Improve Mysql Performance Large Database

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MySQL and PostgreSQL: which open source database to choose? Which one is better?

Naresh Kumar is a software engineer and enthusiastic blogger, passionate and interested in programming and new things.   Recently, Naresh wrote a blog, the open source world's two most common database MySQL and PostgreSQL characteristics of the detailed analysis and comparison. If you're going to choose a free, open source database for your project, you may be hesitant between MySQL and PostgreSQL. MySQL and PostgreSQL are free, open source, powerful, and feature-rich databases ...

Optimization of caching parameters for MySQL database performance optimization

In peacetime is asked the most questions about the MySQL database performance optimization issues, so recently intended to write a MySQL database performance optimization of the series of articles, I hope that the junior high level MySQL DBA and other interested in MySQL performance of friends to help. Databases are IO-intensive applications whose primary responsibility is data management and storage. And we know that the time to read a database from memory is the microsecond level, and reading an IO from a common hard disk is at the millisecond level, both ...

Big data improvements for MySQL: Support for NoSQL and Hadoop

When it comes to big data, it has to do with Alibaba. The world's leading E-commerce enterprise, the amount of data processed every day is unmatched by any other company, it is also transforming into a real data company--mysql is an important weapon in the transformation of Alibaba.   A database architect who interviewed Ali, who believes Ali has the best performance of open source MySQL, beyond any relational database and NoSQL. In the 2009, Oracle acquired the copyright of MySQL by acquiring Sun, and the industry began to question the use of Oracle ...

MySQL limit optimization method for large data paging

MySQL optimization is very important. The most common and most needed optimization is limit.   The limit of MySQL brings great convenience to paging, but when the amount of data is large, the performance of limit is reduced dramatically. The same is 10 data select * FROM Yanxue8_visit limit 10000,10 and select * from Yanxue8_visit limit 0,10 is not a quantitative level ...

MySQL vs. MongoDB have a winner.

The initial key value comparison, MongoDB victory faster, and this has always been our goal to give the database system MySQL dragster the speed of the disk as its biggest obstacle, this really can make sense? Let's just make an obstacle, what about the solution? If an obstacle limits your dragster, you can choose to bypass it faster or improve on the computer. For example: Avoid the use of disk, as much as possible memory in lieu of faster disk (such as SSD) in fact, this is not good analogy, because the limit from the disk is like ...

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MySQL database optimization of the specific methods that

The following article is mainly about the specific method of implementing a simple and practical optimization of the MySQL database, as well as what specific steps in the actual operation are worthy of our attention. The following article describes the MySQL database is a simple practical optimization of the specific methods to achieve, including how to conduct regular table analysis and inspection, and how to properly optimize the table on a regular basis, the following is a description of the specific program, I hope in your future Learning will be helpful. 1, regular analysis table and checklist analysis table syntax is as follows: ANAL ...

MySQL database statement optimization principles

1, use the index to traverse the table faster. The index created by default is a non-clustered index, but sometimes it is not optimal. Under non-clustered indexes, the data is physically stored on the data page. Reasonable index design should be based on the analysis and prediction of various inquiries. In general: a. There are a large number of duplicate values, and often range query (>, <,> =, <=) and order by, group by occurred columns, consider the establishment of cluster index; Column, and each column contains duplicate values ​​can be ...

Discussion on database technology in large data age

Today's world is a large data age of the information world, our life, whether life, work, learning are inseparable from the support of information systems. The database is the place behind the information system for saving and processing the final result.   Therefore, the database system becomes particularly important, which means that if the database is facing problems, it means that the entire application system will also face challenges, resulting in serious losses and consequences. Now the word "Big Data age" has become very popular, although it is unclear how the concept landed. But what is certain is that as the internet of things 、...

Inventory: Free database software for open source community

Many business owners with only more than 10 to dozens of employees ask if they don't want to spend thousands or even million to buy a database software and ask if there are any free database software available. In fact, there are a lot of small business owners in this type of enterprise, their company needs a small database software to statistics the company's some product data and the information of the storage, the amount of data is really small. As I've seen before, some small businesses use office-brought access small databases, but still feel less convenient. Here, the editor recommends several open source databases for small business use ...

MySQL statement optimization principles

1, use the index to traverse the table faster. The index created by default is a non-clustered index, but sometimes it is not optimal. Under non-clustered indexes, the data is physically stored on the data page. Reasonable index design should be based on the analysis and prediction of various inquiries. In general: a. A large number of duplicate values, and often range query (>, <,> =, <=) and order by, group by occurred column, consider the establishment of cluster index; b. Column, ...

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