What optimization techniques can be suggested for improving the slow query performance on 3 million records?

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Indexing - Ensure that the tables involved in the slow queries have the appropriate indexes. This will allow the database to access the relevant data more quickly.

Query Optimization - Use Explain to analyze the queries and optimize them. This can include re-writing queries, using sub-queries where appropriate, and reducing the number of table joins.

Partitioning - Partitioning allows the database to break large tables into smaller, more manageable pieces. This allows queries to run faster by reducing the amount of data the database needs to scan.

Caching - Use caching mechanisms such as Memcached or Redis to store frequently accessed data in memory. This can improve query performance by reducing the amount of time required to read the data from disk.

Load Balancing - Load balancing can be used to distribute queries across multiple servers. This will reduce the load on any single database server and improve overall query performance.

Denormalization - Denormalization involves duplicating data in a database to optimize query performance. By duplicating data, the database can access the data more quickly, reducing the time it takes to run queries.

Hardware Upgrades - Consider upgrading the hardware used to run the database. This can include upgrading the CPU, RAM, and storage devices to improve query performance.