| ShoutBox |
| Timo: Ein paar Worte zu deinen drei Punkten: Ja, die Implementierung macht natürlich eine binäre Suche auf den sortierten Schlüsselwerten in einem Knoten. Jedoch würde ich binäre Bäume nicht als Sicherheitsrisiko, sondern als Performance- oder Skalierungsproblem bezeichnen. Der B-Baum verbraucht verglichen mit dem Binärbaum zwar insgesamt mehr Speicher, aber immer in zusammenhängenden Blöcken. Ob virtuellen oder realen Speicher ist erstmal egal. Durch die größeren Speicherblöcke wird die L1/L2 Cache-Hitrate verbessert, dies zu zeigen war eines der Ausgangspunkte, wie auch in der Zusammenfassung steht. Was an dem direkten Vergleich "unfair" sein soll verstehe ich nicht. Er war Ausgangsüberlegung der Arbeit. Darüber steht aber viel mehr im englischen Text. |
Frank Mertens : Der Performance-Vergleich ist etwas unfair gegenüber den Binär-Bäumen. Wäre schön, wenn folgende Punkte Erwähnung fänden:
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The STX B+ Tree package is a set of C++ template classes implementing a B+ tree key/data container in main memory. The classes are designed as drop-in replacements of the STL containers set, map, multiset and multimap and follow their interfaces very closely. By packing multiple value pairs into each node of the tree the B+ tree reduces heap fragmentation and utilizes cache-line effects better than the standard red-black binary tree. The tree algorithms are based on the implementation in Cormen, Leiserson and Rivest's Introduction into Algorithms, Jan Jannink's paper and other algorithm resources. The classes contain extensive assertion and verification mechanisms to ensure the implementation's correctness by testing the tree invariants. To illustrate the B+ tree's structure a wxWidgets demo program is included in the source package.
The main B+ tree implementation can be found in doxygen stx/btree.h or with plain text comments btree.h.
Special interest was put into performing a speed comparison test between the standard red-black tree and the new B+ tree implementation. The speed test results are interesting and show the B+ tree to be significantly faster for trees containing more than 16,000 items.
The B+ tree main header code is covered to 91.9% by test cases. A graphical display of the test suite's coverage can be viewed online.
The package now includes a demo program, which illustrates how the B+ tree organises integer and string keys. Compiled binaries for Windows and and some Linux distributions are available on the demo download page.
See the README file below for a more detailed overview. See ChangeLog below on what changed in version 0.8.3.
| STX B+ Tree Version 0.8.3 (current) released 2008-09-07 | ||
| Source code archive: (includes Doxygen HTML) | Download stx-btree-0.8.3.tar.bz2 (932kb) MD5: 1c13439c5d6ca6ba8bfce6b39f1ca65c | Browse online |
| ChangeLog | ||
| Extensive Documentation: | Browse documentation online | |
| Demo Binaries: | See Extra Download Page for Win32 and Linux binaries. | |
See bottom of this page for older downloads.
The complete source code is released under the GNU Lesser General Public License v2.1 (LGPL).
The subversion repository containing all sources and packages is available at http://idlebox.net/2007/stx-btree/svn/.
Some further papers, documentation and some future branches are also available there.
The idea originally arose while coding a read-only database, which used a huge map of millions of non-sequential integer keys to 8-byte file offsets. When using the standard STL red-black tree implementation this would yield millions of 20-byte heap allocations and very slow search times due to the tree's height. So the original intension was to reduce memory fragmentation and improve search times. The B+ tree solves this by packing multiple data pairs into one node with a large number of descendant nodes.
In computer science lectures it is often stated that using consecutive bytes in memory would be more cache-efficient, because the CPU's cache levels always fetch larger blocks from main memory. So it would be best to store the keys of a node in one continuous array. This way the inner scanning loop would be accelerated by benefiting from cache effects and pipelining speed-ups. Thus the cost of scanning for a matching key would be lower than in a red-black tree, even though the number of key comparisons are theoretically larger. This second aspect aroused my academic interest and resulted in the speed test experiments.
A third inspiration was that no working C++ template implementation of a B+ tree could be found on the Internet. Now this one can be found.
This implementation contains five main classes within the stx namespace (blandly named Some Template eXtensions). The base class btree implements the B+ tree algorithms using inner and leaf nodes in main memory. Almost all STL-required function calls are implemented (see below for the exceptions). The asymptotic time requirements of the STL standard are theoretically not always fulfilled. However in practice this B+ tree performs better than the STL's red-black tree at the cost of using more memory. See the speed test results for details.
The base class is then specialized into btree_set, btree_multiset, btree_map and btree_multimap using default template parameters and facade functions. These classes are designed to be drop-in replacements for the corresponding STL containers.
The insertion function splits the nodes on recursion unroll. Erase is largely based on Jannink's ideas. See http://dbpubs.stanford.edu:8090/pub/1995-19 for his paper on "Implementing Deletion in B+-trees".
The two set classes (btree_set and btree_multiset) are derived from the base implementation class btree by specifying an empty struct as data_type. All functions are adapted to provide the base class with empty placeholder objects. Note that it is somewhat inefficient to implement a set or multiset using a B+ tree: a plain B tree (without +) would hold no extra copies of the keys. The main focus was on implementing the maps.
The most noteworthy difference to the default red-black tree implementation of std::map is that the B+ tree does not hold key/data pairs together in memory. Instead each B+ tree node has two separate arrays containing keys and data values. This design was chosen to utilize cache-line effects while scanning the key array.
However it also directly generates many problems in implementing the iterators' operators. These return a (writable) reference or pointer to a value_type, which is a std::pair composition. These data/key pairs however are not stored together and thus a temporary copy must be constructed. This copy should not be written to, because it is not stored back into the B+ tree. This effectively prohibits use of many STL algorithms which writing to the B+ tree's iterators. I would be grateful for hints on how to resolve this problem without folding the key and data arrays.
The B+ tree distribution contains an extensive test suite using cppunit. According to gcov 91.9% of the btree.h implementation is covered.
The tree algorithms currently do not use copy-construction. All key/data items are allocated in the nodes using the default-constructor and are subsequently only assigned new data (using operator=).
The most important incompatibility are the non-writable operator* and operator-> of the iterator. See above for a discussion of the problem on separated key/data arrays. Instead of *iter and iter-> use the new function iter.data() which returns a writable reference to the data value in the tree.
The B+ tree supports only two erase functions:
The following STL-required functions are not supported:
Beyond the usual STL interface the B+ tree classes support some extra goodies.
All tree template classes take a template parameter structure which holds important options of the implementation. The following structure shows which static variables specify the options and the corresponding defaults:
The implementation was tested using the speed test sources contained in the package. For a long discussion please see the results web page within the documentation.
__gnu_cxx. Extending tests by another set of runs measuring only the find/lookup functions.verify() on an empty btree object. Now the root node is freed when the last item is removed. Also fixing crash when attempting to copy an empty btree or when trying to remove a non-existing item from an empty btree./ 2 integer divisions with >> 1 as suggested by received e-mails. This may or may not improve speed. I personally doubt it, because modern compilers should optimize these simple instructions.reverse_iterator classes. Now they are real implementations and do not use STL magic. Both reverse_iterator and const_reverse_iterator should work as expected now. Added two large test cases for iterators. Also enabling public Default-Constructor on iterators.leaf->slotkey[leaf->slotuse - 1] if leaf-slotuse == 0. This doesnt have any other bad effect, because the case only occurs when leaf == root and thus the btree_update_lastkey message is never really processed. However it still is a bad-memory access.find() function find_lower() is called and returns the slot number with the smallest or equal key. However if the queried key is larger than all keys in a leaf node or in the whole tree, find_lower() returns a slot number past the last valid key slot. Comparison of this invalid slot with the queried key then yields an uninitialized memory error in valgrind.print() because of non-existing root. Fixed segfault in end() when the tree is totally empty. Added BTREE_FRIENDS macro so that wxBTreeDemo can access private members. Changing print function to output to a user-given std::ostream| STX B+ Tree Version 0.8.2 released 2008-08-13 | ||
| Source code archive: (includes Doxygen HTML) | Download stx-btree-0.8.2.tar.bz2 (788kb) MD5: bf147a1f2f9a540d283244e5a92c5353 | Browse online |
| ChangeLog | ||
| Extensive Documentation: | Browse documentation online | |
| STX B+ Tree Version 0.8.1 released 2008-01-25 | ||
| Source code archive: | Download stx-btree-0.8.1.tar.bz2 (412kb) MD5: 87df74dab5c5b2a34c6ebfbfc224b26b | Browse online |
| ChangeLog | ||
| Extensive Documentation: | Download stx-btree-0.8.1-doxygen.tar.bz2 (310kb) MD5: f7801dd6e8672820a599704a7fd7df4f | Browse documentation online |
| STX B+ Tree Version 0.8 released 2007-05-13 | ||
| Source code archive: | Download stx-btree-0.8.tar.bz2 (411kb) MD5: b3e2981dff63d9a01bfc0a102a49c32c | Browse online |
| ChangeLog | ||
| Extensive Documentation: | Download stx-btree-0.8-doxygen.tar.bz2 (324kb) MD5: 7e14e8eb904129f77d96c8abb517068d | Browse documentation online |
| STX B+ Tree Version 0.7 released 2007-04-27 | ||
| Source code archive: | Download stx-btree-0.7.tar.bz2 (360kb) MD5: b10da911facd14f4faa6f31b43fd0591 | Browse online |
| Extensive Documentation: | Download stx-btree-0.7-doxygen.tar.bz2 (291kb) MD5: a4106a81fb5982a3bc5fcb822f85d219 | Browse documentation online |