Indexes speed up data retrieval from "summary" of SQL and Relational Theory by C. Date
Indexes are an important concept in databases. An index is a data structure that lets the system find specific rows quickly, without having to examine every row in the table. In other words, an index speeds up data retrieval by providing a shortcut to the desired information. Without an index, the system would have to read every row in a table to find the data we're looking for. This process can be time-consuming and inefficient, especially for large tables with a significant amount of data. By creating an index on one or more columns in a table, we can significantly improve the performance of queries that use those columns in the WHERE clause. When a query is executed, the system can use the index to quickly locate the rows that satisfy the search criteria. This can greatly reduce the amount of disk I/O and CPU processing required to retrieve the data, resulting in faster query performance. It's important to note that indexes come with a trade-off. While they can speed up data retrieval, they also require additional storage space and maintenance overhead. Every time a row is inserted, updated, or deleted in a table, the corresponding index(es) must be updated as well. This can impact the performance of data modification operations, as the system has to maintain the integrity of the indexes along with the table data.- It's a good practice to create indexes on columns that are frequently used in query predicates, such as columns in the WHERE, JOIN, and ORDER BY clauses. Properly designed indexes can significantly improve the performance of queries and enhance the overall efficiency of the database system. However, it's essential to strike a balance between the benefits of indexes and the overhead they introduce, as creating too many indexes can lead to diminishing returns and potentially degrade system performance.
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