Top-K Query Heap Materialization for In-Memory Databases
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Solution Overview
Problem
Existing database query optimization methods for top k queries face inefficiencies due to excessive materialization of values during heap sort, leading to resource bottlenecks and poor performance, particularly in in-memory databases using dictionary compression.
Innovation Solution
Implementing selective materialization techniques during top k query operations, where only necessary values are materialized based on comparison results, reducing unnecessary materialization and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all values are materialized during heap sort in top k queries, then complete data is available for accurate comparison and result generation, but resource consumption increases and performance deteriorates
Solution Approach 1:
The patent applies partial action by materializing only the necessary portion of data (first value from first column) during heap sort operations, rather than materializing all values from all columns. This selective materialization reduces resource consumption while maintaining sufficient information for accurate top k query results, directly resolving the contradiction between complete data availability and performance efficiency
2Productivity
If selective materialization is implemented, then resource consumption is reduced and query performance improves, but implementation complexity increases
Solution Approach 1:
The patent segments the materialization process into distinct stages: reading the first value identifier, selectively materializing only the first value from the first column, comparing with heap top element, and conditionally materializing the second value from the second column only when needed. This segmentation of the materialization logic into manageable, conditional steps reduces overall implementation complexity while maintaining query execution efficiency
Data Source
AI summary
In some implementations, there is provided query execution optimization for a top k query that includes in response to a first value being less than a first heap value, selectively materializing a second value corresponding to a second field and inserting the first value and the second value into the heap, and in response to the first value not being less that the first heap value, skipping the first incoming element and proceeding, when available, to another incoming element. Related systems, methods and articles of manufacture are also disclosed.