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| <title>Associative-Container Performance Tests</title> |
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| <div id="page"> |
| <h1><a name="assoc" id="assoc">Associative-Container |
| Performance Tests</a></h1> |
| <h2><a name="settings" id="settings">Settings</a></h2> |
| <p>This section describes performance tests and their results. |
| In the following, <a href="#gcc"><u>g++</u></a>, <a href="#msvc"><u>msvc++</u></a>, and <a href="#local"><u>local</u></a> (the build used for generating this |
| documentation) stand for three different builds:</p> |
| <div id="gcc_settings_div"> |
| <div class="c1"> |
| <h3><a name="gcc" id="gcc"><u>g++</u></a></h3> |
| <ul> |
| <li>CPU speed - cpu MHz : 2660.644</li> |
| <li>Memory - MemTotal: 484412 kB</li> |
| <li>Platform - |
| Linux-2.6.12-9-386-i686-with-debian-testing-unstable</li> |
| <li>Compiler - g++ (GCC) 4.0.2 20050808 (prerelease) |
| (Ubuntu 4.0.1-4ubuntu9) Copyright (C) 2005 Free Software |
| Foundation, Inc. This is free software; see the source |
| for copying conditions. There is NO warranty; not even |
| for MERCHANTABILITY or FITNESS FOR A PARTICULAR |
| PURPOSE.</li> |
| </ul> |
| </div> |
| <div class="c2"></div> |
| </div> |
| <div id="msvc_settings_div"> |
| <div class="c1"> |
| <h3><a name="msvc" id="msvc"><u>msvc++</u></a></h3> |
| <ul> |
| <li>CPU speed - cpu MHz : 2660.554</li> |
| <li>Memory - MemTotal: 484412 kB</li> |
| <li>Platform - Windows XP Pro</li> |
| <li>Compiler - Microsoft (R) 32-bit C/C++ Optimizing |
| Compiler Version 13.10.3077 for 80x86 Copyright (C) |
| Microsoft Corporation 1984-2002. All rights |
| reserved.</li> |
| </ul> |
| </div> |
| <div class="c2"></div> |
| </div> |
| <div id="local_settings_div"><div style = "border-style: dotted; border-width: 1px; border-color: lightgray"><h3><a name = "local"><u>local</u></a></h3><ul> |
| <li>CPU speed - cpu MHz : 2250.000</li> |
| <li>Memory - MemTotal: 2076248 kB</li> |
| <li>Platform - Linux-2.6.16-1.2133_FC5-i686-with-redhat-5-Bordeaux</li> |
| <li>Compiler - g++ (GCC) 4.1.1 20060525 (Red Hat 4.1.1-1) |
| Copyright (C) 2006 Free Software Foundation, Inc. |
| This is free software; see the source for copying conditions. There is NO |
| warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
| </li> |
| </ul> |
| </div><div style = "width: 100%; height: 20px"></div></div> |
| <h2><a name="assoc_tests" id="assoc_tests">Tests</a></h2> |
| <h3><a name="hash_based" id="hash_based">Hash-Based |
| Containers</a></h3> |
| <ol> |
| <li><a href="hash_text_find_find_timing_test.html">Hash-Based |
| Text <tt>find</tt> Find Timing Test</a></li> |
| <li><a href="hash_random_int_find_find_timing_test.html">Hash-Based |
| Random-Integer <tt>find</tt> Find Timing Test</a></li> |
| <li><a href="hash_random_int_subscript_find_timing_test.html">Hash-Based |
| Random-Integer Subscript Find Timing Test</a></li> |
| <li><a href="hash_random_int_subscript_insert_timing_test.html">Hash-Based |
| Random-Integer Subscript Insert Timing Test</a></li> |
| <li><a href="hash_zlob_random_int_find_find_timing_test.html">Hash-Based |
| Skewed-Distribution Random-Integer <tt>find</tt> Find Timing |
| Test</a></li> |
| <li><a href="hash_random_int_erase_mem_usage_test.html">Hash-Based Erase |
| Memory Use Test</a></li> |
| </ol> |
| <h3><a name="tree_like_based" id="tree_like_based">Tree-Like-Based Containers</a></h3> |
| <ol> |
| <li><a href="tree_text_insert_timing_test.html">Tree-Based |
| and Trie-Based Text Insert Timing Test</a></li> |
| <li><a href="tree_text_find_find_timing_test.html">Tree-Based |
| and Trie-Based Text <tt>find</tt> Find Timing Test</a></li> |
| <li><a href="tree_text_lor_find_find_timing_test.html">Tree-Based |
| Locality-of-Reference Text <tt>find</tt> Find Timing |
| Test</a></li> |
| <li><a href="tree_random_int_find_find_timing_test.html">Tree-Based |
| Random-Integer <tt>find</tt> Find Timing Test</a></li> |
| <li><a href="tree_split_join_timing_test.html">Tree Split and |
| Join Timing Test</a></li> |
| <li><a href="tree_order_statistics_timing_test.html">Tree |
| Order-Statistics Timing Test</a></li> |
| </ol> |
| <h3><a name="multimaps" id="multimaps">Multimaps</a></h3> |
| <ol> |
| <li><a href="multimap_text_find_timing_test_small.html">"Multimap" |
| Text Find Timing Test with <u>Small</u> Average Secondary-Key |
| to Primary-Key Ratio</a></li> |
| <li><a href="multimap_text_find_timing_test_large.html">"Multimap" |
| Text Find Timing Test with <u>Large</u> Average Secondary-Key |
| to Primary-Key Ratio</a></li> |
| <li><a href="multimap_text_insert_timing_test_small.html">"Multimap" |
| Text Insert Timing Test with <u>Small</u> Average |
| Secondary-Key to Primary-Key Ratio</a></li> |
| <li><a href="multimap_text_insert_timing_test_large.html">"Multimap" |
| Text Insert Timing Test with <u>Large</u> Average |
| Secondary-Key to Primary-Key Ratio</a></li> |
| <li><a href="multimap_text_insert_mem_usage_test_small.html">"Multimap" |
| Text Insert Memory-Use Test with <u>Small</u> Average |
| Secondary-Key to Primary-Key Ratio</a></li> |
| <li><a href="multimap_text_insert_mem_usage_test_large.html">"Multimap" |
| Text Insert Memory-Use Test with <u>Large</u> Average |
| Secondary-Key to Primary-Key Ratio</a></li> |
| </ol> |
| <h2><a name="assoc_observations" id="assoc_observations">Observations</a></h2> |
| <h3><a name="dss_family_choice" id="dss_family_choice">Underlying Data-Structure Families</a></h3> |
| <p>In general, hash-based containers (see <a href="hash_based_containers.html">Design::Associative |
| Containers::Hash-Based Containers</a>) have better timing |
| performance than containers based on different underlying-data |
| structures. The main reason to choose a tree-based (see |
| <a href="tree_based_containers.html">Design::Associative |
| Containers::Tree-Based Containers</a>) or trie-based container |
| (see <a href="trie_based_containers.html">Design::Associative |
| Containers::Trie-Based Containers</a>) is if a byproduct of the |
| tree-like structure is required: either order-preservation, or |
| the ability to utilize node invariants (see <a href="tree_based_containers.html#invariants">Design::Associative |
| Containers::Tree-Based Containers::Node Invariants</a> and |
| <a href="trie_based_containers.html#invariants">Design::Associative |
| Containers::Trie-Based Containers::Node Invariants</a>). If |
| memory-use is the major factor, an ordered-vector tree (see |
| <a href="tree_based_containers.html">Design::Associative |
| Containers::Tree-Based Containers</a>) gives optimal results |
| (albeit with high modificiation costs), and a list-based |
| container (see <a href="lu_based_containers.html">Design::Associative |
| Containers::List-Based Containers</a>) gives reasonable |
| results.</p> |
| <h3><a name="hash_based_types" id="hash_based_types">Hash-Based |
| Container Types</a></h3> |
| <p>Hash-based containers are typically either collision |
| chaining or probing (see <a href="hash_based_containers.html">Design::Associative |
| Containers::Hash-Based Containers</a>). Collision-chaining |
| containers are more flexible internally, and so offer better |
| timing performance. Probing containers, if used for simple |
| value-types, manage memory more efficiently (they perform far |
| fewer allocation-related calls). In general, therefore, a |
| collision-chaining table should be used. A probing container, |
| conversely, might be used efficiently for operations such as |
| eliminating duplicates in a sequence, or counting the number of |
| occurrences within a sequence. Probing containers might be more |
| useful also in multithreaded applications where each thread |
| manipulates a hash-based container: in the STL, allocators have |
| class-wise semantics (see [<a href="references.html#meyers96more">meyers96more</a>] - Item 10); a |
| probing container might incur less contention in this case.</p> |
| <h3><a name="hash_based_policies" id="hash_based_policies">Hash-Based Containers' Policies</a></h3> |
| <p>In hash-based containers, the range-hashing scheme (see |
| <a href="hash_based_containers.html#hash_policies">Design::Associative |
| Containers::Hash-Based Containers::Hash Policies</a>) seems to |
| affect performance more than other considerations. In most |
| settings, a mask-based scheme works well (or can be made to |
| work well). If the key-distribution can be estimated a-priori, |
| a simple hash function can produce nearly uniform hash-value |
| distribution. In many other cases (<i>e.g.</i>, text hashing, |
| floating-point hashing), the hash function is powerful enough |
| to generate hash values with good uniformity properties |
| [<a href="references.html#knuth98sorting">knuth98sorting</a>]; |
| a modulo-based scheme, taking into account all bits of the hash |
| value, appears to overlap the hash function in its effort.</p> |
| <p>The range-hashing scheme determines many of the other |
| policies (see <a href="hash_based_containers.html#policy_interaction">Design::Hash-Based |
| Containers::Policy Interaction</a>). A mask-based scheme works |
| well with an exponential-size policy (see <a href="hash_based_containers.html#resize_policies">Design::Associative |
| Containers::Hash-Based Containers::Resize Policies</a>) ; for |
| probing-based containers, it goes well with a linear-probe |
| function (see <a href="hash_based_containers.html#hash_policies">Design::Associative |
| Containers::Hash-Based Containers::Hash Policies</a>).</p> |
| <p>An orthogonal consideration is the trigger policy (see |
| <a href="hash_based_containers.html#resize_policies">Design::Associative |
| Containers::Hash-Based Containers::Resize Policies</a>). This |
| presents difficult tradeoffs. <i>E.g.</i>, different load |
| factors in a load-check trigger policy yield a |
| space/amortized-cost tradeoff.</p> |
| <h3><a name="tree_like_based_types" id="tree_like_based_types">Tree-Like-Based Container |
| Types</a></h3> |
| <p>In general, there are several families of tree-based |
| underlying data structures: balanced node-based trees |
| (<i>e.g.</i>, red-black or AVL trees), high-probability |
| balanced node-based trees (<i>e.g.</i>, random treaps or |
| skip-lists), competitive node-based trees (<i>e.g.</i>, splay |
| trees), vector-based "trees", and tries. (Additionally, there |
| are disk-residing or network-residing trees, such as B-Trees |
| and their numerous variants. An interface for this would have |
| to deal with the execution model and ACID guarantees; this is |
| out of the scope of this library.) Following are some |
| observations on their application to different settings.</p> |
| <p>Of the balanced node-based trees, this library includes a |
| red-black tree (see <a href="tree_based_containers.html">Design::Associative |
| Containers::Tree-Based Containers</a>), as does STL (in |
| practice). This type of tree is the "workhorse" of tree-based |
| containers: it offers both reasonable modification and |
| reasonable lookup time. Unfortunately, this data structure |
| stores a huge amount of metadata. Each node must contain, |
| besides a value, three pointers and a boolean. This type might |
| be avoided if space is at a premium [<a href="references.html#austern00noset">austern00noset</a>].</p> |
| <p>High-probability balanced node-based trees suffer the |
| drawbacks of deterministic balanced trees. Although they are |
| fascinating data structures, preliminary tests with them showed |
| their performance was worse than red-black trees. The library |
| does not contain any such trees, therefore.</p> |
| <p>Competitive node-based trees have two drawbacks. They are |
| usually somewhat unbalanced, and they perform a large number of |
| comparisons. Balanced trees perform one comparison per each |
| node they encounter on a search path; a splay tree performs two |
| comparisons. If the keys are complex objects, <i>e.g.</i>, |
| <tt>std::string</tt>, this can increase the running time. |
| Conversely, such trees do well when there is much locality of |
| reference. It is difficult to determine in which case to prefer |
| such trees over balanced trees. This library includes a splay |
| tree (see <a href="tree_based_containers.html">Design::Associative |
| Containers::Tree-Based Containers</a>).</p> |
| <p>Ordered-vector trees (see <a href="tree_based_containers.html">Design::Associative |
| Containers::Tree-Based Containers</a>) use very little space |
| [<a href="references.html#austern00noset">austern00noset</a>]. |
| They do not have any other advantages (at least in this |
| implementation).</p> |
| <p>Large-fan-out PATRICIA tries (see <a href="trie_based_containers.html">Design::Associative |
| Containers::Trie-Based Containers</a>) have excellent lookup |
| performance, but they do so through maintaining, for each node, |
| a miniature "hash-table". Their space efficiency is low, and |
| their modification performance is bad. These tries might be |
| used for semi-static settings, where order preservation is |
| important. Alternatively, red-black trees cross-referenced with |
| hash tables can be used. [<a href="references.html#okasaki98mereable">okasaki98mereable</a>] |
| discusses small-fan-out PATRICIA tries for integers, but the |
| cited results seem to indicate that the amortized cost of |
| maintaining such trees is higher than that of balanced trees. |
| Moderate-fan-out trees might be useful for sequences where each |
| element has a limited number of choices, <i>e.g.</i>, DNA |
| strings (see <a href="assoc_examples.html#trie_based">Examples::Associative |
| Containers::Trie-Based Containers</a>).</p> |
| <h3><a name="msc" id="msc">Mapping-Semantics |
| Considerations</a></h3> |
| <p>Different mapping semantics were discussed in <a href="motivation.html#assoc_mapping_semantics">Motivation::Associative |
| Containers::Alternative to Multiple Equivalent Keys</a> and |
| <a href="tutorial.html#assoc_ms">Tutorial::Associative |
| Containers::Associative Containers Others than Maps</a>. We |
| will focus here on the case where a keys can be composed into |
| primary keys and secondary keys. (In the case where some keys |
| are completely identical, it is trivial that one should use an |
| associative container mapping values to size types.) In this |
| case there are (at least) five possibilities:</p> |
| <ol> |
| <li>Use an associative container that allows equivalent-key |
| values (such as <tt>std::multimap</tt>)</li> |
| <li>Use a unique-key value associative container that maps |
| each primary key to some complex associative container of |
| secondary keys, say a tree-based or hash-based container (see |
| <a href="tree_based_containers.html">Design::Associative |
| Containers::Tree-Based Containers</a> and <a href="hash_based_containers.html">Design::Associative |
| Containers::Hash-Based Containers</a>)</li> |
| <li>Use a unique-key value associative container that maps |
| each primary key to some simple associative container of |
| secondary keys, say a list-based container (see <a href="lu_based_containers.html">Design::Associative |
| Containers::List-Based Containers</a>)</li> |
| <li>Use a unique-key value associative container that maps |
| each primary key to some non-associative container |
| (<i>e.g.</i>, <tt>std::vector</tt>)</li> |
| <li>Use a unique-key value associative container that takes |
| into account both primary and secondary keys.</li> |
| </ol> |
| <p>We do not think there is a simple answer for this (excluding |
| option 1, which we think should be avoided in all cases).</p> |
| <p>If the expected ratio of secondary keys to primary keys is |
| small, then 3 and 4 seem reasonable. Both types of secondary |
| containers are relatively lightweight (in terms of memory use |
| and construction time), and so creating an entire container |
| object for each primary key is not too expensive. Option 4 |
| might be preferable to option 3 if changing the secondary key |
| of some primary key is frequent - one cannot modify an |
| associative container's key, and the only possibility, |
| therefore, is erasing the secondary key and inserting another |
| one instead; a non-associative container, conversely, can |
| support in-place modification. The actual cost of erasing a |
| secondary key and inserting another one depends also on the |
| allocator used for secondary associative-containers (The tests |
| above used the standard allocator, but in practice one might |
| choose to use, <i>e.g.</i>, [<a href="references.html#boost_pool">boost_pool</a>]). Option 2 is |
| definitely an overkill in this case. Option 1 loses out either |
| immediately (when there is one secondary key per primary key) |
| or almost immediately after that. Option 5 has the same |
| drawbacks as option 2, but it has the additional drawback that |
| finding all values whose primary key is equivalent to some key, |
| might be linear in the total number of values stored (for |
| example, if using a hash-based container).</p> |
| <p>If the expected ratio of secondary keys to primary keys is |
| large, then the answer is more complicated. It depends on the |
| distribution of secondary keys to primary keys, the |
| distribution of accesses according to primary keys, and the |
| types of operations most frequent.</p> |
| <p>To be more precise, assume there are <i>m</i> primary keys, |
| primary key <i>i</i> is mapped to <i>n<sub>i</sub></i> |
| secondary keys, and each primary key is mapped, on average, to |
| <i>n</i> secondary keys (<i>i.e.</i>, |
| <i><b>E</b>(n<sub>i</sub>) = n</i>).</p> |
| <p>Suppose one wants to find a specific pair of primary and |
| secondary keys. Using 1 with a tree based container |
| (<tt>std::multimap</tt>), the expected cost is |
| <i><b>E</b>(Θ(log(m) + n<sub>i</sub>)) = Θ(log(m) + |
| n)</i>; using 1 with a hash-based container |
| (<tt>std::tr1::unordered_multimap</tt>), the expected cost is |
| <i>Θ(n)</i>. Using 2 with a primary hash-based container |
| and secondary hash-based containers, the expected cost is |
| <i>O(1)</i>; using 2 with a primary tree-based container and |
| secondary tree-based containers, the expected cost is (using |
| the Jensen inequality [<a href="references.html#motwani95random">motwani95random</a>]) |
| <i><b>E</b>(O(log(m) + log(n<sub>i</sub>)) = O(log(m)) + |
| <b>E</b>(O(log(n<sub>i</sub>)) = O(log(m)) + O(log(n))</i>, |
| assuming that primary keys are accessed equiprobably. 3 and 4 |
| are similar to 1, but with lower constants. Using 5 with a |
| hash-based container, the expected cost is <i>O(1)</i>; using 5 |
| with a tree based container, the cost is |
| <i><b>E</b>(Θ(log(mn))) = Θ(log(m) + |
| log(n))</i>.</p> |
| <p>Suppose one needs the values whose primary key matches some |
| given key. Using 1 with a hash-based container, the expected |
| cost is <i>Θ(n)</i>, but the values will not be ordered |
| by secondary keys (which may or may not be required); using 1 |
| with a tree-based container, the expected cost is |
| <i>Θ(log(m) + n)</i>, but with high constants; again the |
| values will not be ordered by secondary keys. 2, 3, and 4 are |
| similar to 1, but typically with lower constants (and, |
| additionally, if one uses a tree-based container for secondary |
| keys, they will be ordered). Using 5 with a hash-based |
| container, the cost is <i>Θ(mn)</i>.</p> |
| <p>Suppose one wants to assign to a primary key all secondary |
| keys assigned to a different primary key. Using 1 with a |
| hash-based container, the expected cost is <i>Θ(n)</i>, |
| but with very high constants; using 1 with a tree-based |
| container, the cost is <i>Θ(nlog(mn))</i>. Using 2, 3, |
| and 4, the expected cost is <i>Θ(n)</i>, but typically |
| with far lower costs than 1. 5 is similar to 1.</p> |
| </div> |
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