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14 wrz 2010 · SELECT SUM( CEIL( dlvSize / 100 ) ) as numItems. FROM log. WHERE timeLogged BETWEEN 1000000 AND 2000000. AND user = 'example'</pre>. It takes minutes to finish and i think that the solution would be at the indexes that i'm using. Here is the result of explain:
23 wrz 2024 · Optimize your MySQL database with our comprehensive guide on MySQL Indexes, covering types, benefits, and effective indexing strategies for better performance.
17 cze 2024 · By following best practices such as identifying high-volume queries, choosing appropriate index columns avoiding over-indexing and regularly monitoring and optimizing indexes we can significantly enhance the efficiency and responsiveness of the MySQL database.
4 sty 2023 · Using indexes in MySQL has multiple benefits. The most common are speeding up WHERE conditional queries (with exact match conditions and comparisons), sorting data with ORDER BY clauses more quickly, and enforcing value uniqueness. However, using indexes may degrade peak database performance in some circumstances.
MySQL uses indexes to rapidly locate rows with specific column values. Without an index, MySQL must scan the entire table to find the relevant rows. The larger the table, the slower the search becomes.
3 paź 2010 · The best way to improve the performance of SELECT operations is to create indexes on one or more of the columns that are tested in the query. The index entries act like pointers to the table rows, allowing the query to quickly determine which rows match a condition in the WHERE clause, and retrieve the other column values for those rows.
