Database Prefetching Using Adjacent Column Access Patterns
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Solution Overview
Problem
Existing database prefetching techniques are inefficient for column-oriented and row-column hybrid storage, as they fail to utilize query predicates and metadata, leading to unnecessary data prefetching and increased computing resource burden.
Innovation Solution
A method that determines sets of adjacent columns accessed by a database query and prefetches data in those columns, optionally processing metadata to identify current and next blocks for efficient data retrieval, thereby optimizing prefetching in row-column hybrid storage systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional database prefetching techniques are used, then query execution can proceed, but unnecessary columns are prefetched into memory, increasing computing resource burden
Solution Approach 1:
The patent extracts and utilizes only the necessary column information from query predicates and projections to determine which columns should be prefetched. By analyzing the query's projection clauses and predicate conditions, the system identifies and extracts specifically the columns that will actually be accessed, excluding unnecessary columns from the prefetching process.
Solution Approach 2:
The patent applies local quality by treating different columns differently based on their relevance to the query. Instead of uniformly prefetching all columns, the system selectively prefetches only those columns that match the query's projection and predicate requirements, optimizing resource allocation based on local (column-specific) needs.
2Productivity
If traditional database prefetching techniques are used, then data can be retrieved, but metadata is not utilized, leading to suboptimal prefetching decisions
Solution Approach 1:
The patent implements feedback by utilizing metadata about columns and data blocks to inform prefetching decisions. The system queries metadata to understand column characteristics, data block structures, and query requirements, then uses this feedback information to dynamically adjust which data blocks and columns should be prefetched, creating a closed-loop optimization system.
3Adaptability or versatility
If row-oriented prefetching techniques are used, then row access patterns are optimized, but column-oriented and row-column hybrid storage systems do not benefit
Solution Approach 1:
The patent achieves universality by designing a prefetching mechanism that works across multiple storage paradigms. The system analyzes query characteristics and adapts its prefetching strategy based on whether the underlying storage is row-oriented, column-oriented, or row-column hybrid, making the same core algorithm universally applicable while optimizing for each storage type's specific access patterns.
Data Source
AI summary
The present disclosure provides systems and methods for prefetching data in databases. One method for prefetching data in a database comprises receiving a database query on the database, determining one or more sets of adjacent columns access by the database query, and for each set of adjacent columns of the one or more determined sets, prefetching data in the adjacent columns.