18047872. BUILD-SIDE SKEW HANDLING FOR HASH-PARTITIONING HASH JOINS simplified abstract (Snowflake Inc.)
Contents
BUILD-SIDE SKEW HANDLING FOR HASH-PARTITIONING HASH JOINS
Organization Name
Inventor(s)
Xinzhu Cai of San Mateo CA (US)
Florian Andreas Funke of San Francisco CA (US)
BUILD-SIDE SKEW HANDLING FOR HASH-PARTITIONING HASH JOINS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18047872 titled 'BUILD-SIDE SKEW HANDLING FOR HASH-PARTITIONING HASH JOINS
Simplified Explanation: The patent application describes systems and methods for handling build-side skew in a join operation by partitioning a build-side row set using frequent hash values.
- Detect frequent hash values in a join operation
- Partition build-side row set using frequent hash values
- Distribute partitioned build-side row set to multiple servers for processing
Key Features and Innovation:
- Computing hash values for a join operation
- Sampling hash values to detect frequent ones
- Partitioning build-side row set for efficient processing
- Distributing partitioned row set to multiple servers
Potential Applications: This technology can be applied in database management systems, data processing platforms, and distributed computing environments where join operations are common.
Problems Solved:
- Addressing build-side skew in join operations
- Improving efficiency and performance of hash join build instances
- Enhancing scalability of distributed computing systems
Benefits:
- Increased efficiency in handling skewed data
- Improved performance in join operations
- Scalability in distributed computing environments
Commercial Applications: Optimizing data processing in large-scale databases, improving query performance in data analytics platforms, and enhancing scalability in cloud computing environments.
Prior Art: Researchers can explore prior patents related to hash join operations, distributed computing, and database optimization to understand the existing technology landscape.
Frequently Updated Research: Stay updated on advancements in distributed computing, database optimization, and data processing technologies to leverage the latest innovations in handling build-side skew.
Questions about Handling Build-Side Skew: 1. How does partitioning a build-side row set using frequent hash values improve join operation efficiency? 2. What are the potential challenges in distributing partitioned build-side row sets to multiple servers for processing?
Original Abstract Submitted
Provided herein are systems and methods for handling build-side skew. For example, a method includes computing a plurality of hash values for a join operation. The join operation uses a corresponding plurality of row sets. The plurality of hash values are sampled to detect a frequent hash value. A build-side row set is partitioned using the frequent hash value to generate a partitioned build-side row set. The build-side row set is selected from the plurality of row sets. The partitioned build-side row set is distributed to a plurality of hash-join-build (HJB) instances executing at a corresponding plurality of servers.
