Snowflake inc. (20240241883). PLACEMENT OF ADAPTIVE AGGREGATION OPERATORS AND PROPERTIES IN A QUERY PLAN simplified abstract
Contents
PLACEMENT OF ADAPTIVE AGGREGATION OPERATORS AND PROPERTIES IN A QUERY PLAN
Organization Name
Inventor(s)
Bowei Chen of San Bruno CA (US)
Thierry Cruanes of San Mateo CA (US)
Florian Andreas Funke of San Francisco CA (US)
Allison Waingold Lee of San Carlos CA (US)
Jiaqi Yan of Menlo Park CA (US)
PLACEMENT OF ADAPTIVE AGGREGATION OPERATORS AND PROPERTIES IN A QUERY PLAN - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240241883 titled 'PLACEMENT OF ADAPTIVE AGGREGATION OPERATORS AND PROPERTIES IN A QUERY PLAN
The technology described in the patent application analyzes a query plan to identify and remove redundant aggregations, while also inserting adaptive aggregation operators based on aggregation properties to optimize the query plan.
- The technology analyzes query plans to identify redundant aggregations.
- It removes redundant aggregations to improve query performance.
- Adaptive aggregation operators are inserted based on aggregation properties.
- The modified query plan is provided with the inserted adaptive aggregation operators.
Potential Applications: - Database management systems - Data analytics platforms - Business intelligence tools
Problems Solved: - Improving query performance by optimizing aggregation operations - Reducing redundant aggregations in query plans
Benefits: - Faster query processing - More efficient use of resources - Improved overall system performance
Commercial Applications: Title: "Optimized Query Processing Technology for Enhanced Performance" This technology can be utilized in various industries such as finance, healthcare, e-commerce, and more to improve data processing and analytics capabilities, leading to better decision-making and operational efficiency.
Questions about Optimized Query Processing Technology: 1. How does the technology identify redundant aggregations in query plans? 2. What are the key benefits of using adaptive aggregation operators in query optimization?
Frequently Updated Research: Stay updated on the latest advancements in query optimization techniques and technologies to further enhance the performance of database systems and data analytics platforms.
Original Abstract Submitted
the subject technology receives a query plan, the query plan comprising a set of query operations, the set of query operations including at least one aggregation and at least one join operation. the subject technology analyzes the query plan to identify an aggregation that is redundant. the subject technology removes the aggregation based at least in part on the analyzing. the subject technology determines at least one aggregation property corresponding to at least one query operation of the query plan. the subject technology inserts at least one adaptive aggregation operator in the query plan based at least in part on the at least one aggregation property, the at least one aggregation property comprising a set of aggregation properties. the subject technology provides a modified query plan based at least in part on the inserted at least one adaptive aggregation operator in the query plan.
