Suppose you have a std::vector<std::map<std::string, T> >. You know that all the maps have the same keys. They might have been initialized with
typedef std::map<std::string, int> MapType;
std::vector<MapType> v;
const int n = 1000000;
v.reserve(n);
for (int i=0;i<n;i++)
{
std::map<std::string, int> m;
m["abc"] = rand();
m["efg"] = rand();
m["hij"] = rand();
v.push_back(m);
}
Given a key (e.g. "efg"), I would like to extract all values of the maps for the given key (which definitely exists in every map).
Is it possible to speed up the following code?
std::vector<int> efgValues;
efgValues.reserve(v.size());
BOOST_FOREACH(MapType const& m, v)
{
efgValues.push_back(m.find("efg")->second);
}
Note that the values are not necessarily int. As profiling confirms that most time is spent in the find function, I was thinking about whether there is a (GCC and MSVC compliant C++03) way to avoid locating the element in the map based on the key for every single map again, because the structure of all the maps is equal.
If no, would it be possible with boost::unordered_map (which is 15% slower on my machine with the code above)? Would it be possible to cache the hash value of the string?
P.S.: I know that having a std::map<std::string, std::vector<T> > would solve my problem. However, I cannot change the data structure (which is actually more complex than what I showed here).
You can cache and playback the sequence of comparison results using a stateful comparator. But that's just nasty; the solution is to adjust the data structure. There's no "cannot." Actually, adding a stateful comparator is changing the data structure. That requirement rules out almost anything.
Another possibility is to create a linked list across the objects of type T so you can get from each map to the next without another lookup. If you might be starting at any of the maps (please, just refactor the structure) then a circular or doubly-linked list will do the trick.
As profiling confirms that most time is spent in the find function
Keeping the tree data structures and optimizing the comparison can only speed up the comparison. Unless the time is spent in operator< (std::string const&, std::string const&), you need to change the way it's linked together.
UPDATED:
I am working on a program whose performance is very critical. I have a vector of structs that are NOT sorted. I need to perform many search operations in this vector. So I decided to cache the vector data into a map like this:
std::map<long, int> myMap;
for (int i = 0; i < myVector.size(); ++i)
{
const Type& theType = myVector[i];
myMap[theType.key] = i;
}
When I search the map, the results of the rest of the program are much faster. However, the remaining bottleneck is the creation of the map itself (it is taking about 0.8 milliseconds on average to insert about 1,500 elements in it). I need to figure out a way to trim this time down. I am simply inserting a long as the key and an int as the value. I don't understand why it is taking this long.
Another idea I had was to create a copy of the vector (can't touch the original one) and somehow perform a faster sort than the std::sort (it takes way too long to sort it).
Edit:
Sorry everyone. I meant to say that I am creating a std::map where the key is a long and the value is an int. The long value is the struct's key value and the int is the index of the corresponding element in the vector.
Also, I did some more debugging and realized that the vector is not sorted at all. It's completely random. So doing something like a stable_sort isn't going to work out.
ANOTHER UPDATE:
Thanks everyone for the responses. I ended up creating a vector of pairs (std::vector of std::pair(long, int)). Then I sorted the vector by the long value. I created a custom comparator that only looked at the first part of the pair. Then I used lower_bound to search for the pair. Here's how I did it all:
typedef std::pair<long,int> Key2VectorIndexPairT;
typedef std::vector<Key2VectorIndexPairT> Key2VectorIndexPairVectorT;
bool Key2VectorIndexPairComparator(const Key2VectorIndexPairT& pair1, const Key2VectorIndexPairT& pair2)
{
return pair1.first < pair2.first;
}
...
Key2VectorIndexPairVectorT sortedVector;
sortedVector.reserve(originalVector.capacity());
// Assume "original" vector contains unsorted elements.
for (int i = 0; i < originalVector.size(); ++i)
{
const TheStruct& theStruct = originalVector[i];
sortedVector.insert(Key2VectorIndexPairT(theStruct.key, i));
}
std::sort(sortedVector.begin(), sortedVector.end(), Key2VectorIndexPairComparator);
...
const long keyToSearchFor = 20;
const Key2VectorIndexPairVectorT::const_iterator cItorKey2VectorIndexPairVector = std::lower_bound(sortedVector.begin(), sortedVector.end(), Key2VectorIndexPairT(keyToSearchFor, 0 /* Provide dummy index value for search */), Key2VectorIndexPairComparator);
if (cItorKey2VectorIndexPairVector->first == keyToSearchFor)
{
const int vectorIndex = cItorKey2VectorIndexPairVector->second;
const TheStruct& theStruct = originalVector[vectorIndex];
// Now do whatever you want...
}
else
{
// Could not find element...
}
This yielded a modest performance gain for me. Before the total time for my calculations were 3.75 milliseconds and now it is down to 2.5 milliseconds.
Both std::map and std::set are built on a binary tree and so adding items does dynamic memory allocation. If your map is largely static (i.e. initialized once at the start and then rarely or never has new items added or removed) you'd probably be better to use a sorted vector and a std::lower_bound to look up items using a binary search.
Maps take a lot of time for two reasons
You need to do a lot of memory allocation for your data storage
You need to perform O(n lg n) comparisons for the sort.
If you are just creating this as one batch, then throwing the whole map out, using a custom pool allocator may be a good idea here - eg, boost's pool_alloc. Custom allocators can also apply optimizations such as not actually deallocating any memory until the map's completely destroyed, etc.
Since your keys are integers, you may want to consider writing your own container based on a radix tree (on the bits of the key) as well. This may give you significantly improved performance, but since there is no STL implementation, you may need to write your own.
If you don't need to sort the data, use a hash table, such as std::unordered_map; these avoid the significant overhead needed for sorting data, and also can reduce the amount of memory allocation needed.
Finally, depending on the overall design of the program, it may be helpful to simply reuse the same map instead of recreating it over and over. Just delete and add keys as needed, rather than building a new vector, then building a new map. Again, this may not be possible in the context of your program, but if it is, it would definitely help you.
I suspect it's the memory management and tree rebalancing that's costing you here.
Obviously profiling may be able to help you pinpoint the issue.
I would suggest as a general idea to just copy the long/int data you need into another vector and since you said it's almost sorted, use stable_sort on it to finish the ordering. Then use lower_bound to locate the items in the sorted vector.
std::find is a linear scan(it has to be since it works on unsorted data). If you can sort(std::sort guaranties n log(n) behavior) the data then you can use std::binary_search to get log(n) searches. But as pointed out by others it may be copy time is the problem.
If keys are solid and short, perhaps try std::hash_map instead. From MSDN's page on hash_map Class:
The main advantage of hashing over sorting is greater efficiency; a
successful hashing performs insertions, deletions, and finds in
constant average time as compared with a time proportional to the
logarithm of the number of elements in the container for sorting
techniques.
Map creation can be a performance bottleneck (in the sense that it takes a measurable amount of time) if you're creating a large map and you're copying large chunks of data into it. You're also using the obvious (but suboptimal) way of inserting elements into a std::map - if you use something like:
myMap.insert(std::make_pair(theType.key, theType));
this should improve the insertion speed, but it will result in a slight change in behaviour if you encounter duplicate keys - using insert will result in values for duplicate keys being dropped, whereas using your method, the last element with the duplicate key will be inserted into the map.
I would also look into avoiding a making a copy of the data (for example by storing a pointer to it instead) if your profiling results determine that it's the copying of the element that is expensive. But for that you'll have to profile the code, IME guesstimates tend to be wrong...
Also, as a side note, you might want to look into storing the data in a std::set using custom comparator as your contains the key already. That however will not really result in a big speed up as constructing a set in this case is likely to be as expensive as inserting it into a map.
I'm not a C++ expert, but it seems that your problem stems from copying the Type instances, instead of a reference/pointer to the Type instances.
std::map<Type> myMap; // <-- this is wrong, since std::map requires two template parameters, not one
If you add elements to the map and they're not pointers, then I believe the copy constructor is invoked and that will certainly cause delays with a large data structure. Use the pointer instead:
std::map<KeyType, ObjectType*> myMap;
Furthermore, your example is a little confusing since you "insert" a value of type int in the map when you're expecting a value of type Type. I think you should assign the reference to the item, not the index.
myMap[theType.key] = &myVector[i];
Update:
The more I look at your example, the more confused I get. If you're using the std::map, then it should take two template types:
map<T1,T2> aMap;
So what are you REALLY mapping? map<Type, int> or something else?
It seems that you're using the Type.key member field as a key to the map (it's a valid idea), but unless key is of the same type as Type, then you can't use it as the key to the map. So is key an instance of Type??
Furthermore, you're mapping the current vector index to the key in the map, which indicates that you're just want the index to the vector so you can later access that index location fast. Is that what you want to do?
Update 2.0:
After reading your answer it seems that you're using std::map<long,int> and in that case there is no copying of the structure involved. Furthermore, you don't need to make a local reference to the object in the vector. If you just need to access the key, then access it by calling myVector[i].key.
Your building a copy of the table from the broken example you give, and not just a reference.
Why Can't I store references in an STL map in C++?
Whatever you store in the map it relies on you not changing the vector.
Try a lookup map only.
typedef vector<Type> Stuff;
Stuff myVector;
typedef std::map<long, *Type> LookupMap;
LookupMap myMap;
LookupMap::iterator hint = myMap.begin();
for (Stuff::iterator it = myVector.begin(); myVector.end() != it; ++it)
{
hint = myMap.insert(hint, std::make_pair(it->key, &*it));
}
Or perhaps drop the vector and just store it in the map??
Since your vector is already partially ordered, you may want to instead create an auxiliary array referencing (indices of) the elements in your original vector. Then you can sort the auxiliary array using Timsort which has good performance for partially sorted data (such as yours).
I think you've got some other problem. Creating a vector of 1500 <long, int> pairs, and sorting it based on the longs should take considerably less than 0.8 milliseconds (at least assuming we're talking about a reasonably modern, desktop/server type processor).
To try to get an idea of what we should see here, I did a quick bit of test code:
#include <vector>
#include <algorithm>
#include <time.h>
#include <iostream>
int main() {
const int size = 1500;
const int reps = 100;
std::vector<std::pair<long, int> > init;
std::vector<std::pair<long, int> > data;
long total = 0;
// Generate "original" array
for (int i=0; i<size; i++)
init.push_back(std::make_pair(rand(), i));
clock_t start = clock();
for (int i=0; i<reps; i++) {
// copy the original array
std::vector<std::pair<long, int> > data(init.begin(), init.end());
// sort the copy
std::sort(data.begin(), data.end());
// use data that depends on sort to prevent it being optimized away
total += data[10].first;
total += data[size-10].first;
}
clock_t stop = clock();
std::cout << "Ignore: " << total << "\n";
clock_t ticks = stop - start;
double seconds = ticks / (double)CLOCKS_PER_SEC;
double ms = seconds * 1000.0;
double ms_p_iter = ms / reps;
std::cout << ms_p_iter << " ms/iteration.";
return 0;
}
Running this on my somewhat "trailing edge" (~5 year-old) machine, I'm getting times around 0.1 ms/iteration. I'd expect searching in this (using std::lower_bound or std::upper_bound) to be somewhat faster than searching in an std::map as well (since the data in the vector is allocated contiguously, we can expect better locality of reference, leading to better cache usage).
Thanks everyone for the responses. I ended up creating a vector of pairs (std::vector of std::pair(long, int)). Then I sorted the vector by the long value. I created a custom comparator that only looked at the first part of the pair. Then I used lower_bound to search for the pair. Here's how I did it all:
typedef std::pair<long,int> Key2VectorIndexPairT;
typedef std::vector<Key2VectorIndexPairT> Key2VectorIndexPairVectorT;
bool Key2VectorIndexPairComparator(const Key2VectorIndexPairT& pair1, const Key2VectorIndexPairT& pair2)
{
return pair1.first < pair2.first;
}
...
Key2VectorIndexPairVectorT sortedVector;
sortedVector.reserve(originalVector.capacity());
// Assume "original" vector contains unsorted elements.
for (int i = 0; i < originalVector.size(); ++i)
{
const TheStruct& theStruct = originalVector[i];
sortedVector.insert(Key2VectorIndexPairT(theStruct.key, i));
}
std::sort(sortedVector.begin(), sortedVector.end(), Key2VectorIndexPairComparator);
...
const long keyToSearchFor = 20;
const Key2VectorIndexPairVectorT::const_iterator cItorKey2VectorIndexPairVector = std::lower_bound(sortedVector.begin(), sortedVector.end(), Key2VectorIndexPairT(keyToSearchFor, 0 /* Provide dummy index value for search */), Key2VectorIndexPairComparator);
if (cItorKey2VectorIndexPairVector->first == keyToSearchFor)
{
const int vectorIndex = cItorKey2VectorIndexPairVector->second;
const TheStruct& theStruct = originalVector[vectorIndex];
// Now do whatever you want...
}
else
{
// Could not find element...
}
This yielded a modest performance gain for me. Before the total time for my calculations were 3.75 milliseconds and now it is down to 2.5 milliseconds.
I am beginner in c++ and have some problem with hash table. I need a Hash table structure for my program. first I use boost unordered_map. it have all things that I need, but it make my program so slow. then I want to test stl hash_map, but I can't do all thing that I need. this is my first code ( this is sample)
#include <hash_map>
using namespace std;
struct eqstr
{
bool operator()(int s1, int s2) const
{
return s1==s2;
}
};
typedef stdext::hash_map< int, int, stdext::hash_compare< int, eqstr > > HashTable;
int main()
{
HashTable a;
a.insert( std::pair<int,int>( 1, 1 ) );
a.insert( std::pair<int,int>( 2, 2 ) );
a.insert( std::pair<int,int>( 4, 4 ) );
//next i want to change value of key 2 to 20
a[2] = 20;
//this code only insert pair<2,20> into a, buy when I use boost unordered_map this code modify previous key of 2
//next I try this code for delete 2 and insert new one
a.erase(2);//this code does work nothing !!!
//next I try to find 2 and delete it
HashTable::iterator i;
i = a.find(2);//this code return end, and does not work!!!
a.erase(i);//cause error
//but when I write this code, it works!!!
i=a.begin();
a.erase(i);
//and finally i write this code
for (i = a.begin(); i!=a.end(); ++i)
{
if (i->first == 2 )
break;
}
if (i!= a.end())
a.erase(i);
//and this code work
but if i want to search over my data, i use array not hash_map, why I can't access, modity and delete from hash_map with o(1)
what is my mistake, and which hash structure is fast for my program with many value modification in initializing phase. is google sparse_hash suitable for me, if it is, can give me some tutorial on it.
thanks for any help
You may look at: http://msdn.microsoft.com/en-us/library/525kffzd(VS.71).aspx
I think stdext::hash_compare< int, eqstr > is causing the problems here. Try to erase it.
Another implementation of a hash map is std::tr1::unordered_map. But I think that performance of various hash map implementation would be similar. Could you elaborate more about how slow the boost::unordered_map was? How did you use it? What for?
There are so many different varieties of hash map and many developers still write their own because you can so much more often get a higher performance in your own one, written to your own specific use, than you can from a generic one, and people tend to use hash when they want a really high performance.
The first thing you need to consider is what you really need to do and how much performance you really need, then determine whether something ready-made can meet that or whether you need to write something of your own.
If you never delete elements, for example, but just write once then constantly look-up, then you can often rehash to reduce collisions for the actual set you obtain: longer at setup time but faster at lookup.
An issue in writing your own will occur if you delete elements because it is not enough to "null" the entry, as another one may have stepped over yours as part of its collision course and now if you look that one up it will give up as "not found" as soon as it hits your null.
Suppose I have some data stored in a container of unique_ptrs:
struct MyData {
int id; // a unique id for this particular instance
data some_data; // arbitrary additional data
};
// ...
std::vector<std::unique_ptr<MyData>> my_data_vec;
The ordering of my_data_vec is important. Suppose now I have another vector of IDs of MyDatas:
std::vector<int> my_data_ids;
I now want to rearrange my_data_vec such that the elements are in the sequence specified by my_data_ids. (Don't forget moving a unique_ptr requires move-semantics with std::move().)
What's the most algorithmically efficient way to achieve this, and do any of the STL algorithms lend themselves well to achieving this? I can't see that std::sort would be any help.
Edit: I can use O(n) memory space (not too worried about memory), but the IDs are arbitrary (in my specific case they are actually randomly generated).
Create a map that maps ids to their index in my_data_ids.
Create a function object that compares std::unique_ptr<MyData> based on their ID's index in that map.
Use std::sort to sort the my_data_vec using that function object.
Here's a sketch of this:
// Beware, brain-compiled code ahead!
typedef std::vector<int> my_data_ids_type;
typedef std::map<int,my_data_ids_type::size_type> my_data_ids_map_type;
class my_id_comparator : public std::binary_function< bool
, std::unique_ptr<MyData>
, std::unique_ptr<MyData> > {
public:
my_id_comparator(const my_data_ids_map_type& my_data_ids_map)
: my_data_ids_map_(my_data_ids_map) {}
bool operator()( const std::unique_ptr<MyData>& lhs
, const std::unique_ptr<MyData>& rhs ) const
{
my_data_ids_map_type::const_iterator it_lhs = my_data_ids_map_.find(lhs.id);
my_data_ids_map_type::const_iterator it_rhs = my_data_ids_map_.find(rhs.id);
if( it_lhs == my_data_ids_map_.end() || it_rhs == my_data_ids_map_.end() )
throw "dammit!"; // whatever
return it_lhs->second < it_rhs->second;
}
private
my_data_ids_map_type& my_data_ids_map_;
};
//...
my_data_ids_map_type my_data_ids_map;
// ...
// populate my_data_ids_map with the IDs and their indexes from my_data_ids
// ...
std::sort( my_data_vec.begin(), my_data_vec.end(), my_id_comparator(my_data_ids_map) );
If memory is scarce, but time doesn't matter, you could do away with the map and search the IDs in the my_data_ids vector for each comparison. However, you would have to be really desperate for memory to do that, since two linearly complex operations per comparison are going to be quite expensive.
Why don't you try moving the data into a STL Set ? you need only to implement the comparison function, and you will end up with a perfectly ordered set of data very fast.
Why don't you just use a map<int, unique_ptr<MyData>> (or multimap)?
I'm currently working on a DNA database class and I currently associate each row in the database with both a match score (based on edit distance) and the actual DNA sequence itself, is it safe to modify first this way within an iteration loop?
typedef std::pair<int, DnaDatabaseRow> DnaPairT;
typedef std::vector<DnaPairT> DnaDatabaseT;
// ....
for(DnaDatabaseT::iterator it = database.begin();
it != database.end(); it++)
{
int score = it->second.query(query);
it->first = score;
}
The reason I am doing this is so that I can sort them by score later. I have tried maps and received a compilation error about modifying first, but is there perhaps a better way than this to store all the information for sorting later?
To answer your first question, yes. It is perfectly safe to modify the members of your pair, since the actual data in the pair does not affect the vector itself.
edit: I have a feeling that you were getting an error when using a map because you tried to modify the first value of the map's internal pair. That would not be allowed because that value is part of the map's inner workings.
As stated by dribeas:
In maps you cannot change first as it would break the invariant of the map being a sorted balanced tree
edit: To answer your second question, I see nothing at all wrong with the way you are structuring the data, but I would have the database hold pointers to DnaPairT objects, instead of the objects themselves. This would dramatically reduce the amount of memory that gets copied around during the sort procedure.
#include <vector>
#include <utility>
#include <algorithm>
typedef std::pair<int, DnaDatabaseRow> DnaPairT;
typedef std::vector<DnaPairT *> DnaDatabaseT;
// ...
// your scoring code, modified to use pointers
void calculateScoresForQuery(DnaDatabaseT& database, queryT& query)
{
for(DnaDatabaseT::iterator it = database.begin(); it != database.end(); it++)
{
int score = (*it)->second.query(query);
(*it)->first = score;
}
}
// custom sorting function to handle DnaPairT pointers
bool sortByScore(DnaPairT * A, DnaPairT * B) { return (A->first < B->first); }
// function to sort the database
void sortDatabaseByScore(DnaDatabaseT& database)
{
sort(database.begin(), database.end(), sortByScore);
}
// main
int main()
{
DnaDatabaseT database;
// code to load the database with DnaPairT pointers ...
calculateScoresForQuery(database, query);
sortDatabaseByScore(database);
// code that uses the sorted database ...
}
The only reason you might need to look into more efficient methods is if your database is so enormous that the sorting loop takes too long to complete. If that is the case, though, I would imagine that your query function would be the one taking up most of the processing time.
You can't modify since the variable first of std::pair is defined const