How does MySQL index cardinality affect query performance?

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

introduction

In database optimization, the role of index is self-evident, and the impact of index cardinality on query performance is an important factor that we cannot ignore. Today we will explore in-depth how the MySQL index cardinality affects query performance. Through this article, you will learn about the concept of cardinality, how it affects the choice of query plans, and how to optimize query performance by adjusting index cardinality in practical applications.

Review of basic knowledge

Let's start from scratch, indexes in MySQL are the key structures used to speed up data retrieval. The index cardinality refers to the number of unique values ​​in the index, which directly affects the decisions of the MySQL optimizer when selecting a query plan. To understand the concept of index cardinality, we need to first review what index is and its role in the database. Indexes are like directories of books, helping us quickly find the data we need. High cardinality indexes mean more unique values, which can lead to higher query performance, while low cardinality indexes may be the opposite.

Core concept or function analysis

Definition and function of index cardinality

Index cardinality refers to the number of different values ​​in the index column. A high cardinality means that the values ​​of the index column are more scattered, while a low cardinality means that the values ​​are more concentrated. For example, if we have a user table, the cardinality of user_id column is high because each user's ID is unique; while the cardinality of gender column is low because there are usually only two values: male or female. The index cardinality directly affects MySQL's decision to select indexes when executing a query.

How it works

When MySQL executes a query, it selects the optimal query plan based on the statistics. Index cardinality is part of these statistics. High cardinality indexing makes it easier for MySQL to find specific rows of data because it can narrow the data more effectively. For example, if we query on a high cardinality index, MySQL can quickly skip irrelevant rows, thereby improving query efficiency.

However, low cardinality indexes may cause MySQL to choose full table scans, because even with indexes, a large number of rows still need to be scanned to find the required data. This is because low cardinality indexes cannot effectively narrow the data range.

 -- Example: High cardinality index CREATE INDEX idx_user_id ON users(user_id);

-- Example: Low cardinality index CREATE INDEX idx_gender ON users(gender);

Example of usage

Basic usage

Let's look at a simple example, suppose we have an order table where order_id is a column with a high cardinality and status is a column with a low cardinality. We can create indexes to speed up queries.

 CREATE TABLE orders (
    order_id INT PRIMARY KEY,
    status VARCHAR(10)
);

CREATE INDEX idx_order_id ON orders(order_id);
CREATE INDEX idx_status ON orders(status);

-- Query uses high cardinality index SELECT * FROM orders WHERE order_id = 12345;

-- Query uses low cardinality index SELECT * FROM orders WHERE status = 'shipped';

In the first query, MySQL prefers the idx_order_id index because it can find specific orders faster. In the second query, MySQL may choose a full table scan because the cardinality of status column is low and the index effect is not obvious.

Advanced Usage

In practical applications, we may encounter some complex query scenarios. For example, the use of joint indexes. In a joint index, the order of index cardinality also affects query performance. Suppose we have a joint index (column1, column2) where the cardinality of column1 is high and the cardinality of column2 is low.

 CREATE INDEX idx_column1_column2 ON table_name(column1, column2);

-- Valid query SELECT * FROM table_name WHERE column1 = 'value1' AND column2 = 'value2';

-- Invalid query SELECT * FROM table_name WHERE column2 = 'value2';

In a valid query, MySQL can use column1 's high cardinality index to narrow the data first, and then use column2 's low cardinality index. In invalid queries, MySQL cannot effectively use joint indexing because it cannot use column2 first to narrow the data scope.

Common Errors and Debugging Tips

We may encounter some common problems when using indexes. For example, index statistics are inaccurate, causing MySQL to select the wrong query plan. At this time, we can debug and optimize through the following methods:

• Use ANALYZE TABLE command to update index statistics.
• Use EXPLAIN command to view query plans and learn how MySQL selects indexes.
• Adjust the order of indexes, especially in joint indexes, to ensure that high cardinality columns are ahead.

 -- Update index statistics ANALYZE TABLE orders;

-- View query plan EXPLAIN SELECT * FROM orders WHERE order_id = 12345;

Performance optimization and best practices

In practical applications, optimizing index cardinality to improve query performance is a continuous process. We can optimize by:

• Update index statistics regularly to ensure that the MySQL optimizer has accurate data.
• When creating indexes, high cardinality columns are given priority, which can improve query efficiency.
• Avoid creating indexes on low-cardinality columns, as it can lead to full table scans, which can actually degrade query performance.

By comparing the performance differences between different methods, we can see the advantages of high cardinality indexing in query performance. For example, in a table with large data volumes, using high cardinality indexes can significantly reduce query time.

 -- Comparison of performance of high cardinality index and low cardinality index SELECT * FROM large_table WHERE high_cardinality_column = 'value';
SELECT * FROM large_table WHERE low_cardinality_column = 'value';

In terms of programming habits and best practices, we should focus on the readability and maintenance of the code. For example, when creating an index, the search should be given a meaningful name, which can be easier to understand when viewing the query plan.

 -- Good naming habits CREATE INDEX idx_user_id ON users(user_id);

In summary, the effect of MySQL index cardinality on query performance is significant. By understanding and optimizing index cardinality, we can significantly improve the database query efficiency, thereby improving the performance of the entire application.

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