How to improve the performance of this slow query in mysql?

@wilmer.lemke 

There are several steps you can take to improve the performance of a slow query in MySQL:

1. Identify the slow query: Use tools like MySQL slow query logs or query profiling to identify the slowest queries. Analyze the query and understand its execution plan.
2. Indexing: Make sure you have proper indexes on the columns used in the query's WHERE, JOIN, and ORDER BY clauses. Use EXPLAIN to analyze the query execution plan and identify missing indexes.
3. Denormalize the database: If the query involves joining multiple tables and the data is not frequently updated, consider denormalizing the tables. This can help reduce the number of JOIN operations required.
4. Optimize the query: Rewrite the query to use more efficient SQL constructs or use MySQL query hints like STRAIGHT_JOIN to force the optimizer to use a specific join order. Use EXPLAIN to analyze different query rewrites and choose the best one.
5. Partitioning: If your dataset is very large, consider partitioning the table based on a specific criteria (such as date range) to improve query performance. This can help limit the amount of data that needs to be scanned.
6. Configure server settings: Adjust the MySQL server configuration parameters like innodb_buffer_pool_size, query_cache_size, and max_connections to optimize the performance of your queries.
7. Optimize database structure: Analyze the table schema and optimize the data types and storage engines used. For example, using INT instead of VARCHAR for storing numerical data can lead to better performance.
8. Tune hardware: If possible, upgrade your hardware to improve the overall performance of the MySQL server. This could include increasing RAM, using faster disks, or using solid-state drives (SSDs) for storage.
9. Monitor and analyze: Continuously monitor and analyze the performance of your queries using tools like MySQL Workbench, pt-query-digest, or third-party monitoring tools. This can help identify performance bottlenecks and guide further optimization efforts.

Remember to always test the impact of any changes on your test environment before applying them to your production environment.