With its excellent performance, low cost, and abundant resources, MySQL has become the preferred relational database for most Internet companies. Although the performance is excellent, the so-called "good horse comes with a good saddle", how to use it better has become a required course for development engineers. We often see things like "Proficient in MySQL" and "SQL statement optimization" from job descriptions , "Understand database principles" and other requirements. We know that in general application systems, the read-write ratio is about 10:1, and insertion operations and general update operations rarely cause performance problems. The most encountered ones, which are also the most likely to cause problems, are some complex query operations, so Optimization of query statements is obviously a top priority. Since July 2013, I have been working on the optimization of slow queries in the core business system department of Meituan. There are more than ten systems in total, and I have solved and accumulated hundreds of slow query cases. As the complexity of the business increases, the problems encountered are all kinds of strange, varied and unbelievable. This article aims to explain the principles of database indexing and how to optimize slow queries from the perspective of a development engineer. Thinking selection caused by a slow query  
1. MySQL index principle and slow query optimization
##Introduction: With its excellent performance, low cost, and abundant resources, MySQL has become the preferred relational database for most Internet companies. Although the performance is excellent, the so-called "good horse comes with a good saddle", how to use it better has become a required course for development engineers. We often see things like "Proficient in MySQL" and "SQL statement optimization" from job descriptions , "Understand database principles" and other requirements. We know that in general application systems, the read-write ratio is about 10:1, and insertion operations and general update operations rarely cause performance problems. The most encountered ones, which are also the most likely to cause problems, are some complex query operations, so Optimization of query statements is obviously a top priority.
2. Detailed explanation of the InnoDB index principle of MySQL
Introduction: Abstract: This article introduces the knowledge related to Mysql's InnoDB index, from various trees to index principles to storage details. InnoDB is the default storage engine of Mysql (before Mysql5.5.5 it was MyISAM, document). In the spirit of efficient learning...
3. Analysis and explanation of index principles in mysql database
Introduction: In fact , you can understand the index as a special directory. Microsoft's SQLSERVER provides two types of indexes: clustered index (also known as clustered index, clustered index) and nonclustered index (nonclustered index, also known as non-clustered index, non-clustered index).
4. Introduction to DB2 database performance optimization
##Introduction: For DB2 database, all this is based on a deep understanding of DB2's lock mechanism and concurrency mechanism, index principles, database parameters, optimizer principles, SQL script optimization and other technologies
5.
Detailed analysis of MySQL’s InnoDB index
## Introduction: This article introduces Learn about MySQL's InnoDB index, from various trees to index principles to storage details. InnoDB is the default storage engine of MySQL (it was MyISAM before MySQL5.5.5,
6.
mysql index principle B+/-TreeIntroduction: http://hi.baidu.com/lzpsky/item/70b944dffe4a9e16e1f46f27 Index is for faster data query. The query algorithm is There are many, and there are many corresponding data structures. The commonly used index data structure in databases is generally B+Tree. 1. B-Tree. The official definition of B-Tree is difficult to understand. Let’s give an example:
7. 【Reprint】MySQL directory principle and slow query optimization
# #Introduction: [Reprint] MySQL index principle and slow query optimization MySQL has become the preferred relational database for most Internet companies with its excellent performance, low cost, and abundant resources. Although the performance is excellent, the so-called "a good horse comes with a good saddle" and how to use it better has become a required course for development engineers. We often see
## from the job description. #8. #Introduction: mysql index principle for this SQL: from message where id=1 and name='a' ??mysql last How was the data found? ? Should we first match the index with id=1, then match the index with name=a, and finally merge, or should we judge at the same time? ? http://www.fuzzy.cz/en/articles/basic-principles-of-database-index9.
Do you understand the indexing principles of SQL
Introduction: The previous article roughly summarized the differences between SQL clustered indexes and non-clustered indexes, but see It seems unclear. In this article, I will analyze it again through the index principle. Indexes exist for retrieval, which means that indexes are not necessary for a table. The table index consists of multiple pages, which together form a tree structure, which is what we usually call a B-tree. First
10.
Basic Principles of Oracle Index
Introduction: Oracle provides two methods: reading all rows from the table (i.e. full table scan), or reading one row at a time through ROWID. If you only access 5% of the rows in the big data table and use index[Related Q&A recommendations]:
mysql index- What is the difference in query principles between mysql's range query and multi-value exact query?
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