18055502. Database Query Optimization Via Parameter-Sensitive Plan Selection simplified abstract (Google LLC)
Database Query Optimization Via Parameter-Sensitive Plan Selection
Organization Name
Inventor(s)
Lyric Pankaj Doshi of San Mateo CA (US)
Eugene Brevdo of Mountain View CA (US)
Campbell Bryce Fraser of Redmond WA (US)
Database Query Optimization Via Parameter-Sensitive Plan Selection - A simplified explanation of the abstract
This abstract first appeared for US patent application 18055502 titled 'Database Query Optimization Via Parameter-Sensitive Plan Selection
Simplified Explanation
The abstract describes a method for optimizing database queries by generating multiple query plans and selecting the most efficient one based on a trained model.
- The method receives a database query with parameters.
- It generates multiple query plans with different orders of operations.
- A model is trained using historical database queries.
- The trained model assigns a query plan score to each plan.
- The method selects the query plan with the highest score.
- Finally, the selected query plan is executed to retrieve the requested data blocks.
Potential Applications
- Database optimization: This method can be used in various industries that heavily rely on databases, such as finance, healthcare, e-commerce, and logistics, to improve query performance and enhance overall system efficiency.
Problems Solved
- Inefficient database queries: By generating and selecting the most optimal query plan, this method addresses the problem of slow and inefficient database queries, which can impact system performance and user experience.
Benefits
- Improved query performance: By selecting the most efficient query plan, this method can significantly enhance the speed and responsiveness of database queries, leading to faster data retrieval and improved system performance.
- Enhanced system efficiency: Optimizing database queries can reduce resource consumption, such as CPU and memory usage, resulting in improved overall system efficiency and scalability.
- Better user experience: Faster query execution and improved system performance contribute to a smoother and more responsive user experience, especially in applications that heavily rely on real-time data processing.
Original Abstract Submitted
A method includes receiving a database query requesting a database to conditionally return one or more data blocks. The database is stored on memory hardware in communication with the data processing hardware and the database query includes a plurality of parameters characterizing the database query. The method includes generating a set of query plans. Each query plan in the set of query plans is configured to execute the database query using a different order of operations. The method includes training a model using historical database queries and generating, using the trained model, a query plan score for each query plan in the set of query plans. The method includes selecting, using the query plan score of each query plan in the set of query plans, a query plan from the set of query plans. The method also includes executing the database query using the selected query plan.
