rationale.qbk 5.3 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111
  1. [/ Copyright 2006-2008 Daniel James.
  2. / Distributed under the Boost Software License, Version 1.0. (See accompanying
  3. / file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) ]
  4. [def __wang__
  5. [@http://web.archive.org/web/20121102023700/http://www.concentric.net/~Ttwang/tech/inthash.htm
  6. Thomas Wang's article on integer hash functions]]
  7. [section:rationale Implementation Rationale]
  8. The intent of this library is to implement the unordered
  9. containers in the draft standard, so the interface was fixed. But there are
  10. still some implementation decisions to make. The priorities are
  11. conformance to the standard and portability.
  12. The [@http://en.wikipedia.org/wiki/Hash_table Wikipedia article on hash tables]
  13. has a good summary of the implementation issues for hash tables in general.
  14. [h2 Data Structure]
  15. By specifying an interface for accessing the buckets of the container the
  16. standard pretty much requires that the hash table uses chained addressing.
  17. It would be conceivable to write a hash table that uses another method. For
  18. example, it could use open addressing, and use the lookup chain to act as a
  19. bucket but there are some serious problems with this:
  20. * The draft standard requires that pointers to elements aren't invalidated, so
  21. the elements can't be stored in one array, but will need a layer of
  22. indirection instead - losing the efficiency and most of the memory gain,
  23. the main advantages of open addressing.
  24. * Local iterators would be very inefficient and may not be able to
  25. meet the complexity requirements.
  26. * There are also the restrictions on when iterators can be invalidated. Since
  27. open addressing degrades badly when there are a high number of collisions the
  28. restrictions could prevent a rehash when it's really needed. The maximum load
  29. factor could be set to a fairly low value to work around this - but the
  30. standard requires that it is initially set to 1.0.
  31. * And since the standard is written with a eye towards chained
  32. addressing, users will be surprised if the performance doesn't reflect that.
  33. So chained addressing is used.
  34. [/ (Removing for now as this is out of date)
  35. For containers with unique keys I store the buckets in a single-linked list.
  36. There are other possible data structures (such as a double-linked list)
  37. that allow for some operations to be faster (such as erasing and iteration)
  38. but the possible gain seems small compared to the extra memory needed.
  39. The most commonly used operations (insertion and lookup) would not be improved
  40. at all.
  41. But for containers with equivalent keys a single-linked list can degrade badly
  42. when a large number of elements with equivalent keys are inserted. I think it's
  43. reasonable to assume that users who choose to use `unordered_multiset` or
  44. `unordered_multimap` do so because they are likely to insert elements with
  45. equivalent keys. So I have used an alternative data structure that doesn't
  46. degrade, at the expense of an extra pointer per node.
  47. This works by adding storing a circular linked list for each group of equivalent
  48. nodes in reverse order. This allows quick navigation to the end of a group (since
  49. the first element points to the last) and can be quickly updated when elements
  50. are inserted or erased. The main disadvantage of this approach is some hairy code
  51. for erasing elements.
  52. ]
  53. [/ (Starting to write up new structure, might not be ready in time)
  54. The node used to be stored in a linked list for each bucket but that
  55. didn't meet the complexity requirements for C++11, so now the nodes
  56. are stored in one long single linked list. But there needs a way to get
  57. the bucket from the node, to do that a copy of the key's hash value is
  58. stored in the node. Another possibility would be to store a pointer to
  59. the bucket, or the bucket's index, but storing the hash value allows
  60. some operations to be faster.
  61. ]
  62. [h2 Number of Buckets]
  63. There are two popular methods for choosing the number of buckets in a hash
  64. table. One is to have a prime number of buckets, another is to use a power
  65. of 2.
  66. Using a prime number of buckets, and choosing a bucket by using the modulus
  67. of the hash function's result will usually give a good result. The downside
  68. is that the required modulus operation is fairly expensive. This is what the
  69. containers do in most cases.
  70. Using a power of 2 allows for much quicker selection of the bucket
  71. to use, but at the expense of losing the upper bits of the hash value.
  72. For some specially designed hash functions it is possible to do this and
  73. still get a good result but as the containers can take arbitrary hash
  74. functions this can't be relied on.
  75. To avoid this a transformation could be applied to the hash function, for an
  76. example see __wang__. Unfortunately, a transformation like Wang's requires
  77. knowledge of the number of bits in the hash value, so it isn't portable enough
  78. to use as a default. It can applicable in certain cases so the containers
  79. have a policy based implementation that can use this alternative technique.
  80. Currently this is only done on 64 bit architectures, where prime number
  81. modulus can be expensive. Although this varies depending on the architecture,
  82. so I probably should revisit it.
  83. I'm also thinking of introducing a mechanism whereby a hash function can
  84. indicate that it's safe to be used directly with power of 2 buckets, in
  85. which case a faster plain power of 2 implementation can be used.
  86. [endsect]