MySQL uses indexes to speed up querying by creating data structures that allow it to quickly locate rows that match a certain condition.
When a table is created, an index can be defined on one or more columns, and this index is stored separately from the table data. The index is organized in a way that allows for fast lookups based on the values in the indexed column(s).
When a query is executed, MySQL can use the index to quickly identify the relevant rows in the table. This is accomplished by performing a binary search on the index to find the first row that matches the condition, and then using the index to efficiently retrieve all subsequent matching rows.
MySQL can also use indexes for sorting data, as well as for joining tables. In these cases, MySQL will use the index to perform the sort or join, instead of having to scan the entire table(s) to find the relevant data.
It is important to note that not all queries can benefit from indexes, and in some cases, using an index may actually slow down the query. For example, if the indexed column has low selectivity (meaning there are only a few distinct values), using the index may result in more disk I/O and slower performance.
Overall, the implementation of indexes in MySQL involves creating and maintaining data structures that allow for efficient lookups and sorting of table data, ultimately resulting in faster query execution times.
