Difference between revisions of "Intermediate C++ Game Programming Tutorial 24"

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== Video Timestamp Index ==
 
== Video Timestamp Index ==
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[https://youtu.be/JlPsCoCO99o Tutorial 24.1]: The ordered associative containers
+
=== [https://youtu.be/JlPsCoCO99o Tutorial 24.1]: The ordered associative containers ===
 
<div class="mw-collapsible mw-collapsed"><br />
 
<div class="mw-collapsible mw-collapsed"><br />
 
* The <code>std::map<KeyType,ValueType></code> class [https://youtu.be/JlPsCoCO99o?t=0m46s 0:46]
 
* The <code>std::map<KeyType,ValueType></code> class [https://youtu.be/JlPsCoCO99o?t=0m46s 0:46]
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</div>
 
</div>
 
</div>
 
</div>
−
[https://youtu.be/LsjFAx-dG5I Tutorial 24.2]: The unordered associative containers
+
=== [https://youtu.be/LsjFAx-dG5I Tutorial 24.2]: The unordered associative containers ===
−
* Main difference between ordered/unordered is performance [https://youtu.be/LsjFAx-dG5I?t=0m14s 0:14]
+
<div class="mw-collapsible mw-collapsed"><br />
−
** Implication: if you iterative over an unordered container, keys will appear in (seemingly) random order
+
* Main difference between ordered/unordered: performance [https://youtu.be/LsjFAx-dG5I?t=0m14s 0:14]
−
** Releasing the ordering requirement makes it possible to use a hash table with performance advantages: O(1) contant time insertion and lookup
+
<div class="mw-collapsible-content">
 +
:* Implication: if you iterative over an unordered container, keys will appear in (seemingly) random order
 +
:* Releasing the ordering requirement makes it possible to use a hash table with performance advantages: O(1) contant time insertion and lookup
 +
</div>
 
* Using an unordered map [https://youtu.be/LsjFAx-dG5I?t=1m38s 1:38]
 
* Using an unordered map [https://youtu.be/LsjFAx-dG5I?t=1m38s 1:38]
−
** The interface is pretty much the same as its ordered counterpart
+
<div class="mw-collapsible-content">
−
** Include <code><unordered_map></code>, declare using <code>std::unordered_map<KeyType,ValueType></code>
+
:* The interface is pretty much the same as its ordered counterpart
−
** You can initialize your map object with an initializer list if you wanted to using <code>({ {..,..},{..,..},... })</code> inside your declaration
+
:* Include <code><unordered_map></code>, declare using <code>std::unordered_map<KeyType,ValueType></code>
 +
:* You can initialize your map object with an initializer list if you wanted to using <code>({ {..,..},{..,..},... })</code> inside your declaration
 +
</div>
 
* The Hash Table data structure [https://youtu.be/LsjFAx-dG5I?t=3m20s 3:20]
 
* The Hash Table data structure [https://youtu.be/LsjFAx-dG5I?t=3m20s 3:20]
−
** A hash table allows you to get the quick access to values, comparable to array access using the index, but with efficient memory usage
+
<div class="mw-collapsible-content">
−
** Buckets are used to group keys; this is done by mapping keys to buckets using a hash function (a.k.a. hashing)
+
:* A hash table allows you to get the quick access to values, comparable to array access using the index, but with efficient memory usage
−
** Multiple keys can map to the same bucket in a hash table ("collision"). We use a linked list to store multiple {key,value} pairs in a bucket
+
:* Buckets are used to group keys; this is done by mapping keys to buckets using a hash function (a.k.a. hashing)
−
** Two ways to minimize hash collisions: i) more buckets, ii) smart hash function that distributes key values uniformly across your bucket space
+
:* Multiple keys can map to the same bucket in a hash table ("collision"). We use a linked list to store multiple {key,value} pairs in a bucket
−
** Hashing a a two step process [https://youtu.be/LsjFAx-dG5I?t=9m26s 9:26]:  
+
:* Two ways to minimize hash collisions: i) more buckets, ii) smart hash function that distributes key values uniformly across your bucket space
−
*:- A hash function takes in the KeyType input (typically a string or int) and outputs a size_t
+
:* Hashing a a two step process [https://youtu.be/LsjFAx-dG5I?t=9m26s 9:26]:  
−
*:- the size_t output is reduced/ditributed to the size of the hash table (number of buckets)
+
::- A hash function takes in the KeyType input (typically a string or int) and outputs a size_t
−
** The Standard Library provides general hasing functions for all the standard types
+
::- the size_t output is reduced/ditributed to the size of the hash table (number of buckets)
−
 
+
:* The Standard Library provides general hashing functions for all the standard types
−
* [WORK-IN-PROGRESS]
+
:* For general use of unordered maps, we don't have to worry about the technical details of how the hash table works, the STL provides this
 +
</div>
 +
* Requirements for the KeyType of an <code>unordered_map</code> / a hash table [https://youtu.be/LsjFAx-dG5I?t=11m56s 11:56]
 +
<div class="mw-collapsible-content">
 +
:* There needs to be a working hash function defined for the KeyType
 +
:* There need to be comparison and equality functor definitions for the KeyType
 +
</div>
 +
* Example: map from <code>Vec2</code> class (2D coordinates) to a string [https://youtu.be/LsjFAx-dG5I?t=12m46s 12:46]
 +
<div class="mw-collapsible-content">
 +
:* In order to make this work, you need to define a hash function and the comparators for <code>Vei2</code>
 +
:* You can implement a comparison/equality functor as a <code>struct</code> that defines a <code>operator()</code> member function, templated on <code>T</code>
 +
::<syntaxhighlight lang="cpp" line>
 +
struct EqVec2
 +
{
 +
    template <typename T>
 +
    bool operator()( const T& lhs,const T& rhs ) const
 +
    {
 +
        return (lhs.x == rhs.x) && (lhs.y == rhs.y);
 +
    }
 +
};
 +
</syntaxhighlight>
 +
:* Defining a custom hashing function is an art, it requires knowledge of cryptography, abstract algebra, discrete math, etc.
 +
:* Luckily, we don't need this; you can revert to the standard hashing functions for the basic types that make up any custom type
 +
</div>
 +
* Hash combining [https://youtu.be/LsjFAx-dG5I?t=14m25s 14:25]
 +
<div class="mw-collapsible-content">
 +
:* Combining hashes from basic types to create a hash over your custom object
 +
:* A simple google search will give you good examples of how to combine hash values in C++
 +
:* You can implement a hashing functor as a <code>struct</code> that defines a member function, templated on <code>T</code>, the basic type of the <code>Vec2</code> coordinates:
 +
::<syntaxhighlight lang="cpp" line>
 +
struct HashVec2
 +
{
 +
    template <typename T>
 +
    size_t operator()( const _Vec2<T>& vec ) const
 +
    {
 +
        std::hash<T> hasher;
 +
        auto hashx = hasher ( vec.x );
 +
        auto hashy = hasher ( vec.y );
 +
        hashx ^= hashy + 0x9e3779b9 + (hashx << 6) + (hashx >> 2);
 +
        return hashx;
 +
    }
 +
};
 +
</syntaxhighlight>
 +
:* You pass this functors when defining the map: <code>std::unordered_map<Vei2,std::string,HashVec2> map;</code> [https://youtu.be/LsjFAx-dG5I?t=17m15s 17:15].
 +
:* Note that the comparison functor is not needed: we can revert back to the equality operator already defined in the <code>Vec2</code> class definition
 +
</div>
 +
* Template Specialization [https://youtu.be/LsjFAx-dG5I?t=18m43s 18:43]
 +
<div class="mw-collapsible-content">
 +
:* Unordered map uses <code>std::hash</code> by default. You can inject Template Specialization for <code>std::hash</code> into the <code>std</code> Namespace for your own custom types only
 +
::<syntaxhighlight lang="cpp" line>
 +
namespace std
 +
{
 +
    template <> struct hash<Vei2>
 +
    {
 +
        size_t operator()( cont Vei2& vec ) const
 +
        {...}
 +
    };
 +
}
 +
</syntaxhighlight>
 +
:* Now you don't need to pass <code>HashVec2</code> in the map definition
 +
</div>
 +
* The <code>std::unordered_map<></code> Bucket interface [https://youtu.be/LsjFAx-dG5I?t=20m00s 20:00]
 +
<div class="mw-collapsible-content">
 +
:* Allows you to get information about the buckets in the hash table and access nodes
 +
:* The bucket iterator takes an index of the bucket and allows you to iterate over all the elements in that specific bucket
 +
</div>
 +
* The <code>std::unordered_map<></code> Hash policy interface [https://youtu.be/LsjFAx-dG5I?t=21m47s 21:47]
 +
<div class="mw-collapsible-content">
 +
:* Allows you to tune your hash table (and thus the growth behavior & performance of the map)
 +
:* Load Factor = average number of elements per bucket. For performance, you typically want to keep this below 1
 +
:* You can set the maximum load factor above which the table gets rehashed
 +
:* When the load factor becomes too high, it will automaticall rehash the table and increase the number of buckets
 +
:* You can manually rehash to a number of buckets you define
 +
:* You can reserve space for max number of elements, is then derives (and manages) the required number of buckets
 +
</div>
 +
* When to choose <code>std::map</code> over <code>std::unordered_map</code>? [https://youtu.be/LsjFAx-dG5I?t=24m15s 25:15]
 +
<div class="mw-collapsible-content">
 +
:* For simplicity and when performance is not a critical issue, no need to define a hash function;
 +
:* If you want to iterate in order;
 +
:* When you want to be able to find keys that are close to a certain key (with <code>lower_bound</code> and <code>upper_bount</code>
 +
</div>
 +
* Homework assignment [https://youtu.be/LsjFAx-dG5I?t=26m04s 26:04]
 +
</div>
  
 
== Homework Assignment ==
 
== Homework Assignment ==

Latest revision as of 23:47, 2 February 2020

Associative containers are super useful, both as a convenient fast way to create dictionary or mapping for real-world problems like managing game resources, and as a data structure to help solve more abstract algorithmic computer science problems. And hash tables are fast as balls.

Topics Covered

Part 1: ordered associative containers

  • std::map container interface
  • Binary tree data structure
  • std::map key requirements (comparison)
  • std::map gotchas (std::remove_if and const keys)
  • std::set
  • std::multimap and std::multiset

Part 2: unordered associative containers

  • Hash table performance vs. binary tree performance
  • Hash table data structure
  • std::unordered_map key requirements
  • Hash combining
  • std::unordered_map bucket interface and hashing policy
  • When to choose std::map over std::unordered_map

Video Timestamp Index

Tutorial 24.1: The ordered associative containers

[Expand]
  • The std::map<KeyType,ValueType> class 0:46
  • A Binary Tree data structure is used to manage the order of map elements 2:46
  • A look at the std::map cppreference.com documentation: insert, lookup & find 7:35
  • Requirements on KeyType 14:30
  • std::map cppreference.com documentation continued: erase 15:28
  • Two important things to know when working with associative containers 16:04
  • The std::set<KeyType> class 20:00
  • The std::multimap and std::multiset classes 21:28
  • Practical example of a multimap use case 22:30
  • Lookup in multimaps 25:21

Tutorial 24.2: The unordered associative containers

[Expand]
  • Main difference between ordered/unordered: performance 0:14
  • Using an unordered map 1:38
  • The Hash Table data structure 3:20
  • Requirements for the KeyType of an unordered_map / a hash table 11:56
  • Example: map from Vec2 class (2D coordinates) to a string 12:46
  • Template Specialization 18:43
  • The std::unordered_map<> Bucket interface 20:00
  • The std::unordered_map<> Hash policy interface 21:47
  • When to choose std::map over std::unordered_map? 25:15
  • Homework assignment 26:04

Homework Assignment

The homework for this video is to enable use of a custom datatype in unordered_map hashing over multiple (4) members of that datatype. The solution video is here.

Supplementary Link

See also

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