10 recommended articles about concurrency

Scenario analysis Here we take the red envelope grabbing scenario as an example. The requirements are as follows: 1. There is a limit on the number of red envelopes. Assume that the number of red envelopes is limited to X. 2. The upper limit of the red envelope amount, assuming that the upper limit of the amount is Y. ​ 3. When users are required to grab red envelopes, they must not exceed the limit of the number of red envelopes X. ​ 4. When users are required to grab red envelopes, they should not exceed the amount Y of the red envelope. 5. Each user can only grab one red envelope at a time. Conventional ideas Here are the most common ideas: 1. When users grab red envelopes, check the number and amount of red envelopes currently issued, and lock them. ​ 2. After checking that the number and amount of red envelopes are normal, the amount of the red envelope is randomly determined by the user. &nbs

1. How to make the project more concurrency? Use ID auto-increment to ensure queuing order

## Introduction: Scenario analysis Here we take the red envelope grabbing scenario as an example. Requirements As follows: Conventional ideas Here are the most common ideas: The advantages and disadvantages of conventional ideas are first the advantages and then the disadvantages. The optimization ideas are analyzed first. Why is the conventional idea slow? Optimization solution Pre-processing of red envelope generation For example, the upper limit of the number of red envelopes is X and the upper limit of the amount is Y. Then, before the event, I insert these X red envelopes into the database and generate serial numbers: HB1, HB2, HB3. . . . HBX So in fact, users only need to go in order...

2. Example codes detailing the three methods of Java fine-grained lock implementation

Introduction: Recently, I encountered some high-concurrency scenarios at work that required locking to ensure the correctness of the business logic. performance, and it is required that the performance should not be greatly affected after locking. The initial idea is to lock through the timestamp, id and other keywords of the data to ensure the concurrency of different types of data processing. The lock granularity provided by Java's own API is too large to meet these needs at the same time, so I wrote a few simple extensions myself... 1. Segmented locks draw on the segmentation idea of ​​concurrentHashMap, first generate a certain number of locks, When used specifically, the corresponding lock will be returned based on the key. This is the simplest of several implementations..

3. [MySQL] Multi-version concurrency control

Introduction: The implementation of most transactional storage engines in MySQL is not a simple row-level lock. Based on the consideration of improving concurrency performance, they generally implement multi-version concurrency control (MVCC) at the same time. Not only MySQL, but other database systems such as Oracle and PostgreSQL also implement MVCC, but their implementation mechanisms are different because there is no unified standard for MVCC. MVCC can be considered a variant of row-level locking, but it avoids locking operations in many cases, so the overhead is lower. Although the implementation mechanisms are different, most of them implement

4. phplock (php process lock) v1.0 beta1

Introduction: PHP does not have built-in lock support in multi-process mode (concurrent web access). After processing some resources, concurrency can easily occur. Sexual issues.

5. Concurrency performance test apache nginx

Introduction:: This article mainly introduces the concurrency performance test apache nginx, students who are interested in PHP tutorials can refer to it.

6. Linux multi-process scalable model exploration

Introduction:: Exploration of Linux multi-process scalable model: Recently, I encountered a requirement at work, hoping that the network framework can dynamically increase or decrease the number of processes. Using a multi-process model can improve service concurrency. The services provided by the cloud platform are multi-tenant, and each user has different needs for concurrency. If the access layer provides services to multiple users at the same time, competition for resources and mutual interference may occur, making problem location and troubleshooting more complex. In order to avoid this problem, one access layer only serves one customer, thus avoiding resource competition and mutual interference. Along with this, the number of access layer deployments will grow significantly. Access layer to

7. "Lock option" function description in the SELECT statement_PHP tutorial

Introduction : Description of the "locking option" function in the SELECT statement. Description of the function of the "locking option" in the SELECT statement SQL Server provides a powerful and complete locking mechanism to help achieve concurrency and high performance of the database system. Users can use SQL Server's

8. Understand the producer-consumer model and its application examples in Python programming

Introduction: The producer-consumer model is generally used to reflect the multi-threaded concurrency of the program. Although Python's multi-threading is controlled by GIL, it can still build a queue to simply reflect the idea of ​​the model. Here we will understand production together. Consumer model and application examples in Python programming:

9. thinkphp nginx php-fpm url rewrite causes 404 exception

Introduction: thinkphp nginx php-fpm url rewrite causes 404 error thinkphp nginx php-fpm url rewrite causes 404 error. Before thinkphp’s system was deployed on apache, considering that nginx is much more powerful than apache in terms of concurrency performance, so in The thinkphp system was redeployed on centos in nginx+php-fpm mode

10. Function Description of "Lock Option" in SELECT Statement

Introduction: Description of the "locking option" function in the SELECT statement. Description of the function of the "locking option" in the SELECT statement SQL Server provides a powerful and complete locking mechanism to help achieve concurrency and high performance of the database system. Users can use SQL Server's

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