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Is there any advantage of using map over unordered_map in case of trivial keys?
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Now that std has a real hash map in unordered_map, why (or when) would I still want to use the good old map over unordered_map on systems where it actually exists? Are there any obvious situations that I cannot immediately see?
As already mentioned, map allows to iterate over the elements in a sorted way, but unordered_map does not. This is very important in many situations, for example displaying a collection (e.g. address book). This also manifests in other indirect ways like: (1) Start iterating from the iterator returned by find(), or (2) existence of member functions like lower_bound().
Also, I think there is some difference in the worst case search complexity.
For map, it is O( lg N )
For unordered_map, it is O( N ) [This may happen when the hash function is not good leading to too many hash collisions.]
The same is applicable for worst case deletion complexity.
In addition to the answers above you should also note that just because unordered_map is constant speed (O(1)) doesn't mean that it's faster than map (of order log(N)). The constant may be bigger than log(N) especially since N is limited by 232 (or 264).
So in addition to the other answers (map maintains order and hash functions may be difficult) it may be that map is more performant.
For example in a program I ran for a blog post I saw that for VS10 std::unordered_map was slower than std::map (although boost::unordered_map was faster than both).
Note 3rd through 5th bars.
This is due to Google's Chandler Carruth in his CppCon 2014 lecture
std::map is (considered by many to be) not useful for performance-oriented work: If you want O(1)-amortized access, use a proper associative array (or for lack of one, std::unorderded_map); if you want sorted sequential access, use something based on a vector.
Also, std::map is a balanced tree; and you have to traverse it, or re-balance it, incredibly often. These are cache-killer and cache-apocalypse operations respectively... so just say NO to std::map.
You might be interested in this SO question on efficient hash map implementations.
(PS - std::unordered_map is cache-unfriendly because it uses linked lists as buckets.)
I think it's obvious that you'd use the std::map you need to iterate across items in the map in sorted order.
You might also use it when you'd prefer to write a comparison operator (which is intuitive) instead of a hash function (which is generally very unintuitive).
Say you have very large keys, perhaps large strings. To create a hash value for a large string you need to go through the whole string from beginning to end. It will take at least linear time to the length of the key. However, when you only search a binary tree using the > operator of the key each string comparison can return when the first mismatch is found. This is typically very early for large strings.
This reasoning can be applied to the find function of std::unordered_map and std::map. If the nature of the key is such that it takes longer to produce a hash (in the case of std::unordered_map) than it takes to find the location of an element using binary search (in the case of std::map), it should be faster to lookup a key in the std::map. It's quite easy to think of scenarios where this would be the case, but they would be quite rare in practice i believe.
Related
I want to know which data-structures are more efficient for iterating through their elements between std::set, std::map and std::unordered_set, std::unordered_map.
I searched through SO and I found this question. The answers either propose to copy the elements in a std::vector or to use Boost.Container, which IMHO don't answer my question.
My purpose is to keep in a container a big number of unique elements, that most of the time I want to iterate through them. Insertions and extractions are more rare. I want to avoid std::vector in combination with std::unique.
Lets consider set vs unordered_set.
The main difference here is the 'nature' of the iteration, that is the traversal of the set will give you the elements in order while traversing a range in an unordered set will give you a bunch of values in no particular order.
Suppose you want to traverse a range [it1, it2]. If we exclude the lookup time that's needed to find elements it1 and it2 there can be no direct mapping from one case to another since the elements in between are not guarrandeed to be the same even if you've used the same elements to construct the container.
There are cases however where something like this has meaning when e.g. you want to traverse a fixed number of elements (regardless of what they are) or when you need to traverse the whole container. In such cases you need to consider implementation mechanics :
Sets are usually implemented like Red–black trees (a form of binary search trees). Like all binary search trees allow efficient in-order traversal (LRR: left root right) of their elements. That is to traverse you pay the cost of pointer chasing (just like traversing a list).
Unordered sets on the other hand are hash tables and to my knowledge the STL implementation uses hashing with chaining. That means (in a very very high level) that what's used for the structure is a (contiguous) buffer where each element is the head of a chain (list) that contains the elements. The way the elements are layed out across those chains (buckets) and across the buffer will affect the traversal time, however you'll be chasing pointers once again jumping through differents lists as well this time. I don't think it'll vary significantly from the tree case but won't be any better for sure.
In any case micro tuning and benchmarking will give you the answer for your particular application.
The difference does not lie between the ordering or lack of one but in the backing container. If it's a contiguous memory it should be fast to iterate over, due to simple implementation of iterator and cache friendliness.
Unordered containers are usually stored as a vector of vectors (or a similar thing), while ordered containers are implemented using trees, but it is left for implementation after all. This would suggest that iterating over unordered version should be waster. However this is left for implementation after all, and I saw implementations (which bent rules a little to be fair) with different behaviour.
Generally speaking, container performance is quite a complex topic and usually has to be tested in actual application to get reliable answer. There is plenty on implemention-defined stuff that might affect the performance. I'd go with hash_set if I had to go in blind. Copying into a vector might also turn out a good option.
EDIT: As #TonyD said in it's comment, there is a rule, that disallows invalidating iterators during addition of element when the max_load_factor() is not exceeded, this practically rules out backing containers which are contiguous in memory.
Thus, copying everything into a vector seems like even more reasonable option. If you need to remove duplicates, a feasible option might be to use http://en.cppreference.com/w/cpp/algorithm/sort and have dupes easily ignored. I have heard that using vector and sort to have a sorted array (or vector) is quite often a used option in case of need for a container that needs to be sorter and is being iterated over more often than modified.
iterate from fastest to slowest should be : set > map > unordered_set > unordered_map;
set is a little lighter than map, and they are ordered with binary tree rule, so should be faster than unordered_ containers.
This is very strange for me, i expected it to be a hash table.
I saw 3 reasons in the following answer (which maybe correct but i don't think that they are the real reason).
Hash tables v self-balancing search trees
Although hash might be not a trivial operation. I think that for most of the types it is pretty simple.
when you use map you expect something that will give you amortized O(1) insert, delete, find , not log(n).
i agree that trees have better worst case performance.
I think that there is a bigger reason for that, but i can't figure it out.
In c# for example Dictionary is a hash table.
It's largely a historical accident. The standard containers (along with iterators and algorithms) were one of the very last additions before the feature set of the standard was frozen. As it happened, they didn't have what they considered an adequate definition of a hash-based map at the time, and there wasn't time to add it before features were frozen, so the original specification included only a tree-based map.
C++ 11 added std::unordered_map (as well as std::unordered_set and multi versions of both), which is based on hashing though.
The reason is that map is explicitly called out as an ordered container. It keeps the elements sorted and allows you to iterate in sorted order in linear time. A hashtable couldn't fulfill those requirements.
In C++11 they added std::unordered_map which is a hashtable implementation.
A hash table requires an additional hash function. The current implementation of map which uses a tree can work without an extra hash function by using operator<. Additionally the map allows sorted access to elements, which may be beneficial for some applications. With C++ we now have the hash versions available in form of unordered_set.
Simple answer: because a hash table cannot satisfy the complexity requirements of iteration over a std::map.
Why does std::map hold these requirements? Unanswerable question. Historical factors contribute but, overall, that's just the way it is.
Hashes are available as std::unordered_map.
It doesn't really matter what the two are called, or what they're called in some other language.
When should I choose one over the other?
Are there any pointers that you would recommend for using the right STL containers?
hash_set is an extension that is not part of the C++ standard. Lookups should be O(1) rather than O(log n) for set, so it will be faster in most circumstances.
Another difference will be seen when you iterate through the containers. set will deliver the contents in sorted order, while hash_set will be essentially random (Thanks Lou Franco).
Edit: The C++11 update to the C++ standard introduced unordered_set which should be preferred instead of hash_set. The performance will be similar and is guaranteed by the standard. The "unordered" in the name stresses that iterating it will produce results in no particular order.
stl::set is implemented as a binary search tree.
hashset is implemented as a hash table.
The main issue here is that many people use stl::set thinking it is a hash table with look-up of O(1), which it isn't, and doesn't have. It really has O(log(n)) for look-ups. Other than that, read about binary trees vs hash tables to get a better idea of the data structures.
Another thing to keep in mind is that with hash_set you have to provide the hash function, whereas a set only requires a comparison function ('<') which is easier to define (and predefined for native types).
I don't think anyone has answered the other part of the question yet.
The reason to use hash_set or unordered_set is the usually O(1) lookup time. I say usually because every so often, depending on implementation, a hash may have to be copied to a larger hash array, or a hash bucket may end up containing thousands of entries.
The reason to use a set is if you often need the largest or smallest member of a set. A hash has no order so there is no quick way to find the smallest item. A tree has order, so largest or smallest is very quick. O(log n) for a simple tree, O(1) if it holds pointers to the ends.
A hash_set would be implemented by a hash table, which has mostly O(1) operations, whereas a set is implemented by a tree of some sort (AVL, red black, etc.) which have O(log n) operations, but are in sorted order.
Edit: I had written that trees are O(n). That's completely wrong.
I can't seem to find any information on this, so I turn to stackoverflow. How efficient are the iterators of std::tr1::unordered_map in C++? Especially compared to, say, list iterators. Would it make sense to make a wrapper class that also holds all the keys in a list to allow for efficient iteration (my code does use a lot of iteration over the keys in an unordered_map). For those who will recommend boost, I can't use it (for whatever reasons).
I haven't checked TR1, but N3035 (C++0x draft) says this:
All the categories of iterators
require only those functions that are
realizable for a given category in
constant time (amortized). Therefore,
requirement tables for the iterators
do not have a complexity column.
The standard isn't going to give an efficiency guarantee other than in terms of complexity, so you have no guaranteed comparison of list and unordered_map other than that they're both amortized constant time (i.e., linear time for a complete iteration over the container).
In practice, I'd expect an unordered_map iterator to be at least in the vicinity of list, unless your hashmap is very sparsely populated. There could be an O(number of buckets) term in the complexity of the complete iteration. But I've never looked at even one implementation specifically of unordered_map for C++, so I don't know what adornments to expect on a simplistic "array of linked lists" hashtable implementation. If you have a "typical" platform test it, if you're trying to write code that will definitely be the fastest possible on all C++ implementations then tough luck, you can't ;-)
The unordered_map iterator basically just has to walk over the internal tree structure of the hashtable. This just means doing some pointer following, and so should be pretty efficient. Of course, if you are walking an unordered_map a lot, you may be using the wrong data structure in the first place. In any case, the answer to this, as it is for all performance questions, is for you to time your specific code to see if it is fast enough.
Unfortunately, you can't say for sure if something is efficient enough unless you've tried it and measured the results. I can tell you that the standard library, TR1, and Boost classes have had tons of eyes on them. They're probably as fast as they're going to get for most common use cases. Walking an container is certainly a common use case.
With all that said, you need to ask yourself a few questions:
What's the clearest way to say what I want? It may be that writing a wrapper class adds unneeded complexity to your code. Make it correct first, then make it fast.
Can I afford the extra memory and time to maintain a list in parallel with the unordered_map?
Is unordered_map really the right data structure? If your most common use case is traversal from beginning to end, you might be better off with vector because the memory is guaranteed to be contiguous.
Answered by the benchmarks here https://stackoverflow.com/a/25027750/1085128
unordered_map is partway between vector and map for iteration. It is significantly faster than map.
I have data that is a set of ordered ints
[0] = 12345
[1] = 12346
[2] = 12454
etc.
I need to check whether a value is in the collection in C++, what container will have the lowest complexity upon retrieval? In this case, the data does not grow after initiailization. In C# I would use a dictionary, in c++, I could either use a hash_map or set. If the data were unordered, I would use boost's unordered collections. However, do I have better options since the data is ordered? Thanks
EDIT: The size of the collection is a couple of hundred items
Just to detail a bit over what have already been said.
Sorted Containers
The immutability is extremely important here: std::map and std::set are usually implemented in terms of binary trees (red-black trees for my few versions of the STL) because of the requirements on insertion, retrieval and deletion operation (and notably because of the invalidation of iterators requirements).
However, because of immutability, as you suspected there are other candidates, not the least of them being array-like containers. They have here a few advantages:
minimal overhead (in term of memory)
contiguity of memory, and thus cache locality
Several "Random Access Containers" are available here:
Boost.Array
std::vector
std::deque
So the only thing you actually need to do can be broken done in 2 steps:
push all your values in the container of your choice, then (after all have been inserted) use std::sort on it.
search for the value using std::binary_search, which has O(log(n)) complexity
Because of cache locality, the search will in fact be faster even though the asymptotic behavior is similar.
If you don't want to reinvent the wheel, you can also check Alexandrescu's [AssocVector][1]. Alexandrescu basically ported the std::set and std::map interfaces over a std::vector:
because it's faster for small datasets
because it can be faster for frozen datasets
Unsorted Containers
Actually, if you really don't care about order and your collection is kind of big, then a unordered_set will be faster, especially because integers are so trivial to hash size_t hash_method(int i) { return i; }.
This could work very well... unless you're faced with a collection that somehow causes a lot of collisions, because then unsorted containers will search over the "collisions" list of a given hash in linear time.
Conclusion
Just try the sorted std::vector approach and the boost::unordered_set approach with a "real" dataset (and all optimizations on) and pick whichever gives you the best result.
Unfortunately we can't really help more there, because it heavily depends on the size of the dataset and the repartition of its elements
If the data is in an ordered random-access container (e.g. std::vector, std::deque, or a plain array), then std::binary_search will find whether a value exists in logarithmic time. If you need to find where it is, use std::lower_bound (also logarithmic).
Use a sorted std::vector, and use a std::binary_search to search it.
Your other options would be a hash_map (not in the C++ standard yet but there are other options, e.g. SGI's hash_map and boost::unordered_map), or an std::map.
If you're never adding to your collection, a sorted vector with binary_search will most likely have better performance than a map.
I'd suggest using a std::vector<int> to store them and a std::binary_search or std::lower_bound to retrieve them.
Both std::unordered_set and std::set add significant memory overhead - and even though the unordered_set provides O(1) lookup, the O(logn) binary search will probably outperform it given that the data is stored contiguously (no pointer following, less chance of a page fault etc.) and you don't need to calculate a hash function.
If you already have an ordered array or std::vector<int> or similar container of the data, you can just use std::binary_search to probe each value. No setup time, but each probe will take O(log n) time, where n is the number of ordered ints you've got.
Alternately, you can use some sort of hash, such as boost::unordered_set<int>. This will require some time to set up, and probably more space, but each probe will take O(1) time on the average. (For small n, this O(1) could be more than the previous O(log n). Of course, for small n, the time is negligible anyway.)
There is no point in looking at anything like std::set or std::map, since those offer no advantage over binary search, given that the list of numbers to match will not change after being initialized.
So, the questions are the approximate value of n, and how many times you intend to probe the table. If you aren't going to check many values to see if they're in the ints provided, then setup time is very important, and std::binary_search on the sorted container is the way to go. If you're going to check a lot of values, it may be worth setting up a hash table. If n is large, the hash table will be faster for probing than binary search, and if there's a lot of probes this is the main cost.
So, if the number of ints to compare is reasonably small, or the number of probe values is small, go with the binary search. If the number of ints is large, and the number of probes is large, use the hash table.