A data analyst is working with a very large dataset and needs to run a complex query that involves several joins and calculations. The analyst notices that an intermediate result set is being calculated multiple times within the same query, causing significant performance issues. Which of the following query optimization techniques is most suitable for storing this intermediate result to avoid redundant calculations?
Adding an index to every column in the source tables.
Applying all filtering criteria in the final SELECT statement.
Using a temporary table to hold the intermediate result set.
Transposing the source tables before executing the query.
Using a temporary table is the most effective technique in this scenario. Temporary tables are created to hold intermediate results for the duration of a session, which is ideal for complex queries where a result set is needed multiple times. Storing the intermediate data in a temporary table avoids the need for the database to perform the same complex calculations repeatedly, thus improving query performance. While indexing can speed up data retrieval, adding an index to every column can degrade performance and does not solve the issue of re-calculating results. Applying filters late in the process is inefficient. Transposing tables is a data restructuring technique not meant for this type of query optimization.
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What are temporary tables in databases and how do they work?
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Why not create an index on every column instead of using a temporary table?
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When should filters be applied in a query for optimization, and why?