Scenario: A financial institution manages vast amounts of transaction data and wants to optimize its database for faster query processing. How could clustering contribute to this optimization effort?
- Categorizing transactions by location
- Grouping similar transactions to reduce I/O operations
- Indexing transactions by customer ID
- Sorting transactions by date
Clustering can help optimize the database by grouping similar transactions together. By clustering transactions based on similarities such as transaction type, amount, or customer, it reduces the number of I/O operations required to access relevant data, thus improving query processing speed.
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