Table of contents
1. Application of C/C++ in the era of big data
1.3: C/C++ image processing and computer vision
2. The future development route of C/C++ programmers
1. Application of C/C++ in the era of big data
C/C++ is still a widely used programming language in the era of big data, especially in fields such as machine learning, artificial intelligence, virtual reality, and game development.
The following are some applications of C/C++ in the big data era:
1. Data processing : C/C++ has the characteristics of high performance and efficiency, and is especially suitable for big data processing. The algorithms and data structures involved in big data processing can be implemented in C/C++. These algorithms and data structures can support tasks such as data analysis, data mining, and machine learning.
2. Database : C/C++ can be used for the development of database systems, including relational databases, graph databases, key-value databases, etc. C/C++ can use efficient data structures and algorithms to optimize database query and update operations, thereby improving database performance and throughput.
3. Image processing and computer vision : C/C++ is widely used in the fields of image processing and computer vision. C/C++ can be used to develop image processing algorithms, image conversion, image segmentation, image recognition and other tasks, and can optimize algorithms to improve the speed and efficiency of image processing.
4. Machine learning and artificial intelligence : C/C++ is also widely used in the fields of machine learning and artificial intelligence. C/C++ can be used to develop algorithms such as neural networks, deep learning, and natural language processing, and can use multi-threading and GPU parallel computing to optimize these algorithms.
C/C++ is widely used in the big data era and can support various data processing, database, image processing, computer vision, machine learning and artificial intelligence tasks.
1.1: C/C++ data processing
C/C++ is an efficient programming language commonly used for data processing and algorithm implementation. Here are some common data processing techniques:
Array processing: Arrays can be used to easily process a set of data. You can use a for loop to traverse the array, or use built-in functions to sort and search the array.
String processing: A string in C/C++ is an array of characters. Strings can be processed using the string class or character arrays. Common string processing functions include strcpy, strlen, strcat, etc.
Pointer operations: Pointers are a major feature in C/C++ and can point to any location in memory, including variables, arrays, functions, etc. Pointers can be used for data processing, such as dynamic memory allocation, array traversal, etc.
File operations: C/C++ can read and write files through file streams. Data persistence can be easily performed using file operations, such as reading configuration files, processing large amounts of data, etc.
Data structure: C/C++ supports a variety of commonly used data structures, such as linked lists, trees, graphs, etc. Using data structures can perform data processing more efficiently, such as fast search, sorting, etc. Common data structure libraries include STL, etc.
1.2: C/C++ database
Although C/C++ are not programming languages designed for use with databases, they are widely used to develop database systems. The following are some commonly used C/C++ databases:
1. MySQL: MySQL is a popular open source relational database management system developed using C and C++.
2. SQLite: SQLite is a small, embedded relational database written in C language. It uses a single file to store all data.
3. PostgreSQL: PostgreSQL is another popular open source relational database management system developed using C language and C++.
4. MongoDB: MongoDB is a NoSQL database developed using C++. It performs well when processing big data.
5. Apache Cassandra: Apache Cassandra is a distributed NoSQL database developed using C++. It performs well when processing large amounts of data.
6. Berkeley DB: Berkeley DB is an embedded database developed using C++. It supports key-value pairs and B+ tree data structures.
The above are some commonly used C/C++ databases. They each have their own advantages and applicable scenarios. Developers can choose the appropriate database according to project needs.
1.3: C/C++ image processing and computer vision
1.3.1: Introduction
Image processing: Pixel-level operations in C/C++ work well for image processing. For example, C/C++ can be used to implement image binarization, edge detection, image enhancement and other operations. OpenCV is an open source computer vision library that implements a large number of image processing and computer vision algorithms based on the C/C++ language and is available for developers to use.
2. The future development route of C/C++ programmers
The future development path of C/C++ programmers depends on personal interests and skills, as well as market needs and trends. Here are several possible directions for development:
1. Learn and master the C++ language and STL library in depth, and become a skilled C++ expert. This requires continuous learning and practice, mastering the advanced features and underlying implementation principles of C++, as well as the use of various STL containers and algorithms.
2. Learn and master the modern development methods of C++, such as test-driven development, continuous integration, code refactoring, etc., to improve development efficiency and code quality.
3. Learn and master modern development frameworks and technologies, such as Qt, Boost, OpenGL, etc., for cross-platform development, graphics programming, etc.
4. Learn and master embedded development technologies, such as embedded C++, RTOS, etc., to develop and optimize embedded systems.
5. Learn and master data structures and algorithms for efficient program design and optimization.
6. Learn and master other programming languages and technologies, such as Python, Java, machine learning, artificial intelligence, etc., to expand your skill tree and face future development and innovation.
It should be noted that with the continuous development of software engineering and technological changes, C/C++ programmers need to continuously learn and adapt to new technologies and methods in order to continuously improve their competitiveness and market value.
2.1: Picture guide
