€•k      Œsphinx.addnodes”Œdocument”“”)”}”(Œ	rawsource”Œ ”Œchildren”]”(Œtranslations”ŒLanguagesNode”“”)”}”(hhh]”(h Œpending_xref”“”)”}”(hhh]”Œdocutils.nodes”ŒText”“”ŒChinese (Simplified)”…””}”Œparent”hsbaŒ
attributes”}”(Œids”]”Œclasses”]”Œnames”]”Œdupnames”]”Œbackrefs”]”Œ	refdomain”Œstd”Œreftype”Œdoc”Œ	reftarget”Œ'/translations/zh_CN/networking/fib_trie”Œmodname”NŒ	classname”NŒrefexplicit”ˆuŒtagname”hhhubh)”}”(hhh]”hŒChinese (Traditional)”…””}”hh2sbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/zh_TW/networking/fib_trie”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒItalian”…””}”hhFsbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/it_IT/networking/fib_trie”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒJapanese”…””}”hhZsbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/ja_JP/networking/fib_trie”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒKorean”…””}”hhnsbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/ko_KR/networking/fib_trie”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubh)”}”(hhh]”hŒSpanish”…””}”hh‚sbah}”(h]”h ]”h"]”h$]”h&]”Œ	refdomain”h)Œreftype”h+Œ	reftarget”Œ'/translations/sp_SP/networking/fib_trie”Œmodname”NŒ	classname”NŒrefexplicit”ˆuh1hhhubeh}”(h]”h ]”h"]”h$]”h&]”Œcurrent_language”ŒEnglish”uh1h
hhŒ	_document”hŒsource”NŒline”NubhŒcomment”“”)”}”(hŒ SPDX-License-Identifier: GPL-2.0”h]”hŒ SPDX-License-Identifier: GPL-2.0”…””}”hh£sbah}”(h]”h ]”h"]”h$]”h&]”Œ	xml:space”Œpreserve”uh1h¡hhhžhhŸŒA/var/lib/git/docbuild/linux/Documentation/networking/fib_trie.rst”h KubhŒsection”“”)”}”(hhh]”(hŒtitle”“”)”}”(hŒLC-trie implementation notes”h]”hŒLC-trie implementation notes”…””}”(hh»hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¹hh¶hžhhŸh³h Kubhµ)”}”(hhh]”(hº)”}”(hŒ
Node types”h]”hŒ
Node types”…””}”(hhÌhžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¹hhÉhžhhŸh³h KubhŒdefinition_list”“”)”}”(hhh]”(hŒdefinition_list_item”“”)”}”(hŒ®leaf
An end node with data. This has a copy of the relevant key, along
with 'hlist' with routing table entries sorted by prefix length.
See struct leaf and struct leaf_info.
”h]”(hŒterm”“”)”}”(hŒleaf”h]”hŒleaf”…””}”(hhçhžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h KhháubhŒ
definition”“”)”}”(hhh]”hŒ	paragraph”“”)”}”(hŒ¨An end node with data. This has a copy of the relevant key, along
with 'hlist' with routing table entries sorted by prefix length.
See struct leaf and struct leaf_info.”h]”hŒ¬An end node with data. This has a copy of the relevant key, along
with â€˜hlistâ€™ with routing table entries sorted by prefix length.
See struct leaf and struct leaf_info.”…””}”(hhühžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K
hh÷ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhháubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KhhÜubhà)”}”(hŒ•trie node or tnode
An internal node, holding an array of child (leaf or tnode) pointers,
indexed through a subset of the key. See Level Compression.
”h]”(hæ)”}”(hŒtrie node or tnode”h]”hŒtrie node or tnode”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h Khj  ubhö)”}”(hhh]”hû)”}”(hŒAn internal node, holding an array of child (leaf or tnode) pointers,
indexed through a subset of the key. See Level Compression.”h]”hŒAn internal node, holding an array of child (leaf or tnode) pointers,
indexed through a subset of the key. See Level Compression.”…””}”(hj+  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Khj(  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KhhÜhžhubeh}”(h]”h ]”h"]”h$]”h&]”uh1hÚhhÉhžhhŸh³h Nubeh}”(h]”Œ
node-types”ah ]”h"]”Œ
node types”ah$]”h&]”uh1h´hh¶hžhhŸh³h Kubhµ)”}”(hhh]”(hº)”}”(hŒA few concepts explained”h]”hŒA few concepts explained”…””}”(hjV  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¹hjS  hžhhŸh³h KubhÛ)”}”(hhh]”(hà)”}”(hŒ†Bits (tnode)
The number of bits in the key segment used for indexing into the
child array - the "child index". See Level Compression.
”h]”(hæ)”}”(hŒBits (tnode)”h]”hŒBits (tnode)”…””}”(hjk  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h Khjg  ubhö)”}”(hhh]”hû)”}”(hŒxThe number of bits in the key segment used for indexing into the
child array - the "child index". See Level Compression.”h]”hŒ|The number of bits in the key segment used for indexing into the
child array - the â€œchild indexâ€. See Level Compression.”…””}”(hj|  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Khjy  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjg  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h Khjd  ubhà)”}”(hŒwPos (tnode)
The position (in the key) of the key segment used for indexing into
the child array. See Path Compression.
”h]”(hæ)”}”(hŒPos (tnode)”h]”hŒPos (tnode)”…””}”(hjš  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h Khj–  ubhö)”}”(hhh]”hû)”}”(hŒjThe position (in the key) of the key segment used for indexing into
the child array. See Path Compression.”h]”hŒjThe position (in the key) of the key segment used for indexing into
the child array. See Path Compression.”…””}”(hj«  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Khj¨  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj–  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h Khjd  hžhubhà)”}”(hXq  Path Compression / skipped bits
Any given tnode is linked to from the child array of its parent, using
a segment of the key specified by the parent's "pos" and "bits"
In certain cases, this tnode's own "pos" will not be immediately
adjacent to the parent (pos+bits), but there will be some bits
in the key skipped over because they represent a single path with no
deviations. These "skipped bits" constitute Path Compression.
Note that the search algorithm will simply skip over these bits when
searching, making it necessary to save the keys in the leaves to
verify that they actually do match the key we are searching for.
”h]”(hæ)”}”(hŒPath Compression / skipped bits”h]”hŒPath Compression / skipped bits”…””}”(hjÉ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h K%hjÅ  ubhö)”}”(hhh]”hû)”}”(hXP  Any given tnode is linked to from the child array of its parent, using
a segment of the key specified by the parent's "pos" and "bits"
In certain cases, this tnode's own "pos" will not be immediately
adjacent to the parent (pos+bits), but there will be some bits
in the key skipped over because they represent a single path with no
deviations. These "skipped bits" constitute Path Compression.
Note that the search algorithm will simply skip over these bits when
searching, making it necessary to save the keys in the leaves to
verify that they actually do match the key we are searching for.”h]”hXd  Any given tnode is linked to from the child array of its parent, using
a segment of the key specified by the parentâ€™s â€œposâ€ and â€œbitsâ€
In certain cases, this tnodeâ€™s own â€œposâ€ will not be immediately
adjacent to the parent (pos+bits), but there will be some bits
in the key skipped over because they represent a single path with no
deviations. These â€œskipped bitsâ€ constitute Path Compression.
Note that the search algorithm will simply skip over these bits when
searching, making it necessary to save the keys in the leaves to
verify that they actually do match the key we are searching for.”…””}”(hjÚ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Khj×  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjÅ  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h K%hjd  hžhubhà)”}”(hXî  Level Compression / child arrays
the trie is kept level balanced moving, under certain conditions, the
children of a full child (see "full_children") up one level, so that
instead of a pure binary tree, each internal node ("tnode") may
contain an arbitrarily large array of links to several children.
Conversely, a tnode with a mostly empty child array (see empty_children)
may be "halved", having some of its children moved downwards one level,
in order to avoid ever-increasing child arrays.
”h]”(hæ)”}”(hŒ Level Compression / child arrays”h]”hŒ Level Compression / child arrays”…””}”(hjø  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h K.hjô  ubhö)”}”(hhh]”hû)”}”(hXÌ  the trie is kept level balanced moving, under certain conditions, the
children of a full child (see "full_children") up one level, so that
instead of a pure binary tree, each internal node ("tnode") may
contain an arbitrarily large array of links to several children.
Conversely, a tnode with a mostly empty child array (see empty_children)
may be "halved", having some of its children moved downwards one level,
in order to avoid ever-increasing child arrays.”h]”hXØ  the trie is kept level balanced moving, under certain conditions, the
children of a full child (see â€œfull_childrenâ€) up one level, so that
instead of a pure binary tree, each internal node (â€œtnodeâ€) may
contain an arbitrarily large array of links to several children.
Conversely, a tnode with a mostly empty child array (see empty_children)
may be â€œhalvedâ€, having some of its children moved downwards one level,
in order to avoid ever-increasing child arrays.”…””}”(hj	  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K(hj  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjô  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h K.hjd  hžhubhà)”}”(hŒZempty_children
the number of positions in the child array of a given tnode that are
NULL.
”h]”(hæ)”}”(hŒempty_children”h]”hŒempty_children”…””}”(hj'  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h K2hj#  ubhö)”}”(hhh]”hû)”}”(hŒJthe number of positions in the child array of a given tnode that are
NULL.”h]”hŒJthe number of positions in the child array of a given tnode that are
NULL.”…””}”(hj8  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K1hj5  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj#  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h K2hjd  hžhubhà)”}”(hX8  full_children
the number of children of a given tnode that aren't path compressed.
(in other words, they aren't NULL or leaves and their "pos" is equal
to this tnode's "pos"+"bits").

(The word "full" here is used more in the sense of "complete" than
as the opposite of "empty", which might be a tad confusing.)
”h]”(hæ)”}”(hŒfull_children”h]”hŒfull_children”…””}”(hjV  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h K:hjR  ubhö)”}”(hhh]”(hû)”}”(hŒ¨the number of children of a given tnode that aren't path compressed.
(in other words, they aren't NULL or leaves and their "pos" is equal
to this tnode's "pos"+"bits").”h]”hŒºthe number of children of a given tnode that arenâ€™t path compressed.
(in other words, they arenâ€™t NULL or leaves and their â€œposâ€ is equal
to this tnodeâ€™s â€œposâ€+â€bitsâ€).”…””}”(hjg  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K5hjd  ubhû)”}”(hŒ(The word "full" here is used more in the sense of "complete" than
as the opposite of "empty", which might be a tad confusing.)”h]”hŒ‹(The word â€œfullâ€ here is used more in the sense of â€œcompleteâ€ than
as the opposite of â€œemptyâ€, which might be a tad confusing.)”…””}”(hju  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K9hjd  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hõhjR  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h K:hjd  hžhubeh}”(h]”h ]”h"]”h$]”h&]”uh1hÚhjS  hžhhŸh³h Nubeh}”(h]”Œa-few-concepts-explained”ah ]”h"]”Œa few concepts explained”ah$]”h&]”uh1h´hh¶hžhhŸh³h Kubhµ)”}”(hhh]”(hº)”}”(hŒComments”h]”hŒComments”…””}”(hj   hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¹hj  hžhhŸh³h K=ubhû)”}”(hŒ}We have tried to keep the structure of the code as close to fib_hash as
possible to allow verification and help up reviewing.”h]”hŒ}We have tried to keep the structure of the code as close to fib_hash as
possible to allow verification and help up reviewing.”…””}”(hj®  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K?hj  hžhubhÛ)”}”(hhh]”(hà)”}”(hŒrfib_find_node()
A good start for understanding this code. This function implements a
straightforward trie lookup.
”h]”(hæ)”}”(hŒfib_find_node()”h]”hŒfib_find_node()”…””}”(hjÃ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h KDhj¿  ubhö)”}”(hhh]”hû)”}”(hŒaA good start for understanding this code. This function implements a
straightforward trie lookup.”h]”hŒaA good start for understanding this code. This function implements a
straightforward trie lookup.”…””}”(hjÔ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KChjÑ  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj¿  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KDhj¼  ubhà)”}”(hŒÏfib_insert_node()
Inserts a new leaf node in the trie. This is bit more complicated than
fib_find_node(). Inserting a new node means we might have to run the
level compression algorithm on part of the trie.
”h]”(hæ)”}”(hŒfib_insert_node()”h]”hŒfib_insert_node()”…””}”(hjò  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h KIhjî  ubhö)”}”(hhh]”hû)”}”(hŒ¼Inserts a new leaf node in the trie. This is bit more complicated than
fib_find_node(). Inserting a new node means we might have to run the
level compression algorithm on part of the trie.”h]”hŒ¼Inserts a new leaf node in the trie. This is bit more complicated than
fib_find_node(). Inserting a new node means we might have to run the
level compression algorithm on part of the trie.”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KGhj   ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjî  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KIhj¼  hžhubhà)”}”(hŒXtrie_leaf_remove()
Looks up a key, deletes it and runs the level compression algorithm.
”h]”(hæ)”}”(hŒtrie_leaf_remove()”h]”hŒtrie_leaf_remove()”…””}”(hj!  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h KLhj  ubhö)”}”(hhh]”hû)”}”(hŒDLooks up a key, deletes it and runs the level compression algorithm.”h]”hŒDLooks up a key, deletes it and runs the level compression algorithm.”…””}”(hj2  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KLhj/  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KLhj¼  hžhubhà)”}”(hŒûtrie_rebalance()
The key function for the dynamic trie after any change in the trie
it is run to optimize and reorganize. It will walk the trie upwards
towards the root from a given tnode, doing a resize() at each step
to implement level compression.
”h]”(hæ)”}”(hŒtrie_rebalance()”h]”hŒtrie_rebalance()”…””}”(hjP  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h KRhjL  ubhö)”}”(hhh]”hû)”}”(hŒéThe key function for the dynamic trie after any change in the trie
it is run to optimize and reorganize. It will walk the trie upwards
towards the root from a given tnode, doing a resize() at each step
to implement level compression.”h]”hŒéThe key function for the dynamic trie after any change in the trie
it is run to optimize and reorganize. It will walk the trie upwards
towards the root from a given tnode, doing a resize() at each step
to implement level compression.”…””}”(hja  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KOhj^  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjL  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KRhj¼  hžhubhà)”}”(hX  resize()
Analyzes a tnode and optimizes the child array size by either inflating
or shrinking it repeatedly until it fulfills the criteria for optimal
level compression. This part follows the original paper pretty closely
and there may be some room for experimentation here.
”h]”(hæ)”}”(hŒresize()”h]”hŒresize()”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h KXhj{  ubhö)”}”(hhh]”hû)”}”(hX	  Analyzes a tnode and optimizes the child array size by either inflating
or shrinking it repeatedly until it fulfills the criteria for optimal
level compression. This part follows the original paper pretty closely
and there may be some room for experimentation here.”h]”hX	  Analyzes a tnode and optimizes the child array size by either inflating
or shrinking it repeatedly until it fulfills the criteria for optimal
level compression. This part follows the original paper pretty closely
and there may be some room for experimentation here.”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KUhj  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj{  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h KXhj¼  hžhubhà)”}”(hŒPinflate()
Doubles the size of the child array within a tnode. Used by resize().
”h]”(hæ)”}”(hŒ	inflate()”h]”hŒ	inflate()”…””}”(hj®  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h K[hjª  ubhö)”}”(hhh]”hû)”}”(hŒEDoubles the size of the child array within a tnode. Used by resize().”h]”hŒEDoubles the size of the child array within a tnode. Used by resize().”…””}”(hj¿  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K[hj¼  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjª  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h K[hj¼  hžhubhà)”}”(hŒhhalve()
Halves the size of the child array within a tnode - the inverse of
inflate(). Used by resize();
”h]”(hæ)”}”(hŒhalve()”h]”hŒhalve()”…””}”(hjÝ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h K_hjÙ  ubhö)”}”(hhh]”hû)”}”(hŒ_Halves the size of the child array within a tnode - the inverse of
inflate(). Used by resize();”h]”hŒ_Halves the size of the child array within a tnode - the inverse of
inflate(). Used by resize();”…””}”(hjî  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K^hjë  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjÙ  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h K_hj¼  hžhubhà)”}”(hŒ©fn_trie_insert(), fn_trie_delete(), fn_trie_select_default()
The route manipulation functions. Should conform pretty closely to the
corresponding functions in fib_hash.
”h]”(hæ)”}”(hŒ<fn_trie_insert(), fn_trie_delete(), fn_trie_select_default()”h]”hŒ<fn_trie_insert(), fn_trie_delete(), fn_trie_select_default()”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h Kchj  ubhö)”}”(hhh]”hû)”}”(hŒkThe route manipulation functions. Should conform pretty closely to the
corresponding functions in fib_hash.”h]”hŒkThe route manipulation functions. Should conform pretty closely to the
corresponding functions in fib_hash.”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Kbhj  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h Kchj¼  hžhubhà)”}”(hŒtfn_trie_flush()
This walks the full trie (using nextleaf()) and searches for empty
leaves which have to be removed.
”h]”(hæ)”}”(hŒfn_trie_flush()”h]”hŒfn_trie_flush()”…””}”(hj;  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h Kghj7  ubhö)”}”(hhh]”hû)”}”(hŒcThis walks the full trie (using nextleaf()) and searches for empty
leaves which have to be removed.”h]”hŒcThis walks the full trie (using nextleaf()) and searches for empty
leaves which have to be removed.”…””}”(hjL  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KfhjI  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhj7  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h Kghj¼  hžhubhà)”}”(hX	  fn_trie_dump()
Dumps the routing table ordered by prefix length. This is somewhat
slower than the corresponding fib_hash function, as we have to walk the
entire trie for each prefix length. In comparison, fib_hash is organized
as one "zone"/hash per prefix length.
”h]”(hæ)”}”(hŒfn_trie_dump()”h]”hŒfn_trie_dump()”…””}”(hjj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1håhŸh³h Kmhjf  ubhö)”}”(hhh]”hû)”}”(hŒùDumps the routing table ordered by prefix length. This is somewhat
slower than the corresponding fib_hash function, as we have to walk the
entire trie for each prefix length. In comparison, fib_hash is organized
as one "zone"/hash per prefix length.”h]”hŒýDumps the routing table ordered by prefix length. This is somewhat
slower than the corresponding fib_hash function, as we have to walk the
entire trie for each prefix length. In comparison, fib_hash is organized
as one â€œzoneâ€/hash per prefix length.”…””}”(hj{  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Kjhjx  ubah}”(h]”h ]”h"]”h$]”h&]”uh1hõhjf  ubeh}”(h]”h ]”h"]”h$]”h&]”uh1hßhŸh³h Kmhj¼  hžhubeh}”(h]”h ]”h"]”h$]”h&]”uh1hÚhj  hžhhŸh³h Nubeh}”(h]”Œcomments”ah ]”h"]”Œcomments”ah$]”h&]”uh1h´hh¶hžhhŸh³h K=ubhµ)”}”(hhh]”(hº)”}”(hŒLocking”h]”hŒLocking”…””}”(hj¦  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¹hj£  hžhhŸh³h Kpubhû)”}”(hX  fib_lock is used for an RW-lock in the same way that this is done in fib_hash.
However, the functions are somewhat separated for other possible locking
scenarios. It might conceivably be possible to run trie_rebalance via RCU
to avoid read_lock in the fn_trie_lookup() function.”h]”hX  fib_lock is used for an RW-lock in the same way that this is done in fib_hash.
However, the functions are somewhat separated for other possible locking
scenarios. It might conceivably be possible to run trie_rebalance via RCU
to avoid read_lock in the fn_trie_lookup() function.”…””}”(hj´  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h Krhj£  hžhubeh}”(h]”Œlocking”ah ]”h"]”Œlocking”ah$]”h&]”uh1h´hh¶hžhhŸh³h Kpubhµ)”}”(hhh]”(hº)”}”(hŒMain lookup mechanism”h]”hŒMain lookup mechanism”…””}”(hjÍ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1h¹hjÊ  hžhhŸh³h Kxubhû)”}”(hŒ-fn_trie_lookup() is the main lookup function.”h]”hŒ-fn_trie_lookup() is the main lookup function.”…””}”(hjÛ  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KyhjÊ  hžhubhû)”}”(hŒÐThe lookup is in its simplest form just like fib_find_node(). We descend the
trie, key segment by key segment, until we find a leaf. check_leaf() does
the fib_semantic_match in the leaf's sorted prefix hlist.”h]”hŒÒThe lookup is in its simplest form just like fib_find_node(). We descend the
trie, key segment by key segment, until we find a leaf. check_leaf() does
the fib_semantic_match in the leafâ€™s sorted prefix hlist.”…””}”(hjé  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K{hjÊ  hžhubhû)”}”(hŒ If we find a match, we are done.”h]”hŒ If we find a match, we are done.”…””}”(hj÷  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KhjÊ  hžhubhû)”}”(hXN  If we don't find a match, we enter prefix matching mode. The prefix length,
starting out at the same as the key length, is reduced one step at a time,
and we backtrack upwards through the trie trying to find a longest matching
prefix. The goal is always to reach a leaf and get a positive result from the
fib_semantic_match mechanism.”h]”hXP  If we donâ€™t find a match, we enter prefix matching mode. The prefix length,
starting out at the same as the key length, is reduced one step at a time,
and we backtrack upwards through the trie trying to find a longest matching
prefix. The goal is always to reach a leaf and get a positive result from the
fib_semantic_match mechanism.”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KhjÊ  hžhubhû)”}”(hŒôInside each tnode, the search for longest matching prefix consists of searching
through the child array, chopping off (zeroing) the least significant "1" of
the child index until we find a match or the child index consists of nothing but
zeros.”h]”hŒøInside each tnode, the search for longest matching prefix consists of searching
through the child array, chopping off (zeroing) the least significant â€œ1â€ of
the child index until we find a match or the child index consists of nothing but
zeros.”…””}”(hj  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K‡hjÊ  hžhubhû)”}”(hŒ“At this point we backtrack (t->stats.backtrack++) up the trie, continuing to
chop off part of the key in order to find the longest matching prefix.”h]”hŒ“At this point we backtrack (t->stats.backtrack++) up the trie, continuing to
chop off part of the key in order to find the longest matching prefix.”…””}”(hj!  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KŒhjÊ  hžhubhû)”}”(hŒçAt this point we will repeatedly descend subtries to look for a match, and there
are some optimizations available that can provide us with "shortcuts" to avoid
descending into dead ends. Look for "HL_OPTIMIZE" sections in the code.”h]”hŒïAt this point we will repeatedly descend subtries to look for a match, and there
are some optimizations available that can provide us with â€œshortcutsâ€ to avoid
descending into dead ends. Look for â€œHL_OPTIMIZEâ€ sections in the code.”…””}”(hj/  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h KhjÊ  hžhubhû)”}”(hŒ¿To alleviate any doubts about the correctness of the route selection process,
a new netlink operation has been added. Look for NETLINK_FIB_LOOKUP, which
gives userland access to fib_lookup().”h]”hŒ¿To alleviate any doubts about the correctness of the route selection process,
a new netlink operation has been added. Look for NETLINK_FIB_LOOKUP, which
gives userland access to fib_lookup().”…””}”(hj=  hžhhŸNh Nubah}”(h]”h ]”h"]”h$]”h&]”uh1húhŸh³h K“hjÊ  hžhubeh}”(h]”Œmain-lookup-mechanism”ah ]”h"]”Œmain lookup mechanism”ah$]”h&]”uh1h´hh¶hžhhŸh³h Kxubeh}”(h]”Œlc-trie-implementation-notes”ah ]”h"]”Œlc-trie implementation notes”ah$]”h&]”uh1h´hhhžhhŸh³h Kubeh}”(h]”h ]”h"]”h$]”h&]”Œsource”h³uh1hŒcurrent_source”NŒcurrent_line”NŒsettings”Œdocutils.frontend”ŒValues”“”)”}”(h¹NŒ	generator”NŒ	datestamp”NŒsource_link”NŒ
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id_counter”Œcollections”ŒCounter”“”}”…”R”Œparse_messages”]”Œtransform_messages”]”Œtransformer”NŒinclude_log”]”Œ
decoration”Nhžhub.