CJOIN Operator for High-Concurrency Data Warehouse Query Optimization
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Solution Overview
Problem
Conventional database systems face inefficiencies and increased latency when handling multiple concurrent queries, leading to 'workload fear' and restricted query capabilities, as they contend for resources and perform random I/O operations, which limits the scalability and effectiveness of data warehouses.
Innovation Solution
The implementation of a high-concurrency query operator (CJOIN) that allows for the concurrent execution of multiple queries through a processor, utilizing a pipeline system with dimension and fact preprocessors, filters, and distributors to optimize resource usage and share work among queries, enabling continuous optimization and efficient processing of highly concurrent workloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional database systems execute multiple concurrent queries independently with separate physical plans, then each query can be processed individually, but resource contention increases and query response time deteriorates significantly
Solution Approach 1:
The patent merges multiple independent query execution plans into a single shared physical plan that serves all concurrent queries. The query processor generates one physical plan that is shared across multiple query objects, allowing concurrent queries to execute together rather than competing for separate resources. This combining approach eliminates redundant operations and reduces resource contention, directly resolving the contradiction between handling multiple queries and maintaining fast response times.
Solution Approach 2:
The shared physical plan acts as a universal execution mechanism that serves multiple different query objects simultaneously. Instead of each query having its own dedicated plan, a single plan performs the work for all concurrent queries, making the execution infrastructure multi-functional. This universality allows the system to maintain high productivity for multiple queries while avoiding the time loss that would result from independent execution.
2Adaptability or versatility
If the database system supports a large number of concurrent queries, then user scalability improves, but resource contention and random I/O operations increase, leading to performance degradation
Solution Approach 1:
The patent combines multiple concurrent query execution paths into a single shared physical plan, allowing the system to support high concurrency without the performance degradation that normally occurs. By merging the execution logic, the system can handle many concurrent queries while avoiding the resource contention and random I/O that would otherwise occur with independent execution plans.
3Ease of operation
If independent physical plans are generated for each query, then query execution can be simplified, but resource usage becomes inefficient and system performance deteriorates under concurrent workloads
Solution Approach 1:
The patent merges the execution of multiple queries into a single physical plan, which improves resource usage efficiency by eliminating redundant operations. While the planning mechanism remains relatively simple (generating one plan instead of many), the combined execution dramatically reduces resource consumption compared to independent plan execution, resolving the contradiction between operational simplicity and resource efficiency.
Data Source
AI summary
In one embodiment, a method includes concurrently executing a set of multiple queries, through a processor, to improve a resource usage within a data warehouse system. The method also includes permitting a group of users of the data warehouse system to simultaneously run a set of queries. In addition, the method includes applying a high-concurrency query operator to continuously optimize a large number of concurrent queries for a set of highly concurrent dynamic workloads.