Tips: The following is a brief description of the real java interview questions. If you are interested in reading this article, and those who are about to interview, prepare a pen and paper if possible , and transfer it to your own knowledge. I hope the next interview will be good luck Again and again
Previous Volume: Java Interview Questions [Volume 1]_CsDn.FF's Blog-CSDN Blog
Table of contents
11. What is a database connection pool? Why do you need to use a connection pool?
12. What is an index? What are the common types? How to optimize index?
14. What are current read and snapshot read?
16. How do redis and mysql ensure data consistency?
17. Please briefly describe the request process of the HTTP protocol.
18. How to conduct session management?
19. Please briefly introduce the RESTful API.
20. Others (analysis and thinking)
11. What is a database connection pool? Why do you need to use a connection pool?
Spring Boot's database connection pool configuration can be done by setting the following properties in the application.properties or application.yml files:
Database driver class name: spring.datasource.driver-class-name=xxx
database connection address: spring.datasource.url=xxx
database user name: spring.datasource.username=xxx
database password: spring.datasource.password=xxx
connection pool Maximum number of connections: spring.datasource.max-active=xxx
connection pool minimum number of idle connections: spring.datasource.min-idle=xxx
connection pool maximum waiting time: spring.datasource.max-wait=xxx
connection pool initialization connections: spring.datasource.initial-size=xxx
Among them, xxx is a specific attribute value. By configuring these properties, you can achieve flexible control of the database connection pool and improve system performance and stability; using the connection pool is to improve the management of database connection resources.
12. What is an index? What are the common types? How to optimize index?
An index is a data structure used in a database to speed up data retrieval, and it can help quickly locate and access specific data in a database table.
Common types of indexes are:
- B-tree index: The most common index type, suitable for equivalence queries and range queries.
- Hash index: suitable for equivalent query, the index key is mapped to a unique hash value through a hash function.
- Full-text index: Used for full-text search of text fields, such as finding keywords in article content.
- Spatial index: used for geospatial data types, such as geographic coordinates, geographic regions, etc.
Methods for optimizing indexes include:
- Select appropriate index columns: Select appropriate index columns based on query frequency and query conditions to avoid creating too many or useless indexes.
- Clustered index: Using a clustered index on columns that are frequently queried together can improve query performance.
- Covering index: Create a covering index, so that the query can directly obtain the required data from the index, reducing the access to the data table.
- Regularly update statistical information: Statistical information is very important for the query optimizer to choose an appropriate execution plan. Regularly updating statistical information can keep query performance stable.
- Avoid too many indexes: Too many indexes will increase the cost of writing operations and occupy additional storage space. You need to weigh query performance and frequency of writing operations to determine the number of indexes.
13. What is a gap lock?
Gap lock (Gap lock) is a locking mechanism in the database to prevent other transactions from inserting or updating data in the gap. It is used under Multiversion Concurrency Control (MVCC) or Repeatable Read (RR) isolation levels.
When a transaction holds a lock on a range of data rows, a gap lock locks the range's gap, that is, the space between two existing index keys. This prevents other transactions from inserting new index keys in the gap, thus guaranteeing data consistency and integrity.
The use of gap locks can avoid the problem of phantom reads (Phantom Read), that is, in the same transaction, the same query statement is executed multiple times, and the number of rows in the result set is inconsistent. It can ensure the stability of the query result set and ensure that the data read by the transaction is consistent.
14. What are current read and snapshot read?
Current read and snapshot read are two ways of reading data in the database.
Current reading refers to reading the latest submitted data, and it will get the latest data version when reading. The current read can ensure that the latest data is read, but it may be affected by concurrent transactions, because data modification may occur during the read.
Snapshot read refers to reading the data of a consistent snapshot, which will obtain the data version at the beginning of a transaction when reading. A snapshot read is not affected by concurrent transactions because it reads a definite version of the data.
In some database systems, different isolation levels can be used to control the behavior of current reads and snapshot reads. For example, the READ COMMITTED isolation level can use current reads, while the REPEATABLE READ isolation level can use snapshot reads.
15. What is middleware?
Middleware is a software component or tool used to pass data or messages between different software systems or applications. It can process, transform, filter or enhance data without modifying the source code. Middleware is typically used to handle requests and responses, authentication and authorization, logging, caching, error handling, and more. It provides a flexible and extensible way to organize and manage the interactions between various components in a software system.
16. How do redis and mysql ensure data consistency?
Redis and MySQL are two different databases that have different guarantee mechanisms for data consistency.
For Redis, it is an in-memory key-value storage system commonly used for caching and temporary data storage. In order to ensure data consistency, the following strategies can be adopted:
- Write double-write strategy: After updating MySQL data, update the corresponding data in Redis. This ensures that the data in Redis is consistent with the data in MySQL.
- Cache strategy when reading: When reading data, first query the data from Redis, if it does not exist in Redis, read it from MySQL, cache the query results in Redis, and directly read from Redis next time obtained from . This can reduce the read pressure on MySQL and improve read performance.
- Regular synchronization strategy: regularly synchronize data in MySQL to Redis to maintain data consistency. Periodic synchronization can be achieved using timed tasks or database triggers.
For MySQL, it is a relational database that ensures data consistency through a transaction mechanism. The following methods can be used to ensure data consistency with Redis:
- Transaction operation: When updating Redis and MySQL data, wrap them in a transaction, or all of them are successfully submitted, or all of them are rolled back, to ensure the atomicity and consistency of the data.
- Asynchronous update: Separate Redis update and MySQL update, first update MySQL, and then update Redis. This reduces the latency of synchronization, but there may be brief moments of data inconsistency during the update.
- Monitor changes in MySQL: monitor changes in the database through mechanisms such as MySQL's binlog or triggers, and update the corresponding data in Redis in a timely manner
17. Please briefly describe the request process of the HTTP protocol.
The request process of the HTTP protocol can be simply described as the following steps:
- Client-initiated request: The client (such as a browser) sends an HTTP request to the server. Request includes request method (such as GET, POST, etc.), request header (including some metadata information, such as User-Agent, Accept, etc.) and request body (some additional data, such as form data, files, etc.).
- Server receives request: The server receives the HTTP request sent by the client. The server will parse the information in the request header and determine how to process the request based on information such as the request method and path.
- Server processing request: The server executes corresponding processing logic according to the path and method of the request. This might include reading files, querying databases, executing scripts, and more.
- The server returns a response: After the server has processed the request, it generates an HTTP response. The response includes a response status code (indicating whether the request is successful or an error), a response header (including some metadata information, such as Content-Type, Content-Length, etc.) and a response body (including the actual response data).
- Client receives response: The client receives the HTTP response returned by the server. The client will parse the information in the response header and judge whether the request is successful based on the status code.
- The client processes the response: the client performs corresponding processing according to the information in the response header and the data in the response body, such as rendering an HTML page
18. How to conduct session management?
Conversation management is an important part of ensuring dialogue coherence and contextual understanding. Here are some commonly used session management methods:
- Context Tracking: During a conversation, track conversation history and contextual information to be able to understand and respond to user questions or requests. This can be achieved by recording the conversation history or using specific data structures such as stacks or queues.
- Entity recognition: Identify and extract important entity information in a conversation, such as time, place, person's name, etc. These entity information can help understand user needs and provide more accurate answers or suggestions.
- Intent recognition: Use natural language processing techniques, such as text classification or sequence labeling, to identify user intent. This can help determine what the user wants to express and act accordingly based on different intents.
- Dialogue state management: maintain a dialog state, record the progress and context information of the current dialog. This can be achieved by using a state machine or a state vector so that state information can be updated and accessed as needed during the course of the conversation.
- Scripting Engine: Use predefined scripts or rules to handle specific types of dialogs. These scripts can trigger specific responses or actions based on user input and help guide the conversation.
- Exception Handling: Identify and handle user input that cannot be understood or processed. When encountering a problem that cannot be answered or handled, it can provide a friendly error prompt or transfer to a human customer service for processing.
The above methods can be combined and adjusted according to specific needs and scenarios.
19. Please briefly introduce the RESTful API.
The following blogs, the author thinks that the writing is better, the following is the blog address, copy it to the browser to open and read
Overview of RESTful API_restfulapi_三木-Neil's Blog-CSDN Blog
Personal understanding of RESTFul API - Programmer Peter's Blog - CSDN Blog
20. Others (analysis and thinking)
1. Please share your project experience in Java background development. Including specific tasks, difficulties and solutions.
2. If you need to design a high-concurrency background system, how will you deal with it?
3. What do you think your strengths and weaknesses are, and how can you improve them?
4. What is your understanding of the current position? What do you expect from this job?
5. At work, what should you do if you encounter a situation where you don’t get along well with your colleagues?
I hope the above content can help you prepare for the JAVA school recruitment interview. Good luck!