forked from OSchip/llvm-project
parent
db83265e3c
commit
f233c425cd
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@ -55,6 +55,7 @@ option</a></li>
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<li><a href="#dss_deque"><deque></a></li>
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<li><a href="#dss_list"><list></a></li>
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<li><a href="#dss_ilist">llvm/ADT/ilist</a></li>
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<li><a href="#dss_other">Other Sequential Container Options</a></li>
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</ul></li>
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<li><a href="#ds_set">Set-Like Containers (std::set, SmallSet, SetVector, etc)</a>
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<ul>
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@ -64,7 +65,8 @@ option</a></li>
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<li><a href="#dss_FoldingSet">"llvm/ADT/FoldingSet.h"</a></li>
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<li><a href="#dss_set"><set></a></li>
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<li><a href="#dss_setvector">"llvm/ADT/SetVector.h"</a></li>
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<li><a href="#dss_otherset">Other Options</a></li>
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<li><a href="#dss_uniquevector">"llvm/ADT/UniqueVector.h"</a></li>
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<li><a href="#dss_otherset">Other Set-Like ContainerOptions</a></li>
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</ul></li>
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<li><a href="#ds_map">Map-Like Containers (std::map, DenseMap, etc)</a></li>
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</ul>
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@ -850,7 +852,7 @@ basic blocks, which is why these are implemented with ilists.</p>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_other">Other options</a>
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<a name="dss_other">Other Sequential Container options</a>
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</div>
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<div class="doc_text">
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@ -986,13 +988,14 @@ elements.
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<div class="doc_text">
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<p><tt>std::set</t> is a reasonable all-around set class, which is good at many
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things but great at nothing. std::set allocates memory for each element
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<p><tt>std::set</tt> is a reasonable all-around set class, which is decent at
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many things but great at nothing. std::set allocates memory for each element
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inserted (thus it is very malloc intensive) and typically stores three pointers
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per element in the set (thus adding a large amount of per-element space
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overhead). It offers guaranteed log(n) performance, which is not particularly
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fast, particularly if the elements of the set are expensive to compare (e.g.
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strings).</p>
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fast from a complexity standpoint (particularly if the elements of the set are
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expensive to compare, like strings), and has extremely high constant factors for
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lookup, insertion and removal.</p>
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<p>The advantages of std::set are that its iterators are stable (deleting or
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inserting an element from the set does not affect iterators or pointers to other
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@ -1036,14 +1039,34 @@ elements out of (linear time).
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_otherset">Other Options</a>
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<a name="dss_uniquevector">"llvm/ADT/UniqueVector.h"</a>
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</div>
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<div class="doc_text">
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<p>
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UniqueVector is similar to <a href="#dss_setvector">SetVector</a>, but it
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retains a unique ID for each element inserted into the set. It internally
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contains a map and a vector, and it assigns a unique ID for each value inserted
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into the set.</p>
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<p>UniqueVector is very expensive: its cost is the sum of the cost of
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maintaining both the map and vector, it has high complexity, high constant
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factors, and produces a lot of malloc traffic. It should be avoided.</p>
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_otherset">Other Set-Like Container Options</a>
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</div>
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<div class="doc_text">
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<p>
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The STL provides several other options, such as std::multiset and the various
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"hash_set" like containers (whether from C++TR1 or from the SGI library).</p>
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"hash_set" like containers (whether from C++ TR1 or from the SGI library).</p>
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<p>std::multiset is useful if you're not interested in elimination of
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duplicates, but has all the drawbacks of std::set. A sorted vector (where you
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@ -1066,13 +1089,151 @@ expensive. Element iteration does not visit elements in a useful order.</p>
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</div>
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<div class="doc_text">
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sorted vector
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std::map
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DenseMap
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UniqueVector
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IndexedMap
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hash_map
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CStringMap
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Map-like containers are useful when you want to associate data to a key. As
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usual, there are a lot of different ways to do this. :)
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_sortedvectormap">A sorted 'vector'</a>
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</div>
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<div class="doc_text">
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<p>
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If your usage pattern follows a strict insert-then-query approach, you can
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trivially use the same approach as <a href="#dss_sortedvectorset">sorted vectors
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for set-like containers</a>. The only difference is that your query function
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(which uses std::lower_bound to get efficient log(n) lookup) should only compare
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the key, not both the key and value. This yields the same advantages as sorted
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vectors for sets.
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</p>
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_cstringmap">"llvm/ADT/CStringMap.h"</a>
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</div>
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<div class="doc_text">
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<p>
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Strings are commonly used as keys in maps, and they are difficult to support
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efficiently: they are variable length, inefficient to hash and compare when
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long, expensive to copy, etc. CStringMap is a specialized container designed to
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cope with these issues. It supports mapping an arbitrary range of bytes that
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does not have an embedded nul character in it ("C strings") to an arbitrary
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other object.</p>
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<p>The CStringMap implementation uses a quadratically-probed hash table, where
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the buckets store a pointer to the heap allocated entries (and some other
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stuff). The entries in the map must be heap allocated because the strings are
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variable length. The string data (key) and the element object (value) are
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stored in the same allocation with the string data immediately after the element
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object. This container guarantees the "<tt>(char*)(&Value+1)</tt>" points
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to the key string for a value.</p>
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<p>The CStringMap is very fast for several reasons: quadratic probing is very
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cache efficient for lookups, the hash value of strings in buckets is not
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recomputed when lookup up an element, CStringMap rarely has to touch the
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memory for unrelated objects when looking up a value (even when hash collisions
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happen), hash table growth does not recompute the hash values for strings
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already in the table, and each pair in the map is store in a single allocation
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(the string data is stored in the same allocation as the Value of a pair).</p>
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<p>CStringMap also provides query methods that take byte ranges, so it only ever
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copies a string if a value is inserted into the table.</p>
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_indexedmap">"llvm/ADT/IndexedMap.h"</a>
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</div>
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<div class="doc_text">
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<p>
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IndexedMap is a specialized container for mapping small dense integers (or
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values that can be mapped to small dense integers) to some other type. It is
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internally implemented as a vector with a mapping function that maps the keys to
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the dense integer range.
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</p>
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<p>
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This is useful for cases like virtual registers in the LLVM code generator: they
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have a dense mapping that is offset by a compile-time constant (the first
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virtual register ID).</p>
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_densemap">"llvm/ADT/DenseMap.h"</a>
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</div>
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<div class="doc_text">
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<p>
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DenseMap is a simple quadratically probed hash table. It excels at supporting
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small keys and values: it uses a single allocation to hold all of the pairs that
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are currently inserted in the map. DenseMap is a great way to map pointers to
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pointers, or map other small types to each other.
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</p>
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<p>
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There are several aspects of DenseMap that you should be aware of, however. The
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iterators in a densemap are invalidated whenever an insertion occurs, unlike
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map. Also, because DenseMap allocates space for a large number of key/value
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pairs (it starts with 64 by default) if you have large keys or values, it can
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waste a lot of space. Finally, you must implement a partial specialization of
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DenseMapKeyInfo for the key that you want, if it isn't already supported. This
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is required to tell DenseMap about two special marker values (which can never be
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inserted into the map).</p>
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_map"><map></a>
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</div>
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<div class="doc_text">
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<p>
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std::map has similar characteristics to <a href="#dss_set">std::set</a>: it uses
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a single allocation per pair inserted into the map, it offers log(n) lookup with
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an extremely large constant factor, imposes a space penalty of 3 pointers per
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pair in the map, etc.</p>
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<p>std::map is most useful when your keys or values are very large, if you need
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to iterate over the collection in sorted order, or if you need stable iterators
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into the map (i.e. they don't get invalidated if an insertion or deletion of
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another element takes place).</p>
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</div>
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<!-- _______________________________________________________________________ -->
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<div class="doc_subsubsection">
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<a name="dss_othermap">Other Map-Like Container Options</a>
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</div>
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<div class="doc_text">
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<p>
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The STL provides several other options, such as std::multimap and the various
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"hash_map" like containers (whether from C++ TR1 or from the SGI library).</p>
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<p>std::multimap is useful if you want to map a key to multiple values, but has
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all the drawbacks of std::map. A sorted vector or some other approach is almost
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always better.</p>
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<p>The various hash_map implementations (exposed portably by
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"llvm/ADT/hash_map") are simple chained hash tables. This algorithm is as
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malloc intensive as std::map (performing an allocation for each element
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inserted, thus having really high constant factors) but (usually) provides O(1)
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insertion/deletion of elements. This can be useful if your elements are large
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(thus making the constant-factor cost relatively low) or if comparisons are
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expensive. Element iteration does not visit elements in a useful order.</p>
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</div>
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Reference in New Issue