Você está se esforçando para melhorar o desempenho da consulta. Como você pode conseguir isso sem perder os prazos do projeto?

Before creating indexes, we need to do some statistics, like which columns the end user uses the most in the WHERE statement from their queries. We can imagine that creating an index is like creating a new subtable where the data is sorted, so if we create a multi-index for each column, then the query must jump into each sub-table to get the data, so this might be expensive. So the solution is to consider using multi-column indexes.

----------------------- ➟ Index Smartly ----------------------- Creating the right indexes is crucial for speeding up query performance. ⤷ Think of an index like a book's table of contents—it helps the database find data without scanning every page. ⤷ Use EXPLAIN plans to understand how queries are executed and identify which columns are frequently used in WHERE clauses, JOIN conditions, or as sort keys. ⤷ Create indexes on these columns to enhance query performance. ⤷ Be careful not to over-index, as this can slow down write operations and consume extra disk space. ⤷ Focus on multi-column indexes that can satisfy multiple queries or partial indexes for specific query patterns.

Primero hay que generar estadísticas de querys pesadas, posterior validar mediante sql plans identificar las querys pesadas y posterior aplicar o indexación si lo requiere o evaluar el uso de JOIN para las subconsultas en caso existan.

To optimize queries, we first need to use smart indexing: check the index in the FK column, use a multi-column index.  Using partition in the table is also a solution to improve query performance. But we need to choose the partition key carefully and make sure to use it most of the time when doing some queries. We can use temporary tables to enhance the query performance as well.

There are multiple approach to achieve a task few of them are following: JOIN's can play a vital role to reduce the execution time of DATABASE query. So, using join's in place of subqueries and for complex calcualtion go for temporary tables. Last but not the least, selective approach (select/work only required attributes) can lead query performance high.

----------------------- ➟ Optimize Queries ----------------------- Optimizing your SQL queries can lead to substantial performance improvements. ⤷ Ensure that you're only selecting the columns you need—retrieving unnecessary data can cause significant overhead. ⤷ Break down complex queries into simpler ones if possible; this can make them easier for the database engine to optimize. ⤷ Use JOIN clauses efficiently and avoid subqueries that can be replaced with JOINs. ⤷ Consider the use of temporary tables to store intermediate results if you're dealing with complex data aggregations. ⤷ Remember, the goal is to reduce the workload on the database so that it can execute queries faster.

----------------------- ➟ Hardware Considerations ----------------------- Sometimes, the bottleneck isn't your query—it's the hardware running your database. ⤷ Ensure your servers have enough RAM to hold frequently accessed data in memory, as disk reads are slower than memory access. ⤷ If you're experiencing disk I/O bottlenecks, consider using faster storage solutions like Solid State Drives (SSDs). ⤷ Check if your database is properly utilizing available CPU cores; parallel query execution can drastically reduce response times for data-intensive operations. ⤷ Be mindful of hardware costs and aim for a balance between performance gains and budget constraints.

Caching can play an important role to increase query performance but it should be beneficial only if it is also update and clear (if it is not used for a specific time period) time to time. There are multiple ways to use caching technique even database technology itself implemented basic caching technique. So, go for it, if you are working on some repeat task.

----------------------- ➟ Leverage Caching ----------------------- Caching is an effective way to improve query performance by temporarily storing results of expensive operations. ⤷ Implement query result caches to avoid recalculating data that doesn't change often. ⤷ Look into object caching within your application layer to store frequently accessed data sets. ⤷ Be aware of the cache invalidation strategy—knowing when to clear and refresh cached data is essential to ensure consistency. ⤷ Use caching judiciously to prevent stale data issues and manage memory usage effectively. ⤷ Proper caching can greatly reduce load times and enhance performance. ⤷ Effective caching strategies improve efficiency and user experience.

Caching is an important technique to improve query performance. Whenever the user requests the data fetch it from the DB and temporarily store it in the cache(for expensive Query operations). Now when another user requests the same data, fetch it from the Cache instead of DB. However, while using caching need to focus on the below details 1. cache time - set result in the optimal amount of time 2. cache data clear - Clear the data whenever the data is updated/deleted. 3. cache key name - need to use the necessary inputs in the key name. Otherwise no.of.cache keys are getting increased. It's also considered as expensive.

----------------------- ➟ Monitor Performance ----------------------- Continuous monitoring of query performance is essential to catch issues before they become critical. ⤷ Use tools that track query execution times, frequency, and resource usage. ⤷ Set up alerts for slow-running queries so you can address them promptly. ⤷ Analyze logs to gain insights into patterns that may indicate the need for further optimization. ⤷ By keeping a close eye on performance metrics, you can proactively make adjustments to maintain optimal query speeds. ⤷ Prevent potential deadline disruptions through regular performance monitoring. ⤷ Continuous monitoring ensures efficient and reliable database operations.

----------------------- ➟ Review Regularly ----------------------- Regular review of your database's performance is key to maintaining and improving query speeds. ⤷ Set aside time for periodic performance audits where you analyze the most resource-intensive queries and look for optimization opportunities. ⤷ As your application evolves, so will the demands on your database—what was once an efficient query may become a bottleneck as data grows or usage patterns change. ⤷ Make review and optimization an ongoing process to ensure your database continues to run efficiently. ⤷ Regular reviews help keep your projects on track and within deadlines. ⤷ Continuous improvement ensures sustained database performance and reliability.

There are several important topics which can be discuss some of them are virtual memory management, page replacement and locks.

1. Remove redundancy data from the DB. 2. Select only necessary data from the table. 3. Avoid using the all the conditions in the query. Instead achieve some of the conditions through code logic