Understand core components: Producers publish events to Topics, Consumers subscribe and process events, KafkaBroker manages message storage and delivery; 2. Locally build Kafka: Use Docker to quickly start ZooKeeper and Kafka services, expose port 9092; 3. Java integration Kafka: introduce kafka-clients dependencies, or use SpringKafka to improve development efficiency; 4. Write Producer: configure KafkaProducer to send JSON format order events to orders topic; 5. Write Consumer: Subscribe to o through KafkaConsumer

The core of optimizing front-end build time is to reduce redundant work, improve processing efficiency, utilize caches and select efficient tools. 1. Use TreeShaking and code segmentation reasonably to ensure that it is introduced on demand and dynamic import reduces the packaging volume; 2. Reduce unnecessary loader processing, exclude node_modules, upgrade loaders and relax the scope of Babel translation; 3. Use the caching mechanism to speed up repeated construction, enable Webpack cache, CI cache and use offline installation; 4. Upgrade toolchain, such as using Vite, esbuild or Rollup to improve the construction speed, although there is migration cost, it has significant effect.

The preprocessor directive is a command used in C for precompilation processing, and its main functions include header file inclusion, macro definition and conditional compilation. 1.#include is used to introduce header files, standard libraries, customization is used; 2.#define defines macros to implement text replacement, and it is recommended to use const or constexpr instead; 3. Conditional compilation controls whether the code segment is compiled through #ifdef, #ifndef, etc.; 4. Others such as #undef cancellation of macros, #pragma sets compilation options, #error triggers errors, etc. Rational use can improve cross-platform compatibility and debugging efficiency, but macro usage should be reduced to enhance code maintainability.

Master the core data structure and its applicable scenarios, such as the selection of HashMap and TreeMap, and the expansion mechanism of ArrayList; 2. Practice algorithms from the Java perspective, proficient in double pointer, sliding window, DFS/BFS and other modes and can be clearly implemented; 3. Write clean and robust Java code, pay attention to naming, boundary processing and language features (such as generics and final); 4. Prepare the practical question of "why use Java" and understand the impact of StringBuilder, GC, etc. on performance; maintain practice and clear expression to stand out.

Reading CSV files is commonly implemented in Python using pandas library or csv module. 1. Use pandas to read through pd.read_csv(), return DataFrame, supports specifying parameters such as sep, header, index_col, encoding, na_values, etc., suitable for data analysis; 2. Use the csv module to read line by line through csv.reader or csv.DictReader, the former returns a list, and the latter returns a dictionary, suitable for lightweight or no dependencies of third-party libraries; 3. Frequently asked questions: Use a complete path to avoid path errors, set encoding='gbk' or 'utf-8' to solve Chinese

Use len() to count the total number of elements in the list, such as len([1,2,3,4,5]) to return 5; 2. Use count() to count the number of occurrences of specific elements, such as ['apple','banana','apple'].count('apple') to return 3; 3. Use collections.Counter to count the frequency of each element, such as Counter(['a','b','a']) to output Counter({'a':3,'b':2,'c':1}); 4. Use dictionary to manually count the traversal and get methods to achieve the same effect, such as loop accumulation to obtain {'a':3,'b':2,'c':1}.

The key to optimizing Java program performance lies in the rational selection of data structures and algorithms. 1. Select appropriate collection classes according to the scene, such as frequent access to intermediate elements, use ArrayList, and use LinkedList to operate head or tail, find multi-priority HashMap or HashSet, and avoid thread-safe classes and capacity expansion losses. 2. Avoid repeated calculations, use memory cache results to reduce time complexity. 3. Master efficient sorting search algorithms, such as insertion sorting, counting sorting, binary search, KMP, etc., and select according to data characteristics. 4. Reduce GC pressure, avoid creating objects in loops, use object pools, StringBuilder and use StreamAPI with caution.

The screen resolution determines the clarity. 1080p is suitable for daily use below 24 inches. 1440p or 4K is recommended for better experience over 27 inches. 2. The refresh rate affects the smoothness of the picture. 60Hz is suitable for office work, 144Hz and above is suitable for gaming and dynamic operations. 3. The response time is related to the sharpness of the dynamic picture. 1ms is suitable for competitive games, 4-5ms meets daily and ordinary game needs, and avoids more than 8ms to prevent striking.