I was looking at STL containers and trying to figure what they really are (i.e. the data structure used), and the deque stopped me: I thought at first that it was a double linked list, which would allow insertion and deletion from both ends in constant time, but I am troubled by the promise made by the operator [] to be done in constant time. In a linked list, arbitrary access should be O(n), right?
And if it's a dynamic array, how can it add elements in constant time? It should be mentioned that reallocation may happen, and that O(1) is an amortized cost, like for a vector.
So I wonder what is this structure that allows arbitrary access in constant time, and at the same time never needs to be moved to a new bigger place.
A deque is somewhat recursively defined: internally it maintains a double-ended queue of chunks of fixed size. Each chunk is a vector, and the queue (“map” in the graphic below) of chunks itself is also a vector.
There’s a great analysis of the performance characteristics and how it compares to the vector over at CodeProject.
The GCC standard library implementation internally uses a T** to represent the map. Each data block is a T* which is allocated with some fixed size __deque_buf_size (which depends on sizeof(T)).
From overview, you can think deque as a double-ended queue
The datas in deque are stored by chuncks of fixed size vector, which are
pointered by a map(which is also a chunk of vector, but its size may change)
The main part code of the deque iterator is as below:
/*
buff_size is the length of the chunk
*/
template <class T, size_t buff_size>
struct __deque_iterator{
typedef __deque_iterator<T, buff_size> iterator;
typedef T** map_pointer;
// pointer to the chunk
T* cur;
T* first; // the begin of the chunk
T* last; // the end of the chunk
//because the pointer may skip to other chunk
//so this pointer to the map
map_pointer node; // pointer to the map
}
The main part code of the deque is as below:
/*
buff_size is the length of the chunk
*/
template<typename T, size_t buff_size = 0>
class deque{
public:
typedef T value_type;
typedef T& reference;
typedef T* pointer;
typedef __deque_iterator<T, buff_size> iterator;
typedef size_t size_type;
typedef ptrdiff_t difference_type;
protected:
typedef pointer* map_pointer;
// allocate memory for the chunk
typedef allocator<value_type> dataAllocator;
// allocate memory for map
typedef allocator<pointer> mapAllocator;
private:
//data members
iterator start;
iterator finish;
map_pointer map;
size_type map_size;
}
Below i will give you the core code of deque, mainly about three parts:
iterator
How to construct a deque
1. iterator(__deque_iterator)
The main problem of iterator is, when ++, -- iterator, it may skip to other chunk(if it pointer to edge of chunk). For example, there are three data chunks: chunk 1,chunk 2,chunk 3.
The pointer1 pointers to the begin of chunk 2, when operator --pointer it will pointer to the end of chunk 1, so as to the pointer2.
Below I will give the main function of __deque_iterator:
Firstly, skip to any chunk:
void set_node(map_pointer new_node){
node = new_node;
first = *new_node;
last = first + chunk_size();
}
Note that, the chunk_size() function which compute the chunk size, you can think of it returns 8 for simplify here.
operator* get the data in the chunk
reference operator*()const{
return *cur;
}
operator++, --
// prefix forms of increment
self& operator++(){
++cur;
if (cur == last){ //if it reach the end of the chunk
set_node(node + 1);//skip to the next chunk
cur = first;
}
return *this;
}
// postfix forms of increment
self operator++(int){
self tmp = *this;
++*this;//invoke prefix ++
return tmp;
}
self& operator--(){
if(cur == first){ // if it pointer to the begin of the chunk
set_node(node - 1);//skip to the prev chunk
cur = last;
}
--cur;
return *this;
}
self operator--(int){
self tmp = *this;
--*this;
return tmp;
}
iterator skip n steps / random access
self& operator+=(difference_type n){ // n can be postive or negative
difference_type offset = n + (cur - first);
if(offset >=0 && offset < difference_type(buffer_size())){
// in the same chunk
cur += n;
}else{//not in the same chunk
difference_type node_offset;
if (offset > 0){
node_offset = offset / difference_type(chunk_size());
}else{
node_offset = -((-offset - 1) / difference_type(chunk_size())) - 1 ;
}
// skip to the new chunk
set_node(node + node_offset);
// set new cur
cur = first + (offset - node_offset * chunk_size());
}
return *this;
}
// skip n steps
self operator+(difference_type n)const{
self tmp = *this;
return tmp+= n; //reuse operator +=
}
self& operator-=(difference_type n){
return *this += -n; //reuse operator +=
}
self operator-(difference_type n)const{
self tmp = *this;
return tmp -= n; //reuse operator +=
}
// random access (iterator can skip n steps)
// invoke operator + ,operator *
reference operator[](difference_type n)const{
return *(*this + n);
}
2. How to construct a deque
common function of deque
iterator begin(){return start;}
iterator end(){return finish;}
reference front(){
//invoke __deque_iterator operator*
// return start's member *cur
return *start;
}
reference back(){
// cna't use *finish
iterator tmp = finish;
--tmp;
return *tmp; //return finish's *cur
}
reference operator[](size_type n){
//random access, use __deque_iterator operator[]
return start[n];
}
template<typename T, size_t buff_size>
deque<T, buff_size>::deque(size_t n, const value_type& value){
fill_initialize(n, value);
}
template<typename T, size_t buff_size>
void deque<T, buff_size>::fill_initialize(size_t n, const value_type& value){
// allocate memory for map and chunk
// initialize pointer
create_map_and_nodes(n);
// initialize value for the chunks
for (map_pointer cur = start.node; cur < finish.node; ++cur) {
initialized_fill_n(*cur, chunk_size(), value);
}
// the end chunk may have space node, which don't need have initialize value
initialized_fill_n(finish.first, finish.cur - finish.first, value);
}
template<typename T, size_t buff_size>
void deque<T, buff_size>::create_map_and_nodes(size_t num_elements){
// the needed map node = (elements nums / chunk length) + 1
size_type num_nodes = num_elements / chunk_size() + 1;
// map node num。min num is 8 ,max num is "needed size + 2"
map_size = std::max(8, num_nodes + 2);
// allocate map array
map = mapAllocator::allocate(map_size);
// tmp_start,tmp_finish poniters to the center range of map
map_pointer tmp_start = map + (map_size - num_nodes) / 2;
map_pointer tmp_finish = tmp_start + num_nodes - 1;
// allocate memory for the chunk pointered by map node
for (map_pointer cur = tmp_start; cur <= tmp_finish; ++cur) {
*cur = dataAllocator::allocate(chunk_size());
}
// set start and end iterator
start.set_node(tmp_start);
start.cur = start.first;
finish.set_node(tmp_finish);
finish.cur = finish.first + num_elements % chunk_size();
}
Let's assume i_deque has 20 int elements 0~19 whose chunk size is 8, and now push_back 3 elements (0, 1, 2) to i_deque:
i_deque.push_back(0);
i_deque.push_back(1);
i_deque.push_back(2);
It's internal structure like below:
Then push_back again, it will invoke allocate new chunk:
push_back(3)
If we push_front, it will allocate new chunk before the prev start
Note when push_back element into deque, if all the maps and chunks are filled, it will cause allocate new map, and adjust chunks.But the above code may be enough for you to understand deque.
Imagine it as a vector of vectors. Only they aren't standard std::vectors.
The outer vector contains pointers to the inner vectors. When its capacity is changed via reallocation, rather than allocating all of the empty space to the end as std::vector does, it splits the empty space to equal parts at the beginning and the end of the vector. This allows push_front and push_back on this vector to both occur in amortized O(1) time.
The inner vector behavior needs to change depending on whether it's at the front or the back of the deque. At the back it can behave as a standard std::vector where it grows at the end, and push_back occurs in O(1) time. At the front it needs to do the opposite, growing at the beginning with each push_front. In practice this is easily achieved by adding a pointer to the front element and the direction of growth along with the size. With this simple modification push_front can also be O(1) time.
Access to any element requires offsetting and dividing to the proper outer vector index which occurs in O(1), and indexing into the inner vector which is also O(1). This assumes that the inner vectors are all fixed size, except for the ones at the beginning or the end of the deque.
(This is an answer I've given in another thread. Essentially I'm arguing that even fairly naive implementations, using a single vector, conform to the requirements of "constant non-amortized push_{front,back}". You might be surprised, and think this is impossible, but I have found other relevant quotes in the standard that define the context in a surprising way. Please bear with me; if I have made a mistake in this answer, it would be very helpful to identify which things I have said correctly and where my logic has broken down. )
In this answer, I am not trying to identify a good implementation, I'm merely trying to help us to interpret the complexity requirements in the C++ standard. I'm quoting from N3242, which is, according to Wikipedia, the latest freely available C++11 standardization document. (It appears to be organized differently from the final standard, and hence I won't quote the exact page numbers. Of course, these rules might have changed in the final standard, but I don't think that has happened.)
A deque<T> could be implemented correctly by using a vector<T*>. All the elements are copied onto the heap and the pointers stored in a vector. (More on the vector later).
Why T* instead of T? Because the standard requires that
"An insertion at either end of the deque invalidates all the iterators
to the deque, but has no effect on the validity of references to
elements of the deque."
(my emphasis). The T* helps to satisfy that. It also helps us to satisfy this:
"Inserting a single element either at the beginning or end of a deque always ..... causes a single call to a constructor of T."
Now for the (controversial) bit. Why use a vector to store the T*? It gives us random access, which is a good start. Let's forget about the complexity of vector for a moment and build up to this carefully:
The standard talks about "the number of operations on the contained objects.". For deque::push_front this is clearly 1 because exactly one T object is constructed and zero of the existing T objects are read or scanned in any way. This number, 1, is clearly a constant and is independent of the number of objects currently in the deque. This allows us to say that:
'For our deque::push_front, the number of operations on the contained objects (the Ts) is fixed and is independent of the number of objects already in the deque.'
Of course, the number of operations on the T* will not be so well-behaved. When the vector<T*> grows too big, it'll be realloced and many T*s will be copied around. So yes, the number of operations on the T* will vary wildly, but the number of operations on T will not be affected.
Why do we care about this distinction between counting operations on T and counting operations on T*? It's because the standard says:
All of the complexity requirements in this clause are stated solely in terms of the number of operations on the contained objects.
For the deque, the contained objects are the T, not the T*, meaning we can ignore any operation which copies (or reallocs) a T*.
I haven't said much about how a vector would behave in a deque. Perhaps we would interpret it as a circular buffer (with the vector always taking up its maximum capacity(), and then realloc everything into a bigger buffer when the vector is full. The details don't matter.
In the last few paragraphs, we have analyzed deque::push_front and the relationship between the number of objects in the deque already and the number of operations performed by push_front on contained T-objects. And we found they were independent of each other. As the standard mandates that complexity is in terms of operations-on-T, then we can say this has constant complexity.
Yes, the Operations-On-T*-Complexity is amortized (due to the vector), but we're only interested in the Operations-On-T-Complexity and this is constant (non-amortized).
The complexity of vector::push_back or vector::push_front is irrelevant in this implementation; those considerations involve operations on T* and hence are irrelevant. If the standard was referring to the 'conventional' theoretical notion of complexity, then they wouldn't have explicitly restricted themselves to the "number of operations on the contained objects". Am I overinterpreting that sentence?
deque = double ended queue
A container which can grow in either direction.
Deque is typically implemented as a vector of vectors (a list of vectors can't give constant time random access). While the size of the secondary vectors is implementation dependent, a common algorithm is to use a constant size in bytes.
I was reading "Data structures and algorithms in C++" by Adam Drozdek, and found this useful.
HTH.
A very interesting aspect of STL deque is its implementation. An STL deque is not implemented as a linked list but as an array of pointers to blocks or arrays of data. The number of blocks changes dynamically depending on storage needs, and the size of the array of pointers changes accordingly.
You can notice in the middle is the array of pointers to the data (chunks on the right), and also you can notice that the array in the middle is dynamically changing.
An image is worth a thousand words.
While the standard doesn't mandate any particular implementation (only constant-time random access), a deque is usually implemented as a collection of contiguous memory "pages". New pages are allocated as needed, but you still have random access. Unlike std::vector, you're not promised that data is stored contiguously, but like vector, insertions in the middle require lots of relocating.
deque could be implemented as a circular buffer of fixed size array:
Use circular buffer so we could grow/shrink at both end by adding/removing a fixed sized array with O(1) complexity
Use fixed sized array so it is easy to calculate the index, hence access via index with two pointer dereferences - also O(1)
Related
I was looking at STL containers and trying to figure what they really are (i.e. the data structure used), and the deque stopped me: I thought at first that it was a double linked list, which would allow insertion and deletion from both ends in constant time, but I am troubled by the promise made by the operator [] to be done in constant time. In a linked list, arbitrary access should be O(n), right?
And if it's a dynamic array, how can it add elements in constant time? It should be mentioned that reallocation may happen, and that O(1) is an amortized cost, like for a vector.
So I wonder what is this structure that allows arbitrary access in constant time, and at the same time never needs to be moved to a new bigger place.
A deque is somewhat recursively defined: internally it maintains a double-ended queue of chunks of fixed size. Each chunk is a vector, and the queue (“map” in the graphic below) of chunks itself is also a vector.
There’s a great analysis of the performance characteristics and how it compares to the vector over at CodeProject.
The GCC standard library implementation internally uses a T** to represent the map. Each data block is a T* which is allocated with some fixed size __deque_buf_size (which depends on sizeof(T)).
From overview, you can think deque as a double-ended queue
The datas in deque are stored by chuncks of fixed size vector, which are
pointered by a map(which is also a chunk of vector, but its size may change)
The main part code of the deque iterator is as below:
/*
buff_size is the length of the chunk
*/
template <class T, size_t buff_size>
struct __deque_iterator{
typedef __deque_iterator<T, buff_size> iterator;
typedef T** map_pointer;
// pointer to the chunk
T* cur;
T* first; // the begin of the chunk
T* last; // the end of the chunk
//because the pointer may skip to other chunk
//so this pointer to the map
map_pointer node; // pointer to the map
}
The main part code of the deque is as below:
/*
buff_size is the length of the chunk
*/
template<typename T, size_t buff_size = 0>
class deque{
public:
typedef T value_type;
typedef T& reference;
typedef T* pointer;
typedef __deque_iterator<T, buff_size> iterator;
typedef size_t size_type;
typedef ptrdiff_t difference_type;
protected:
typedef pointer* map_pointer;
// allocate memory for the chunk
typedef allocator<value_type> dataAllocator;
// allocate memory for map
typedef allocator<pointer> mapAllocator;
private:
//data members
iterator start;
iterator finish;
map_pointer map;
size_type map_size;
}
Below i will give you the core code of deque, mainly about three parts:
iterator
How to construct a deque
1. iterator(__deque_iterator)
The main problem of iterator is, when ++, -- iterator, it may skip to other chunk(if it pointer to edge of chunk). For example, there are three data chunks: chunk 1,chunk 2,chunk 3.
The pointer1 pointers to the begin of chunk 2, when operator --pointer it will pointer to the end of chunk 1, so as to the pointer2.
Below I will give the main function of __deque_iterator:
Firstly, skip to any chunk:
void set_node(map_pointer new_node){
node = new_node;
first = *new_node;
last = first + chunk_size();
}
Note that, the chunk_size() function which compute the chunk size, you can think of it returns 8 for simplify here.
operator* get the data in the chunk
reference operator*()const{
return *cur;
}
operator++, --
// prefix forms of increment
self& operator++(){
++cur;
if (cur == last){ //if it reach the end of the chunk
set_node(node + 1);//skip to the next chunk
cur = first;
}
return *this;
}
// postfix forms of increment
self operator++(int){
self tmp = *this;
++*this;//invoke prefix ++
return tmp;
}
self& operator--(){
if(cur == first){ // if it pointer to the begin of the chunk
set_node(node - 1);//skip to the prev chunk
cur = last;
}
--cur;
return *this;
}
self operator--(int){
self tmp = *this;
--*this;
return tmp;
}
iterator skip n steps / random access
self& operator+=(difference_type n){ // n can be postive or negative
difference_type offset = n + (cur - first);
if(offset >=0 && offset < difference_type(buffer_size())){
// in the same chunk
cur += n;
}else{//not in the same chunk
difference_type node_offset;
if (offset > 0){
node_offset = offset / difference_type(chunk_size());
}else{
node_offset = -((-offset - 1) / difference_type(chunk_size())) - 1 ;
}
// skip to the new chunk
set_node(node + node_offset);
// set new cur
cur = first + (offset - node_offset * chunk_size());
}
return *this;
}
// skip n steps
self operator+(difference_type n)const{
self tmp = *this;
return tmp+= n; //reuse operator +=
}
self& operator-=(difference_type n){
return *this += -n; //reuse operator +=
}
self operator-(difference_type n)const{
self tmp = *this;
return tmp -= n; //reuse operator +=
}
// random access (iterator can skip n steps)
// invoke operator + ,operator *
reference operator[](difference_type n)const{
return *(*this + n);
}
2. How to construct a deque
common function of deque
iterator begin(){return start;}
iterator end(){return finish;}
reference front(){
//invoke __deque_iterator operator*
// return start's member *cur
return *start;
}
reference back(){
// cna't use *finish
iterator tmp = finish;
--tmp;
return *tmp; //return finish's *cur
}
reference operator[](size_type n){
//random access, use __deque_iterator operator[]
return start[n];
}
template<typename T, size_t buff_size>
deque<T, buff_size>::deque(size_t n, const value_type& value){
fill_initialize(n, value);
}
template<typename T, size_t buff_size>
void deque<T, buff_size>::fill_initialize(size_t n, const value_type& value){
// allocate memory for map and chunk
// initialize pointer
create_map_and_nodes(n);
// initialize value for the chunks
for (map_pointer cur = start.node; cur < finish.node; ++cur) {
initialized_fill_n(*cur, chunk_size(), value);
}
// the end chunk may have space node, which don't need have initialize value
initialized_fill_n(finish.first, finish.cur - finish.first, value);
}
template<typename T, size_t buff_size>
void deque<T, buff_size>::create_map_and_nodes(size_t num_elements){
// the needed map node = (elements nums / chunk length) + 1
size_type num_nodes = num_elements / chunk_size() + 1;
// map node num。min num is 8 ,max num is "needed size + 2"
map_size = std::max(8, num_nodes + 2);
// allocate map array
map = mapAllocator::allocate(map_size);
// tmp_start,tmp_finish poniters to the center range of map
map_pointer tmp_start = map + (map_size - num_nodes) / 2;
map_pointer tmp_finish = tmp_start + num_nodes - 1;
// allocate memory for the chunk pointered by map node
for (map_pointer cur = tmp_start; cur <= tmp_finish; ++cur) {
*cur = dataAllocator::allocate(chunk_size());
}
// set start and end iterator
start.set_node(tmp_start);
start.cur = start.first;
finish.set_node(tmp_finish);
finish.cur = finish.first + num_elements % chunk_size();
}
Let's assume i_deque has 20 int elements 0~19 whose chunk size is 8, and now push_back 3 elements (0, 1, 2) to i_deque:
i_deque.push_back(0);
i_deque.push_back(1);
i_deque.push_back(2);
It's internal structure like below:
Then push_back again, it will invoke allocate new chunk:
push_back(3)
If we push_front, it will allocate new chunk before the prev start
Note when push_back element into deque, if all the maps and chunks are filled, it will cause allocate new map, and adjust chunks.But the above code may be enough for you to understand deque.
Imagine it as a vector of vectors. Only they aren't standard std::vectors.
The outer vector contains pointers to the inner vectors. When its capacity is changed via reallocation, rather than allocating all of the empty space to the end as std::vector does, it splits the empty space to equal parts at the beginning and the end of the vector. This allows push_front and push_back on this vector to both occur in amortized O(1) time.
The inner vector behavior needs to change depending on whether it's at the front or the back of the deque. At the back it can behave as a standard std::vector where it grows at the end, and push_back occurs in O(1) time. At the front it needs to do the opposite, growing at the beginning with each push_front. In practice this is easily achieved by adding a pointer to the front element and the direction of growth along with the size. With this simple modification push_front can also be O(1) time.
Access to any element requires offsetting and dividing to the proper outer vector index which occurs in O(1), and indexing into the inner vector which is also O(1). This assumes that the inner vectors are all fixed size, except for the ones at the beginning or the end of the deque.
(This is an answer I've given in another thread. Essentially I'm arguing that even fairly naive implementations, using a single vector, conform to the requirements of "constant non-amortized push_{front,back}". You might be surprised, and think this is impossible, but I have found other relevant quotes in the standard that define the context in a surprising way. Please bear with me; if I have made a mistake in this answer, it would be very helpful to identify which things I have said correctly and where my logic has broken down. )
In this answer, I am not trying to identify a good implementation, I'm merely trying to help us to interpret the complexity requirements in the C++ standard. I'm quoting from N3242, which is, according to Wikipedia, the latest freely available C++11 standardization document. (It appears to be organized differently from the final standard, and hence I won't quote the exact page numbers. Of course, these rules might have changed in the final standard, but I don't think that has happened.)
A deque<T> could be implemented correctly by using a vector<T*>. All the elements are copied onto the heap and the pointers stored in a vector. (More on the vector later).
Why T* instead of T? Because the standard requires that
"An insertion at either end of the deque invalidates all the iterators
to the deque, but has no effect on the validity of references to
elements of the deque."
(my emphasis). The T* helps to satisfy that. It also helps us to satisfy this:
"Inserting a single element either at the beginning or end of a deque always ..... causes a single call to a constructor of T."
Now for the (controversial) bit. Why use a vector to store the T*? It gives us random access, which is a good start. Let's forget about the complexity of vector for a moment and build up to this carefully:
The standard talks about "the number of operations on the contained objects.". For deque::push_front this is clearly 1 because exactly one T object is constructed and zero of the existing T objects are read or scanned in any way. This number, 1, is clearly a constant and is independent of the number of objects currently in the deque. This allows us to say that:
'For our deque::push_front, the number of operations on the contained objects (the Ts) is fixed and is independent of the number of objects already in the deque.'
Of course, the number of operations on the T* will not be so well-behaved. When the vector<T*> grows too big, it'll be realloced and many T*s will be copied around. So yes, the number of operations on the T* will vary wildly, but the number of operations on T will not be affected.
Why do we care about this distinction between counting operations on T and counting operations on T*? It's because the standard says:
All of the complexity requirements in this clause are stated solely in terms of the number of operations on the contained objects.
For the deque, the contained objects are the T, not the T*, meaning we can ignore any operation which copies (or reallocs) a T*.
I haven't said much about how a vector would behave in a deque. Perhaps we would interpret it as a circular buffer (with the vector always taking up its maximum capacity(), and then realloc everything into a bigger buffer when the vector is full. The details don't matter.
In the last few paragraphs, we have analyzed deque::push_front and the relationship between the number of objects in the deque already and the number of operations performed by push_front on contained T-objects. And we found they were independent of each other. As the standard mandates that complexity is in terms of operations-on-T, then we can say this has constant complexity.
Yes, the Operations-On-T*-Complexity is amortized (due to the vector), but we're only interested in the Operations-On-T-Complexity and this is constant (non-amortized).
The complexity of vector::push_back or vector::push_front is irrelevant in this implementation; those considerations involve operations on T* and hence are irrelevant. If the standard was referring to the 'conventional' theoretical notion of complexity, then they wouldn't have explicitly restricted themselves to the "number of operations on the contained objects". Am I overinterpreting that sentence?
deque = double ended queue
A container which can grow in either direction.
Deque is typically implemented as a vector of vectors (a list of vectors can't give constant time random access). While the size of the secondary vectors is implementation dependent, a common algorithm is to use a constant size in bytes.
I was reading "Data structures and algorithms in C++" by Adam Drozdek, and found this useful.
HTH.
A very interesting aspect of STL deque is its implementation. An STL deque is not implemented as a linked list but as an array of pointers to blocks or arrays of data. The number of blocks changes dynamically depending on storage needs, and the size of the array of pointers changes accordingly.
You can notice in the middle is the array of pointers to the data (chunks on the right), and also you can notice that the array in the middle is dynamically changing.
An image is worth a thousand words.
While the standard doesn't mandate any particular implementation (only constant-time random access), a deque is usually implemented as a collection of contiguous memory "pages". New pages are allocated as needed, but you still have random access. Unlike std::vector, you're not promised that data is stored contiguously, but like vector, insertions in the middle require lots of relocating.
deque could be implemented as a circular buffer of fixed size array:
Use circular buffer so we could grow/shrink at both end by adding/removing a fixed sized array with O(1) complexity
Use fixed sized array so it is easy to calculate the index, hence access via index with two pointer dereferences - also O(1)
Can someone tell me if there is a datatype in C++/STL that allows me to solve the following problem comfortably:
I have a preallocated contiguous area of memory representing an array of objects of type T.
I have a raw pointer ptrEnd to this area which points right after the last object of the area.
I have a pointer ptrCurrent that points to some position inside this area.
Now what I want is some kind of wrapper class that helps me insert new elements into this area. It should have some kind of "append" function which basically does the following things
Assign *ptrCurrent the value of object to insert
Increment ptrCurrent by one.
Omit the aforementioned steps if ptrCurrent >= ptrEnd. Return an error instead (or a false to indicate failure).
I could write something like this myself, but I wanted to ask first if there is a class in C++ STL that allows me to solve this problem more elegantly.
Thanks for your help.
There is a convenient feature for exactly this in C++17, polymorphic allocators. More specifically, this is what you want:
std::pmr::monotonic_buffer_resource buffer(sizeof(T) * 256);
// Buffer that can hold 256 objects of type `T`.
std::pmr::vector<T> vec(&buffer);
// The vector will use `buffer` as the backing storage.
live godbolt.org example
You'd need to write an Allocator that hands out Ts from your array, and then std::vector can use it.
template <typename T>
class ArrayAllocator
{
T* current;
T* end;
public:
using value_type = T;
ArrayAllocator(T* start, T* end) : current(start), end(end) {}
T* allocate(size_t n)
{
if (current + n >= end) throw std::bad_alloc();
T * result = current;
current += n;
return result;
}
void deallocate(T* what, size_t n)
{
if (what + n != current) throw std::runtime_error("bad deallocate");
current = what;
}
size_t max_size() { return end - current; }
};
You'd have to immediately reserve the whole amount, because when vector reallocates it needs to copy the old values into the new space, which will result in a "bad deallocate".
I ended up writing an AppendHelper class that takes the start and end pointer and otherwise reproduces the std::vector interface. I realized that using std::vector with a custom allocator meant not having full control over when allocation and deallocation is performed, so the result could behave differently from my original intention.
I need the lighter container that must store till 128 unsigned int.
It must add, edit and remove each element accessing it quickly, without allocating new memory every time (I already know it will be max 128).
Such as:
add int 40 at index 4 (1/128 item used)
add int 36 at index 90 (2/128 item used)
edit to value 42 the element at index 4
add int 36 at index 54 (3/128 item used)
remove element with index 90 (2/128 item used)
remove element with index 4 (1/128 item used)
... and so on. So every time I can iterate trought only the real number of elements added to the container, not all and check if NULL or not.
During this process, as I said, it must not allocating/reallocating new memory, since I'm using an app that manage "audio" data and this means a glitch every time I touch the memory.
Which container would be the right candidate?
It sounds like a "indexes" queue.
As I understand the question, you have two operations
Insert/replace element value at cell index
Delete element at cell index
and one predicate
Is cell index currently occupied?
This is an array and a bitmap. When you insert/replace, you stick the value in the array cell and set the bitmap bit. When you delete, you clear the bitmap bit. When you ask, you query the bitmap bit.
You can just use std::vector<int> and do vector.reserve(128); to keep the vector from allocating memory. This doesn't allow you to keep track of particular indices though.
If you need to keep track of an 'index' you could use std::vector<std::pair<int, int>>. This doesn't allow random access though.
If you only need cheap setting and erasing values, just use an array. You
can keep track of what cells are used by marking them in another array (or bitmap). Or by just defining one value (e.g. 0 or -1) as an "unused" value.
Of course, if you need to iterate over all used cells, you need to scan the whole array. But that's a tradeoff you need to make: either do more work during adding and erasing, or do more work during a search. (Note that an .insert() in the middle of a vector<> will move data around.)
In any case, 128 elements is so few, that a scan through the whole array will be negligible work. And frankly, I think anything more complex than a vector will be total overkill. :)
Roughly:
unsigned data[128] = {0}; // initialize
unsigned used[128] = {0};
data[index] = newvalue; used[index] = 1; // set value
data[index] = used[index] = 0; // unset value
// check if a cell is used and do something
if (used[index]) { do something } else { do something else }
I'd suggest a tandem of vectors, one to hold the active indices, the other to hold the data:
class Container
{
std::vector<size_t> indices;
std::vector<int> data;
size_t index_worldToData(size_t worldIndex) const
{
auto it = std::lower_bound(begin(indices), end(indices), worldIndex);
return it - begin(indices);
}
public:
Container()
{
indices.reserve(128);
data.reserve(128);
}
int& operator[] (size_t worldIndex)
{
return data[index_worldToData(worldIndex)];
}
void addElement(size_t worldIndex, int element)
{
auto dataIndex = index_worldToData(worldIndex);
indices.insert(it, worldIndex);
data.insert(begin(data) + dataIndex, element);
}
void removeElement(size_t worldIndex)
{
auto dataIndex = index_worldToData(worldIndex);
indices.erase(begin(indices) + dataIndex);
data.erase(begin(indices) + dataIndex);
}
class iterator
{
Container *cnt;
size_t dataIndex;
public:
int& operator* () const { return cnt.data[dataIndex]; }
iterator& operator++ () { ++dataIndex; }
};
iterator begin() { return iterator{ this, 0 }; }
iterator end() { return iterator{ this, indices.size() }; }
};
(Disclaimer: code not touched by compiler, preconditions checks omitted)
This one has logarithmic time element access, linear time insertion and removal, and allows iterating over non-empty elements.
You could use a doubly-linked list and an array of node pointers.
Preallocate 128 list nodes and keep them on freelist.
Create a empty itemlist.
Allocate an array of 128 node pointers called items
To insert at i: Pop the head node from freelist, add it to
itemlist, set items[i] to point at it.
To access/change a value, use items[i]->value
To delete at i, remove the node pointed to by items[i], reinsert it in 'freelist'
To iterate, just walk itemlist
Everything is O(1) except iteration, which is O(Nactive_items). Only caveat is that iteration is not in index order.
Freelist can be singly-linked, or even an array of nodes, as all you need is pop and push.
class Container {
private:
set<size_t> indices;
unsigned int buffer[128];
public:
void set_elem(const size_t index, const unsigned int element) {
buffer[index] = element;
indices.insert(index);
}
// and so on -- iterate over the indices if necessary
};
There are multiple approaches that you can use, I will cite them in order of effort expended.
The most affordable solution is to use the Boost non-standard containers, of particular interest is flat_map. Essentially, a flat_map offers the interface of a map over the storage provided by a dynamic array.
You can call its reserve member at the start to avoid memory allocation afterward.
A slightly more involved solution is to code your own memory allocator.
The interface of an allocator is relatively easy to deal with, so that coding an allocator is quite simple. Create a pool-allocator which will never release any element, warm it up (allocate 128 elements) and you are ready to go: it can be plugged in any collection to make it memory-allocation-free.
Of particular interest, here, is of course std::map.
Finally, there is the do-it-yourself road. Much more involved, quite obviously: the number of operations supported by standard containers is just... huge.
Still, if you have the time or can live with only a subset of those operations, then this road has one undeniable advantage: you can tailor the container specifically to your needs.
Of particular interest here is the idea of having a std::vector<boost::optional<int>> of 128 elements... except that since this representation is quite space inefficient, we use the Data-Oriented Design to instead make it two vectors: std::vector<int> and std::vector<bool>, which is much more compact, or even...
struct Container {
size_t const Size = 128;
int array[Size];
std::bitset<Size> marker;
}
which is both compact and allocation-free.
Now, iterating requires iterating the bitset for present elements, which might seem wasteful at first, but said bitset is only 16 bytes long so it's a breeze! (because at such scale memory locality trumps big-O complexity)
Why not use std::map<int, int>, it provides random access and is sparse.
If a vector (pre-reserved) is not handy enough, look into Boost.Container for various “flat” varieties of indexed collections. This will store everything in a vector and not need memory manipulation, but adds a layer on top to make it a set or map, indexable by which elements are present and able to tell which are not.
I've written some code to decrease the capacity of a templated container class. After an element is removed from the container, the erase function checks to see whether or not 25% of the total space is in use, and whether reducing the capacity by half would cause it to be less than the default size I've set. If these two return true, then the downsize function runs. However, if this happens while I'm in the middle of a const_iterator loop, I get a segfault.
edit again: I'm thinking it's because the const_iterator pointer is pointing to the old array and needs to be pointed to the new one created by downsize()...now how to go about doing that...
template <class T>
void sorted<T>::downsize(){
// Run the same process as resize, except
// in reverse (sort of).
int newCapacity = (m_capacity / 2);
T *temp_array = new T[newCapacity];
for (int i = 0; i < m_size; i++)
temp_array[i] = m_data[i];
// Frees memory, points m_data at the
// new, smaller array, sets the capacity
// to the proper (lower) value.
delete [] m_data;
m_data = temp_array;
setCap(newCapacity);
cout << "Decreased array capacity to " << newCapacity << "." << endl;
}
// Implementation of the const_iterator erase method.
template <class T>
typename sorted<T>::const_iterator sorted<T>::erase(const_iterator itr){
// This section is reused from game.cpp, a file provided in the
// Cruno project. It handles erasing the element pointed to
// by the constant iterator.
T *end = &m_data[m_capacity]; // one past the end of data
T *ptr = itr.m_current; // element to erase
// to erase element at ptr, shift elements from ptr+1 to
// the end of the array down one position
while ( ptr+1 != end ) {
*ptr = *(ptr+1);
ptr++;
}
m_size--;
// Once the element is removed, check to
// see if a size reduction of the array is
// necessary.
// Initialized some new values here to make
// sure downsize only runs when the correct
// conditions are met.
double capCheck = m_capacity;
double sizeCheck = m_size;
double usedCheck = (sizeCheck / capCheck);
int boundCheck = (m_capacity / 2);
if ((usedCheck <= ONE_FOURTH) && (boundCheck >= DEFAULT_SIZE))
downsize();
return itr;
}
// Chunk from main that erases.
int i = 0;
for (itr = x.begin(); itr != x.end(); itr++) {
if (i < 7) x.erase(itr);
i++;
}
To prevent issues with invalidated iterators during an erase loop, you can use:
x.erase(itr++);
instead of separate increment and increment calls (obviously if you're not erasing everything you loop over you'd need an else case to increment past the non-erased items.) Note this is a case where you need to use post-increment rather than pre-increment.
The whole thing looks a bit inefficient though. The way you convert to an array suggests that it's only going to work with certain container types anyway. If you expect lots of erasing from the middle of the container you might be able to avoid the memory issue by just choosing a different container; list maybe.
If you choose vector, you might find that calling shrink_to_fit is what you want.
Also note that erase has a return value that will point to the (new) location of the element after the erased one.
If you go down the line of returning an iterator to a newly created down-sized version of the container, note that comparing to the original containers end() iterator wouldn't work.
I figured out the segfault problem!
What was going on was that my x.end() was using the size of the array (NOT the capacity), where the size is the number of data elements stored in the array, instead of the capacity which is actually the size of the array. So when it was looking for the end of the array, it was seeing it as numerous elements before the actual end.
Now on to more interesting problems!
Good afternoon , We are trying to make a simple emulation of the Windows memory mapped caching subsystem. We are using several STL data structures.
A STL deque , std::deque<Range> accesses, which holds and records information about the last recently used to the most recently used memory mapped regions.
A STL set, std::set<char *> ranges_pointer which might hold pointers to the elements in the STL deque..
Basically, when we retrieve a pointer to a valid memory mapped region from the STL set , we would like to use that pointer to direcly access the corresponding element deque in O(constant time). Then, we would like to move that deque element to the front of the STL deque so that that subsequent reguests for clusters of memory mapped addreses can be found at the front of the STL deque accesses.
We know from Stack Overflow that the only STL container that guarantees contingous addresses is STL vector. However, every time one moves a element from a STL vector, it takes O(linear) time to shift or memcpy the remaining items into the right location,This could be expensive. In contrast, when you move a element from STL deque, all one has to rearrange the next and prev pointers on both sides of the element that is moved.
We were wondering if one could write a method to access a STL deque element by its address. Although the std::allocator does not guarantee contiguous STL deque adresses, perhaps we could use a custom memory pool allocator to get a chunk of contiguous addresses.
Also, do BOOST or other C++ frameworks implement contiguous doubly linked lists which offer random access just like STL deque. The class Range holds all the essential information about every cached memory mapped region, The class Range is stored in the the std::deque accessess member variable. Thank you. The class Range is shown below:
class Range {
public:
explicit Range(int item){
mLow = item;
mHigh = item;
mPtr = 0;
mMapPtr = 0;
}
Range(int low, int high, char* ptr = 0,char* mapptr = 0,
int currMappedLength = 0){
mLow = low;
mHigh = high;
mPtr = ptr;
mMapPtr = mapptr;
mMappedLength = currMappedLength;
}
Range(void){
mLow = 0;
mHigh = 0;
mPtr = 0;
mMapPtr = 0;
}
~Range(){
}
bool operator<(const Range& rhs) const{
return mHigh < rhs.mHigh;
}
int low() const { return mLow; }
int high() const { return mHigh; }
char* getMapPtr() const { return mMapPtr; }
int getMappedLength() const { return mMappedLength; }
private:
int mLow; // beginning of memory mapped region
int mHigh; // end of memory mapped region
char* mMapPtr; // return value from MapViewOfFile
int mMappedLength; // length of memory mapped region
}; // class Range
Rather than using a set to hold the addresses, how about a map that contains the address and an iterator into the deque?
Note that moving an element from the middle of a deque to the beginning or end is going to be no faster than doing it for a vector. You might want to think about using a list.