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This article mainly explains "what is the high concurrency of the server and the processing method of big data". The content of the explanation in the article is simple and clear, and it is easy to learn and understand. let's study and learn "what is the processing method of server high concurrency and big data?"

High concurrency solution

When it comes to high concurrency, how does the high concurrency we encounter come about? Have you ever thought about it? Concurrency is nothing more than accessing our server at the same time, the processing capacity of the server reaches the upper limit, the whole program is in a state of high load or even downtime, and there are more database queries or data storage at the same time. So high concurrency processing needs to deal with two core points, one is the web server problem, the other is our big data problem.

The first one: using clustering and distribution

Increase the number of web servers, do web server clusters, and distribute requests to servers with low pressure through load balancing algorithm, so that requests can be answered in the shortest time and avoid affecting the user experience. Cluster distribution is a common way used by most companies.

Cluster: under the premise of multiple server clusters, the function of each server is the same, no matter which server is accessed, which mainly plays a role of diversion.

Distributed: distribute different services to different servers, several servers may be used to process a request, so that the request can be responded quickly, and can be used when distributed and cluster can be used.

The second kind: static page

In our web, not all the data changes all the time, and some pages change very little, so we can store these pages in the cache. If the frequency is high, we can use Ajax to update the data, so we can avoid a large number of users' requests to the database.

The third kind: the separation of application and static resources

At this point, we put our static resources (js,html,css, etc.) on a separate resource server, which can reduce the pressure on our application server.

Fourth: show other server resources to users through reverse proxy

The reverse proxy server is when we normally visit website A, send us the information of website B. This greatly reduces the pressure on our servers. The server directly accessed by the client does not really provide the service. It takes resources from other servers and returns the results to the user.

Big data's treatment plan:

1, use caching

We can put the data in memory to avoid the pressure on the data every time we access the database. At the same time, using cache can also improve query efficiency and shorten query time.

2the optimization of SQL statement

The optimization of sql statements is very important. We can query whatever data we need to avoid unnecessary waste of performance. Sql statement optimization details, in my Mysql database (3)-mysql optimization scheme, have an idea can take a look.

3, database cluster and database table hash

Thank you for your reading. the above is the content of "what is the high concurrency of the server and the processing method of big data". After the study of this article, I believe you have a deeper understanding of the problem of high server concurrency and big data's processing method, and the specific use still needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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