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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 10:05:51 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 10:05:51 +0000 |
commit | 5d1646d90e1f2cceb9f0828f4b28318cd0ec7744 (patch) | |
tree | a94efe259b9009378be6d90eb30d2b019d95c194 /Documentation/core-api/rbtree.rst | |
parent | Initial commit. (diff) | |
download | linux-430c2fc249ea5c0536abd21c23382884005c9093.tar.xz linux-430c2fc249ea5c0536abd21c23382884005c9093.zip |
Adding upstream version 5.10.209.upstream/5.10.209upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'Documentation/core-api/rbtree.rst')
-rw-r--r-- | Documentation/core-api/rbtree.rst | 429 |
1 files changed, 429 insertions, 0 deletions
diff --git a/Documentation/core-api/rbtree.rst b/Documentation/core-api/rbtree.rst new file mode 100644 index 000000000..6b88837fb --- /dev/null +++ b/Documentation/core-api/rbtree.rst @@ -0,0 +1,429 @@ +================================= +Red-black Trees (rbtree) in Linux +================================= + + +:Date: January 18, 2007 +:Author: 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 + https://lwn.net/Articles/184495/ + + Wikipedia entry on red-black trees + https://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); + +Cached rbtrees +-------------- + +Computing the leftmost (smallest) node is quite a common task for binary +search trees, such as for traversals or users relying on a the particular +order for their own logic. To this end, users can use 'struct rb_root_cached' +to optimize O(logN) rb_first() calls to a simple pointer fetch avoiding +potentially expensive tree iterations. This is done at negligible runtime +overhead for maintanence; albeit larger memory footprint. + +Similar to the rb_root structure, cached rbtrees are initialized to be +empty via:: + + struct rb_root_cached mytree = RB_ROOT_CACHED; + +Cached rbtree is simply a regular rb_root with an extra pointer to cache the +leftmost node. This allows rb_root_cached to exist wherever rb_root does, +which permits augmented trees to be supported as well as only a few extra +interfaces:: + + struct rb_node *rb_first_cached(struct rb_root_cached *tree); + void rb_insert_color_cached(struct rb_node *, struct rb_root_cached *, bool); + void rb_erase_cached(struct rb_node *node, struct rb_root_cached *); + +Both insert and erase calls have their respective counterpart of augmented +trees:: + + void rb_insert_augmented_cached(struct rb_node *node, struct rb_root_cached *, + bool, struct rb_augment_callbacks *); + void rb_erase_augmented_cached(struct rb_node *, struct rb_root_cached *, + struct rb_augment_callbacks *); + + +Support for Augmented rbtrees +----------------------------- + +Augmented rbtree is an rbtree with "some" additional data stored in +each node, where the additional data for node N must be a function of +the contents of all nodes in the subtree rooted at N. 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. +An rbtree user who wants this feature will have to call the augmentation +functions with the user provided augmentation callback when inserting +and erasing nodes. + +C files implementing augmented rbtree manipulation must include +<linux/rbtree_augmented.h> instead of <linux/rbtree.h>. Note that +linux/rbtree_augmented.h exposes some rbtree implementations details +you are not expected to rely on; please stick to the documented APIs +there and do not include <linux/rbtree_augmented.h> from header files +either so as to minimize chances of your users accidentally relying on +such implementation details. + +On insertion, the user must update the augmented information on the path +leading to the inserted node, then call rb_link_node() as usual and +rb_augment_inserted() instead of the usual rb_insert_color() call. +If rb_augment_inserted() rebalances the rbtree, it will callback into +a user provided function to update the augmented information on the +affected subtrees. + +When erasing a node, the user must call rb_erase_augmented() instead of +rb_erase(). rb_erase_augmented() calls back into user provided functions +to updated the augmented information on affected subtrees. + +In both cases, the callbacks are provided through struct rb_augment_callbacks. +3 callbacks must be defined: + +- A propagation callback, which updates the augmented value for a given + node and its ancestors, up to a given stop point (or NULL to update + all the way to the root). + +- A copy callback, which copies the augmented value for a given subtree + to a newly assigned subtree root. + +- A tree rotation callback, which copies the augmented value for a given + subtree to a newly assigned subtree root AND recomputes the augmented + information for the former subtree root. + +The compiled code for rb_erase_augmented() may inline the propagation and +copy callbacks, which results in a large function, so each augmented rbtree +user should have a single rb_erase_augmented() call site in order to limit +compiled code size. + + +Sample usage +^^^^^^^^^^^^ + +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 descendants. 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:: + + struct interval_tree_node * + interval_tree_first_match(struct rb_root *root, + unsigned long start, unsigned long last) + { + struct interval_tree_node *node; + + if (!root->rb_node) + return NULL; + node = rb_entry(root->rb_node, struct interval_tree_node, rb); + + while (true) { + if (node->rb.rb_left) { + struct interval_tree_node *left = + rb_entry(node->rb.rb_left, + struct interval_tree_node, rb); + if (left->__subtree_last >= start) { + /* + * Some nodes in left subtree satisfy Cond2. + * Iterate to find the leftmost such node N. + * If it also satisfies Cond1, that's the match + * we are looking for. Otherwise, there is no + * matching interval as nodes to the right of N + * can't satisfy Cond1 either. + */ + node = left; + continue; + } + } + if (node->start <= last) { /* Cond1 */ + if (node->last >= start) /* Cond2 */ + return node; /* node is leftmost match */ + if (node->rb.rb_right) { + node = rb_entry(node->rb.rb_right, + struct interval_tree_node, rb); + if (node->__subtree_last >= start) + continue; + } + } + return NULL; /* No match */ + } + } + +Insertion/removal are defined using the following augmented callbacks:: + + static inline unsigned long + compute_subtree_last(struct interval_tree_node *node) + { + unsigned long max = node->last, subtree_last; + if (node->rb.rb_left) { + subtree_last = rb_entry(node->rb.rb_left, + struct interval_tree_node, rb)->__subtree_last; + if (max < subtree_last) + max = subtree_last; + } + if (node->rb.rb_right) { + subtree_last = rb_entry(node->rb.rb_right, + struct interval_tree_node, rb)->__subtree_last; + if (max < subtree_last) + max = subtree_last; + } + return max; + } + + static void augment_propagate(struct rb_node *rb, struct rb_node *stop) + { + while (rb != stop) { + struct interval_tree_node *node = + rb_entry(rb, struct interval_tree_node, rb); + unsigned long subtree_last = compute_subtree_last(node); + if (node->__subtree_last == subtree_last) + break; + node->__subtree_last = subtree_last; + rb = rb_parent(&node->rb); + } + } + + static void augment_copy(struct rb_node *rb_old, struct rb_node *rb_new) + { + struct interval_tree_node *old = + rb_entry(rb_old, struct interval_tree_node, rb); + struct interval_tree_node *new = + rb_entry(rb_new, struct interval_tree_node, rb); + + new->__subtree_last = old->__subtree_last; + } + + static void augment_rotate(struct rb_node *rb_old, struct rb_node *rb_new) + { + struct interval_tree_node *old = + rb_entry(rb_old, struct interval_tree_node, rb); + struct interval_tree_node *new = + rb_entry(rb_new, struct interval_tree_node, rb); + + new->__subtree_last = old->__subtree_last; + old->__subtree_last = compute_subtree_last(old); + } + + static const struct rb_augment_callbacks augment_callbacks = { + augment_propagate, augment_copy, augment_rotate + }; + + void interval_tree_insert(struct interval_tree_node *node, + struct rb_root *root) + { + struct rb_node **link = &root->rb_node, *rb_parent = NULL; + unsigned long start = node->start, last = node->last; + struct interval_tree_node *parent; + + while (*link) { + rb_parent = *link; + parent = rb_entry(rb_parent, struct interval_tree_node, rb); + if (parent->__subtree_last < last) + parent->__subtree_last = last; + if (start < parent->start) + link = &parent->rb.rb_left; + else + link = &parent->rb.rb_right; + } + + node->__subtree_last = last; + rb_link_node(&node->rb, rb_parent, link); + rb_insert_augmented(&node->rb, root, &augment_callbacks); + } + + void interval_tree_remove(struct interval_tree_node *node, + struct rb_root *root) + { + rb_erase_augmented(&node->rb, root, &augment_callbacks); + } |