Snowflake inc. (20240273096). BUILD-SIDE SKEW HANDLING FOR JOIN OPERATIONS simplified abstract
Contents
BUILD-SIDE SKEW HANDLING FOR JOIN OPERATIONS
Organization Name
Inventor(s)
Xinzhu Cai of San Mateo CA (US)
Florian Andreas Funke of San Francisco CA (US)
BUILD-SIDE SKEW HANDLING FOR JOIN OPERATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240273096 titled 'BUILD-SIDE SKEW HANDLING FOR JOIN OPERATIONS
The method described in the abstract involves generating hash values using build-side row data, detecting frequent hash values based on row size, generating hash partitions, and distributing them to hash-join-build instances for join operations.
- Hash values are generated using build-side row data by a hardware processor.
- Frequent hash values are detected based on row size associated with build-side row sets.
- Hash partitions of the build-side row data are generated using the frequent hash value.
- The hash partitions are distributed to corresponding hash-join-build instances for join operations.
Potential Applications: - Database management systems - Data processing and analysis tools - Distributed computing systems
Problems Solved: - Efficient generation and distribution of hash values - Optimized performance in join operations - Scalability in handling large datasets
Benefits: - Improved data processing speed - Enhanced performance in join operations - Scalability for handling big data
Commercial Applications: Title: "Optimized Hash Value Generation for Efficient Join Operations" This technology can be utilized in various industries such as e-commerce, finance, healthcare, and telecommunications for optimizing database operations and improving data processing efficiency.
Prior Art: Researchers can explore prior patents related to hash value generation, distributed computing, and database optimization to understand the existing technologies in this field.
Frequently Updated Research: Researchers can stay updated on advancements in distributed computing, database management, and data processing technologies to enhance the efficiency of hash value generation and distribution.
Questions about Hash Value Generation: 1. How does the method optimize performance in join operations? - The method optimizes performance by efficiently generating hash values and distributing them to hash-join-build instances, reducing processing time and improving scalability.
2. What are the potential applications of this technology beyond database management systems? - This technology can also be applied in data analytics platforms, cloud computing services, and machine learning algorithms to enhance data processing speed and efficiency.
Original Abstract Submitted
a method includes generating, by at least one hardware processor of a first computing node, a plurality of hash values using build-side row data. a frequent hash value of the plurality of hash values is detected based on row size associated with a plurality of build-side row sets including the build-side row data. a plurality of hash partitions of the build-side row data is generated using a build-side row set of the plurality of build-side row sets that includes the frequent hash value. the plurality of hash partitions of the build-side row data is distributed to a corresponding plurality of hash-join-build (hjb) instances associated with a plurality of join operations.
