stl vector insert iterators

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Std::vector<t,allocator>:: insert.

Inserts elements at the specified location in the container.

If after the operation the new size() is greater than old capacity() a reallocation takes place, in which case all iterators (including the end() iterator) and all references to the elements are invalidated. Otherwise, only the iterators and references before the insertion point remain valid.

[ edit ] Parameters

[ edit ] return value, [ edit ] complexity, [ edit ] exceptions.

If an exception is thrown other than by

• the copy constructor of T ,
• the copy assignment operator of T ,
• any InputIt operation,

these functions have no effect ( strong exception safety guarantee ).

[ edit ] Defect reports

The following behavior-changing defect reports were applied retroactively to previously published C++ standards.

[ edit ] See also

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std::vector:: insert

Inserts elements at specified position in the container.

Causes reallocation if the new size() is greater than the old capacity() .If the new size() is greater than capacity() , all iterators and references are invalidated. Otherwise, only the iterators and references after the added element are invalidated. Past-the-end iterator is also invalidated.

[ edit ] Parameters

[ edit ] return value.

1-2) iterator pointing to the inserted value

3) iterator pointing to the first element inserted, or pos if count == 0 .

4) iterator pointing to the first element inserted, or pos if first == last .

5) iterator pointing to the first element inserted, or pos if ilist is empty.

[ edit ] Complexity

1-2) Constant plus linear in the distance between pos and end of the container.

3) Linear in count plus linear in the distance between pos and end of the container.

4) Linear in std:: distance ( first, last ) plus linear in the distance between pos and end of the container.

5) Linear in ilist. size ( ) plus linear in the distance between pos and end of the container.

[ edit ] See also

std::vector:: insert

Inserts elements at the specified location in the container.

Causes reallocation if the new size() is greater than the old capacity() . If the new size() is greater than capacity() , all iterators and references are invalidated. Otherwise, only the iterators and references before the insertion point remain valid. The past-the-end iterator is also invalidated.

Return value

If an exception is thrown when inserting a single element at the end, and T is CopyInsertable or std::is_nothrow_move_constructible<T>::value is true , there are no effects (strong exception guarantee).

• <cassert> (assert.h)
• <cctype> (ctype.h)
• <cerrno> (errno.h)
• C++11 <cfenv> (fenv.h)
• <cfloat> (float.h)
• C++11 <cinttypes> (inttypes.h)
• <ciso646> (iso646.h)
• <climits> (limits.h)
• <clocale> (locale.h)
• <cmath> (math.h)
• <csetjmp> (setjmp.h)
• <csignal> (signal.h)
• <cstdarg> (stdarg.h)
• C++11 <cstdbool> (stdbool.h)
• <cstddef> (stddef.h)
• C++11 <cstdint> (stdint.h)
• <cstdio> (stdio.h)
• <cstdlib> (stdlib.h)
• <cstring> (string.h)
• C++11 <ctgmath> (tgmath.h)
• <ctime> (time.h)
• C++11 <cuchar> (uchar.h)
• <cwchar> (wchar.h)
• <cwctype> (wctype.h)

Containers:

• C++11 <array>
• <deque>
• C++11 <forward_list>
• <list>
• <map>
• <queue>
• <set>
• <stack>
• C++11 <unordered_map>
• C++11 <unordered_set>
• <vector>

Input/Output:

• <fstream>
• <iomanip>
• <ios>
• <iosfwd>
• <iostream>
• <istream>
• <ostream>
• <sstream>
• <streambuf>

Multi-threading:

• C++11 <atomic>
• C++11 <condition_variable>
• C++11 <future>
• C++11 <mutex>
• C++11 <thread>
• <algorithm>
• <bitset>
• C++11 <chrono>
• C++11 <codecvt>
• <complex>
• <exception>
• <functional>
• C++11 <initializer_list>
• <iterator>
• <limits>
• <locale>
• <memory>
• <new>
• <numeric>
• C++11 <random>
• C++11 <ratio>
• C++11 <regex>
• <stdexcept>
• <string>
• C++11 <system_error>
• C++11 <tuple>
• C++11 <type_traits>
• C++11 <typeindex>
• <typeinfo>
• <utility>
• <valarray>
• vector<bool>
• vector::~vector
• vector::vector

member functions

• vector::assign
• vector::back
• vector::begin
• vector::capacity
• C++11 vector::cbegin
• C++11 vector::cend
• vector::clear
• C++11 vector::crbegin
• C++11 vector::crend
• C++11 vector::data
• C++11 vector::emplace
• C++11 vector::emplace_back
• vector::empty
• vector::end
• vector::erase
• vector::front
• vector::get_allocator
• vector::insert
• vector::max_size
• vector::operator[]
• vector::operator=
• vector::pop_back
• vector::push_back
• vector::rbegin
• vector::rend
• vector::reserve
• vector::resize
• C++11 vector::shrink_to_fit
• vector::size
• vector::swap

non-member overloads

• relational operators (vector)
• swap (vector)

std:: vector

Container properties, template parameters, member types, member functions, non-member function overloads, template specializations.

21.3 — STL iterators overview

An Iterator is an object that can traverse (iterate over) a container class without the user having to know how the container is implemented. With many classes (particularly lists and the associative classes), iterators are the primary way elements of these classes are accessed.

An iterator is best visualized as a pointer to a given element in the container, with a set of overloaded operators to provide a set of well-defined functions:

• Operator* -- Dereferencing the iterator returns the element that the iterator is currently pointing at.
• Operator++ -- Moves the iterator to the next element in the container. Most iterators also provide Operator-- to move to the previous element.
• Operator== and Operator!= -- Basic comparison operators to determine if two iterators point to the same element. To compare the values that two iterators are pointing at, dereference the iterators first, and then use a comparison operator.
• Operator= -- Assign the iterator to a new position (typically the start or end of the container’s elements). To assign the value of the element the iterator is pointing at, dereference the iterator first, then use the assign operator.

Each container includes four basic member functions for use with Operator=:

• begin() returns an iterator representing the beginning of the elements in the container.
• end() returns an iterator representing the element just past the end of the elements.
• cbegin() returns a const (read-only) iterator representing the beginning of the elements in the container.
• cend() returns a const (read-only) iterator representing the element just past the end of the elements.

It might seem weird that end() doesn’t point to the last element in the list, but this is done primarily to make looping easy: iterating over the elements can continue until the iterator reaches end(), and then you know you’re done.

Finally, all containers provide (at least) two types of iterators:

• container::iterator provides a read/write iterator
• container::const_iterator provides a read-only iterator

Lets take a look at some examples of using iterators.

Iterating through a vector

This prints the following:

Iterating through a list

Now let’s do the same thing with a list:

This prints:

Note the code is almost identical to the vector case, even though vectors and lists have almost completely different internal implementations!

Iterating through a set

In the following example, we’re going to create a set from 6 numbers and use an iterator to print the values in the set:

This program produces the following result:

Note that although populating the set differs from the way we populate the vector and list, the code used to iterate through the elements of the set was essentially identical.

Iterating through a map

This one is a little trickier. Maps and multimaps take pairs of elements (defined as a std::pair). We use the make_pair() helper function to easily create pairs. std::pair allows access to the elements of the pair via the first and second members. In our map, we use first as the key, and second as the value.

This program produces the result:

Notice here how easy iterators make it to step through each of the elements of the container. You don’t have to care at all how map stores its data!

Iterators provide an easy way to step through the elements of a container class without having to understand how the container class is implemented. When combined with STL’s algorithms and the member functions of the container classes, iterators become even more powerful. In the next lesson, you’ll see an example of using an iterator to insert elements into a list (which doesn’t provide an overloaded operator[] to access its elements directly).

One point worth noting: Iterators must be implemented on a per-class basis, because the iterator does need to know how a class is implemented. Thus iterators are always tied to specific container classes.

Azure Cosmos DB Conf 2024: Accelerating Innovation in AI and Data

May 13th, 2024 0 1

The fourth annual Azure Cosmos DB Conf, held on April 16, 2024, was an exciting event for developers, product managers and C-Suite executives focused on the cutting-edge of cloud data management and AI-driven applications. Featuring a comprehensive lineup of talks and discussions, the conference provided first-hand insights into leveraging Azure Cosmos DB for building the next generation of AI applications.

Having a great guide to navigate the show is always helpful, but in our case we had two!. The event hosts, Estefani Arroyo and Tara Bhatia , kept the audience engaged, enriching the conference with real-time interactions and comments pulled from social media and live YouTube chat streams.

Led by Kirill Gavrylyuk, VP of Azure Cosmos DB , the conference kicked off with a special opening keynote that not only spotlighted new features and advancements in Azure Cosmos DB but also showcased how companies like TomTom and Mastercard are using these capabilities to drive significant business innovation and outcomes.

Building an AI automotive assistant with TomTom

During the keynote, Kirill invited Massimiliano Ungheretti , Staff Data Scientist at TomTom, to discuss TomTom’s use of generative AI for their automotive in-car driving experience. Massi shared how TomTom has leveraged Azure Cosmos DB to develop the TomTom Digital Cockpit, an in-vehicle assistant that integrates seamlessly with vehicle infotainment and navigation systems, enabling natural voice interactions that enhance the driving experience.

TomTom is using Azure Cosmos DB to manage the extensive data involved in this project. Azure Cosmos DB provides a flexible, scalable solution that can handle the rapid prototyping and iteration necessary for developing AI-driven applications. For TomTom, Azure Cosmos DB provides the necessary performance and capabilities to manage conversation history, essential for the functionality of the voice assistant, and ensuring context-aware interactions that resemble human conversation.

The discussion also touched on the broader impact of generative AI on programming paradigms, suggesting a shift from traditional coding to more dynamic, language-based development processes. This shift is particularly relevant in the context of AI applications, where the ability to iterate quickly and efficiently is paramount.

Fighting financial fraud at Mastercard with Azure Cosmos DB

Siddique Hamid , VP of Software Engineering, and Neeraj Javia , Director of Software Engineering, at Mastercard shared their insights on using Azure Cosmos DB for their Consumer Clarity platform. This platform plays a crucial role in connecting banks and merchants and providing detailed transaction data to minimize credit card disputes and enhance fraud prevention .

Siddique explained how the platform handles complex, data-intensive operations that must execute within fractions of a second to meet strict service level agreements (SLAs) with customers. The ability of Azure Cosmos DB to support high throughput and maintain high availability makes it an ideal choice for Mastercard’s needs, according to Siddique, particularly in their efforts to detect and prevent fraud effectively.

Neeraj highlighted the technical requirements of their system, which demands reliable performance and scalability across multiple regions. Azure Cosmos DB’s global distribution and multi-region replication capabilities ensure that the Consumer Clarity platform can deliver consistent, quick responses to users worldwide, which is critical for maintaining Mastercard’s reputation for security and reliability.

Azure Cosmos DB Conf Highlights

Generative ai and the next generation of intelligent applications.

The conference featured a variety of sessions aimed at both seasoned developers and newcomers. For instance , James Codella of Microsoft delivered an insightful session titled “ Building Generative AI Apps with Azure Cosmos DB .” The session was rich with demonstrations, showcasing how Azure Cosmos DB can be utilized to enhance Generative AI applications. James highlighted the use of vector search for Retrieval Augmented Generation (RAG), crucial for efficiently retrieving relevant data. He also covered how Azure Cosmos DB handles chat histories and implements semantic caching, critical for maintaining context in AI interactions. Furthermore, James demonstrated the integration with popular orchestration tools like Semantic Kernel and LangChain, underlining Azure Cosmos DB’s adaptability and robust capabilities in supporting complex AI functionalities.

Another standout session was ” NoSQL, YesCosmos: Build that Eventually Consistent Application using Azure Cosmos DB ,” presented by Sr. Lead Cloud Engineer Teena Idnani from JP Morgan Chase. It focused on the principles of building applications with eventual consistency, providing a deep dive into the design strategies and performance optimizations for using Azure Cosmos DB in large-scale, distributed environments.

Handling Rapid Growth with Azure Cosmos DB

Karlo Zatylny , CTO of Portnox Security, led a compelling session titled “ Turning Growing Pains to Growing Wins with Azure Cosmos DB ” where he spoke about the challenges and solutions associated with scaling cloud-native applications rapidly. Karlo shared how Portnox managed to triple its scale within a year by utilizing Azure Cosmos DB. The session detailed the methodologies and tools employed to address scale issues effectively, including strategies for optimizing container management and caching techniques.

Exploring Azure Cosmos DB as a Vector Database

Microsoft MVP Michael John Pena of Playtime Solutions presented “ Azure Cosmos DB as a Vector Database .” This session explored the advanced capabilities of Azure Cosmos DB in managing large-scale vector data, highlighting its low-latency, high-throughput, and global distribution features. Michael provided a comprehensive walkthrough on setting up Azure Cosmos DB as a vector database, including data loading and query execution.

Innovative use cases and customer stories

Several customer stories were also spotlighted, including Rishi Gupta ’s testimonial on why JetBlue opted for Azure Cosmos DB. Rishi emphasized the database service response times and vector database support as key deciding factors.

Michal Calvin , CTO of Kinectify, shared how his team uses Azure Cosmos DB and Azure AI services to combat financial crime in the gaming industry. He explored the intersection of data management and regulatory compliance, illustrating how Azure’s technologies are instrumental in sensitive, high-stakes environments.

Chief Software Architect Craig Courtney and CTO Debasish Biswas from Aware led a session on “ Efficient Data Processing with Azure Cosmos DB .” They explored how Aware leverages Azure Cosmos DB to manage vast streams of messages within their AI/ML-driven data ingestion and enrichment pipeline. The session emphasized the implementation of Kubernetes KEDA auto-scalers, Azure Cosmos DB partitioning, and throughput auto-scaling to enhance performance and efficiency. Additionally, they discussed the use of Azure Cosmos DB change feeds for dynamic data management and shared strategies for optimizing costs in a high-volume data environment.

Closing thoughts

Azure Cosmos DB Conf 2024 highlighted how Azure Cosmos DB is being used to build the applications of today and tomorrow, with a focus on generative AI apps that are transforming customer and developer experiences. The conference, as every year, also fostered a sense of community among Azure Cosmos DB developers and those looking to take their apps to the next level with Azure cloud-scale data. The event demonstrated Microsoft’s commitment to continuously evolving its services to meet the demands of modern application development in the era of AI.

For those who missed the live event, all sessions are available on-demand at Azure Cosmos DB Conference Videos .

Watch our video highlight reel to catch up on the key moments from this year’s conference: Azure Cosmos DB Conf 2024 Highlights .

Join us next year for another exciting chapter in cloud data management and AI innovation at Azure Cosmos DB Conf 2025!

About Azure Cosmos DB 

Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra. Try Azure Cosmos DB for free here. To stay in the loop on Azure Cosmos DB updates, follow us on X , YouTube , and LinkedIn .

Jay Gordon Senior Program Manager, Azure Cosmos DB

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• Standard Template Library
• STL Priority Queue
• STL Interview Questions
• STL Cheatsheet
• C++ Templates
• C++ Functors
• C++ Iterators

Vector in C++ STL

• Initialize a vector in C++ (7 different ways)

Commonly Used Methods

• vector::begin() and vector::end() in C++ STL
• vector::empty() and vector::size() in C++ STL
• vector::operator= and vector::operator[ ] in C++ STL
• vector::front() and vector::back() in C++ STL
• vector::push_back() and vector::pop_back() in C++ STL
• vector insert() Function in C++ STL
• vector emplace() function in C++ STL
• vector :: assign() in C++ STL
• vector erase() and clear() in C++

Other Member Methods

• vector max_size() function in C++ STL
• vector capacity() function in C++ STL
• vector rbegin() and rend() function in C++ STL
• vector :: cbegin() and vector :: cend() in C++ STL
• vector::crend() & vector::crbegin() with example
• vector : : resize() in C++ STL
• vector shrink_to_fit() function in C++ STL
• Using std::vector::reserve whenever possible
• vector data() function in C++ STL
• 2D Vector In C++ With User Defined Size
• Passing Vector to a Function in C++
• How does a vector work in C++?
• How to implement our own Vector Class in C++?
• Advantages of vector over array in C++

Common Vector Programs

• Sorting a vector in C++
• How to reverse a Vector using STL in C++?
• How to find the minimum and maximum element of a Vector using STL in C++?
• How to find index of a given element in a Vector in C++

Vectors are the same as dynamic arrays with the ability to resize themselves automatically when an element is inserted or deleted, with their storage being handled automatically by the container. Vector elements are placed in contiguous storage so that they can be accessed and traversed using iterators. In vectors, data is inserted at the end. Inserting at the end takes differential time, as sometimes the array may need to be extended. Removing the last element takes only constant time because no resizing happens. Inserting and erasing at the beginning or in the middle is linear in time.

What is std::vector in C++?

std::vector in C++ is the class template that contains the vector container and its member functions. It is defined inside the <vector> header file. The member functions of the std::vector class provide various functionalities to vector containers.

Syntax to Declare Vector in C++

where the data type is the type of data of each element of the vector. You can remove the std:: if you have already used the std namespace.

Initialization of Vector in C++

We can initialize a vector in the following ways:

1. Initialization Using List

This initialization is done with a declaration. Here, we pass the list of elements to the vector constructor to create a vector with the specified elements.

2. Initialization With a Single Value

This initialization is also done with declaration. Here, we specify the size of the vector and then initialize every element of the vector with the value.

3. Initialization From Another Vector

This initialization is used to create a vector that is an exact copy of other_vec.

Some commonly used member functions of std::vector class are written below:

• begin() – Returns an iterator pointing to the first element in the vector
• end() – Returns an iterator pointing to the theoretical element that follows the last element in the vector
• rbegin() – Returns a reverse iterator pointing to the last element in the vector (reverse beginning). It moves from last to first element
• rend() – Returns a reverse iterator pointing to the theoretical element preceding the first element in the vector (considered as reverse end)
• cbegin() – Returns a constant iterator pointing to the first element in the vector.
• cend() – Returns a constant iterator pointing to the theoretical element that follows the last element in the vector.
• crbegin() – Returns a constant reverse iterator pointing to the last element in the vector (reverse beginning). It moves from last to first element
• crend() – Returns a constant reverse iterator pointing to the theoretical element preceding the first element in the vector (considered as reverse end)
• size() – Returns the number of elements in the vector.
• max_size() – Returns the maximum number of elements that the vector can hold.
• capacity() – Returns the size of the storage space currently allocated to the vector expressed as number of elements.
• resize(n) – Resizes the container so that it contains ‘n’ elements.
• empty() – Returns whether the container is empty.
• shrink_to_fit() – Reduces the capacity of the container to fit its size and destroys all elements beyond the capacity.
• reserve() – Requests that the vector capacity be at least enough to contain n elements.

Element access

• reference operator [g] – Returns a reference to the element at position ‘g’ in the vector
• at(g) – Returns a reference to the element at position ‘g’ in the vector
• front() – Returns a reference to the first element in the vector
• back() – Returns a reference to the last element in the vector
• data() – Returns a direct pointer to the memory array used internally by the vector to store its owned elements.
• assign() – It assigns new value to the vector elements by replacing old ones
• push_back() – It push the elements into a vector from the back
• pop_back() – It is used to pop or remove elements from a vector from the back.
• insert() – It inserts new elements before the element at the specified position
• erase() – It is used to remove elements from a container from the specified position or range.
• swap() – It is used to swap the contents of one vector with another vector of same type. Sizes may differ.
• clear() – It is used to remove all the elements of the vector container
• emplace() – It extends the container by inserting new element at position
• emplace_back() – It is used to insert a new element into the vector container, the new element is added to the end of the vector

The time complexity for doing various operations on vectors is-

• Random access – constant O(1)
• Insertion or removal of elements at the end – constant O(1)
• Insertion or removal of elements – linear in the distance to the end of the vector O(N)
• Knowing the size – constant O(1)
• Resizing the vector- Linear O(N)  

All Member Functions of std::vector

Following is the list of all member functions of std::vector class in C++:

• How to Check if a Vector Contains a Given Element in C++?

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