Logging Into Mysql

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 ...

In the development of friends especially and MySQL have contact friends will encounter sometimes MySQL query is very slow, of course, I refer to the large amount of data millions level, not dozens of, the following we take a look at the resolution of the query slow way. -Often find developers looking up statements that are not indexed or limit n, which can have a significant impact on the database, such as a large table of tens of millions of records to scan all, or do filesort, and the database and server IO impact. This is the case above the mirrored library. And ...

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 ...

In our development of the efficiency has been a problem, especially for a lot of large data operations, today we ran into a random query data, at first we may think of the simplest order by RAND () to operate but the efficiency is not flattering ah. Recently, because of the need to study the MySQL random extraction implementation method. For example, to randomly extract a record from the TableName table, the general wording is: SELECT * from TableName ORDER by RAND () LIM ...

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Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

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I joined the LinkedIn company at an exciting time six years ago. From that point on, we cracked down on a single, centralized database and started switching to a special distributed System suite. This is an exciting thing: the Distributed graphics database, the distributed search backend, the Hadoop installation, and the first and second generation key value data stores that we build, deploy, and still run until today. The most rewarding thing we've learned from all of this is that the core of many of the things we build contains a simple idea: log. Sometimes ...