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Red-black Trees (rbtree) in Linux
:Date: January 18, 2007
:Author: Rob Landley <>
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
Wikipedia entry on red-black trees
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.
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;
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.
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);
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);
struct mytype *data = mysearch(&mytree, "walrus");
if (data) {
rb_erase(&data->node, &mytree);
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).
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
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
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 =
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;
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)
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)
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;
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);