structure may be accessed with the standard container_of() macro. In addition, +individual members may be accessed directly via rb_entry(node, type, member). + +At the root of each rbtree is an rb_root structure, which is initialized to be +empty via: + + struct rb_root mytree = RB_ROOT; + +Searching for a value in an rbtree +---------------------------------- + +Writing a search function for your tree is fairly straightforward: start at the +root, compare each value, and follow the left or right branch as necessary. + +Example: + + struct mytype *my_search(struct rb_root *root, char *string) + { + struct rb_node *node = root->rb_node; + + while (node) { + struct mytype *data = container_of(node, struct mytype, node); + int result; + + result = strcmp(string, data->keystring); + + if (result < 0) + node = node->rb_left; + else if (result > 0) + node = node->rb_right; + else + return data; + } + return NULL; + } + +Inserting data into an rbtree +----------------------------- + +Inserting data in the tree involves first searching for the place to insert the +new node, then inserting the node and rebalancing ("recoloring") the tree. + +The search for insertion differs from the previous search by finding the +location of the pointer on which to graft the new node. The new node also +needs a link to its parent node for rebalancing purposes. + +Example: + + int my_insert(struct rb_root *root, struct mytype *data) + { + struct rb_node **new = &(root->rb_node), *parent = NULL; + + /* Figure out where to put new node */ + while (*new) { + struct mytype *this = container_of(*new, struct mytype, node); + int result = strcmp(data->keystring, this->keystring); + + parent = *new; + if (result < 0) + new = &((*new)->rb_left); + else if (result > 0) + new = &((*new)->rb_right); + else + return FALSE; + } + + /* Add new node and rebalance tree. */ + rb_link_node(&data->node, parent, new); + rb_insert_color(&data->node, root); + + return TRUE; + } + +Removing or replacing existing data in an rbtree +------------------------------------------------ + +To remove an existing node from a tree, call: + + void rb_erase(struct rb_node *victim, struct rb_root *tree); + +Example: + + struct mytype *data = mysearch(&mytree, "walrus"); + + if (data) { + rb_erase(&data->node, &mytree); + myfree(data); + } + +To replace an existing node in a tree with a new one with the same key, call: + + void rb_replace_node(struct rb_node *old, struct rb_node *new, + struct rb_root *tree); + +Replacing a node this way does not re-sort the tree: If the new node doesn't +have the same key as the old node, the rbtree will probably become corrupted. + +Iterating through the elements stored in an rbtree (in sort order) +------------------------------------------------------------------ + +Four functions are provided for iterating through an rbtree's contents in +sorted order. These work on arbitrary trees, and should not need to be +modified or wrapped (except for locking purposes): + + struct rb_node *rb_first(struct rb_root *tree); + struct rb_node *rb_last(struct rb_root *tree); + struct rb_node *rb_next(struct rb_node *node); + struct rb_node *rb_prev(struct rb_node *node); + +To start iterating, call rb_first() or rb_last() with a pointer to the root +of the tree, which will return a pointer to the node structure contained in +the first or last element in the tree. To continue, fetch the next or previous +node by calling rb_next() or rb_prev() on the current node. This will return +NULL when there are no more nodes left. + +The iterator functions return a pointer to the embedded struct rb_node, from +which the containing data structure may be accessed with the container_of() +macro, and individual members may be accessed directly via +rb_entry(node, type, member). + +Example: + + struct rb_node *node; + for (node = rb_first(&mytree); node; node = rb_next(node)) + printk("key=%s\n", rb_entry(node, struct mytype, node)->keystring); + +Support for Augmented rbtrees +----------------------------- + +Augmented rbtree is an rbtree with "some" additional data stored in each node. +This data can be used to augment some new functionality to rbtree. +Augmented rbtree is an optional feature built on top of basic rbtree +infrastructure. rbtree user who wants this feature will have an augment +callback function in rb_root initialized. + +This callback function will be called from rbtree core routines whenever +a node has a change in one or both of its children. It is the responsibility +of the callback function to recalculate the additional data that is in the +rb node using new children information. Note that if this new additional +data affects the parent node's additional data, then callback function has +to handle it and do the recursive updates. + + +Interval tree is an example of augmented rb tree. Reference - +"Introduction to Algorithms" by Cormen, Leiserson, Rivest and Stein. +More details about interval trees: + +Classical rbtree has a single key and it cannot be directly used to store +interval ranges like [lo:hi] and do a quick lookup for any overlap with a new +lo:hi or to find whether there is an exact match for a new lo:hi. + +However, rbtree can be augmented to store such interval ranges in a structured +way making it possible to do efficient lookup and exact match. + +This "extra information" stored in each node is the maximum hi +(max_hi) value among all the nodes that are its descendents. This +information can be maintained at each node just be looking at the node +and its immediate children. And this will be used in O(log n) lookup +for lowest match (lowest start address among all possible matches) +with something like: + +find_lowest_match(lo, hi, node) +{ + lowest_match = NULL; + while (node) { + if (max_hi(node->left) > lo) { + // Lowest overlap if any must be on left side + node = node->left; + } else if (overlap(lo, hi, node)) { + lowest_match = node; + break; + } else if (lo > node->lo) { + // Lowest overlap if any must be on right side + node = node->right; + } else { + break; + } + } + return lowest_match; +} + +Finding exact match will be to first find lowest match and then to follow +successor nodes looking for exact match, until the start of a node is beyond +the hi value we are looking for. |