How to achieve efficient deduplication of tens of millions of data through MySQL

When dealing with big data, deduplicated queries are an important task.

This article will introduce some practical tips and best practices to help you achieve efficient deduplication of tens of millions of data through MySQL.

We will start with index design, query optimization, hardware resource utilization, etc., to provide you with comprehensive analysis and guidance.

I. Index design.

1. # Create a suitable index #: -Indexing is the key to improving query performance.

For deduplication queries, it is recommended to create an index on the column that needs to be deduplicated.

For example, if you want to deduplicate emailColumn, you can create a unique index:

     CREATE UNIQUE INDEX idx_unique_email ON users(email);
     

-For compound indexes, multi-column indexes can be created according to query requirements.

For example, if you want to first_nameSumlast_nameTo deduplicate, you can create a composite index:

     CREATE UNIQUE INDEX idx_unique_name ON users(first_name, last_name);
     

2. # Covering Index #: -An overriding index means that the index contains all the columns required by the query.

This can avoid table return operations and improve query efficiency.

For example, if the query only needs idSumemailColumn, you can create the following overriding index:

     CREATE INDEX idx_covering ON users(email) INCLUDE (id);
     

II. Query optimization.

1. # use the DISTINCT keyword #: \n -DISTINCTKeyword is used to return a unique value.

For example, to get the unique emailList, you can use:

     SELECT DISTINCT email FROM users;
     

- For composite column deduplication, multiple columns can be specified:

     SELECT DISTINCT first_name, last_name FROM users;
     

2. # GROUP BY clause #: \n -GROUP BYClauses are also commonly used to deduplicate.

For example, to get the unique emailList, you can use:

     SELECT email FROM users GROUP BY email;
     

- For composite column deduplication, multiple columns can be specified:

     SELECT first_name, last_name FROM users GROUP BY first_name, last_name;
     

3. # Temporary table deduplication #: -For complex de-duplication logic, consider using temporary tables.

First insert the data into the temporary table, and then deduplicate the temporary table.

E.g:

     CREATE TEMPORARY TABLE temp_users AS SELECT * FROM users;
     DELETE t1 FROM temp_users t1 INNER JOIN temp_users t2 WHERE t1.id > t2.id AND t1.email = t2.email;
     SELECT * FROM temp_users;
     

III. Utilization of hardware resources.

1. # Increase memory #: - Increasing the memory of the server can reduce disk I/O operations, thereby improving query performance.

Make sure MySQL has enough memory to cache data and indexes.

2. # use SSD #: - Solid state drives (SSDs) have faster read and write speeds than traditional mechanical hard drives (HDDs).

Using SSD can significantly improve the response time of the database.

3. # Distributed Database #: - For very large-scale datasets, consider using distributed database systems, such as MySQL Cluster or Sharding technology, to distribute data to multiple nodes to improve query performance.

Fourth, practical skills.

1. # Batch processing #: -For tens of millions of data, one-time processing may result in low memory or query timeout.

The data can be processed in batches.

For example, processing 100,000 records at a time:

     SET @batch_size = 100000;
     SET @offset = 0;
     WHILE @offset < (SELECT COUNT(*) FROM users) DO
       SELECT DISTINCT email FROM users LIMIT @batch_size OFFSET @offset;
       SET @offset = @offset + @batch_size;
     END WHILE;
     

2. # Parallel Query #: -Using MySQL's parallel query function can improve query efficiency.

Parallel queries can be enabled in the configuration file:

     [mysqld]
     innodb_thread_concurrency = 8
     

- then use PARALLELPrompt to perform parallel queries:

     SELECT /*+ PARALLEL(4) */ DISTINCT email FROM users;
     

3. # Periodic maintenance #: -Regular maintenance of the database, such as rebuilding indexes, cleaning up fragments, etc., can maintain the performance of the database.

For example, you can use OPTIMIZE TABLECommand:

     OPTIMIZE TABLE users;
     

V. Summary.

Through reasonable index design, query optimization and full utilization of hardware resources, MySQL can effectively improve the performance of de-duplicated queries when processing tens of millions of data.

With these skills, you will be able to easily meet the challenge of big data deduplication.

I hope the content of this article will be helpful to you, so that your data query will no longer be a headache!