Difference between revisions of "Intermediate C++ Game Programming Tutorial 24"
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*:- Insertion is done by navigating the tree along a route Left for smaller, Right for larger such that the order property always holds | *:- Insertion is done by navigating the tree along a route Left for smaller, Right for larger such that the order property always holds | ||
** The big advantage of the BT properties is that retrieval is very fast | ** The big advantage of the BT properties is that retrieval is very fast | ||
| + | ** The beauty of <code>std::map</code> is that we don't have to implement any of this; it's all there in the STL [https://youtu.be/JlPsCoCO99o?t=7m00s 7:00] | ||
| + | ** The STL implementation is further optimized, e.g. it uses a red-black tree for BT rebalancing | ||
</div> | </div> | ||
| − | * | + | * A look at the <code>std::map</code> cppreference.com documentation [https://youtu.be/JlPsCoCO99o?t=7m35s 7:35] |
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</div> | </div> | ||
Revision as of 03:07, 20 January 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.
Contents
Topics Covered
Part 1
-
std::mapcontainer interface - Binary tree data structure
-
std::mapkey requirements (comparison) -
std::mapgotchas (std::remove_ifandconstkeys) -
std::set -
std::multimapandstd::multiset
Part 2
- Hash table performance vs. binary tree performance
- Hash table data structure
-
std::unordered_mapkey requirements - Hash combining
-
std::unordered_mapbucket interface and hashing policy - When to choose
std::mapoverstd::unordered_map
Video Timestamp Index
- The
std::map<KeyType,ValueType>class 0:46
- Maps consist of keys to lookup (associated with) values
-
map.insert( {key,value} )to insert (key,value) pairs -
map[key]returns a reference to the ValueType for a KeyType
- The Binary tree data structure 2:46
-
std::mapperforms lookup in O(log(n)), it uses a Binary tree data structure - Key properties of a Binary Tree (BT):
- - Nodes can have at most 2 children (hence: binary)
- - Each left child is smaller and each right child is larger than its parent
- - Insertion is done by navigating the tree along a route Left for smaller, Right for larger such that the order property always holds
- The big advantage of the BT properties is that retrieval is very fast
- The beauty of
std::mapis that we don't have to implement any of this; it's all there in the STL 7:00 - The STL implementation is further optimized, e.g. it uses a red-black tree for BT rebalancing
-
- A look at the
std::mapcppreference.com documentation 7:35
- [WORK-IN-PROGRESS]
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.
