Control Node for Subquery Execution in Analytics Continuous Queries
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Solution Overview
Problem
Existing solutions for determining where to execute subqueries in real-time analytics continuous queries in distributed cloud environments fail to optimize performance due to limitations in measuring latency and resource allocation across multiple data centers, especially when computational resources are constrained.
Innovation Solution
A control node and method that monitor properties of data centers and data streams to dynamically determine the optimal computing nodes for executing subqueries, allowing for adaptive redistribution based on performance metrics and resource availability, ensuring efficient execution and minimal latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If subqueries are executed on multiple computing nodes in distributed data centers, then query processing capability is improved, but latency and resource allocation optimization becomes difficult to measure and control
Solution Approach 1:
The patent introduces a control node as an intermediary that coordinates subquery execution across multiple computing nodes. The control node receives the continuous query, determines execution plans, and manages the distribution of subqueries to appropriate computing nodes, thereby simplifying the complexity of measuring and controlling latency across the distributed system.
Solution Approach 2:
The system implements feedback mechanisms where execution results and performance metrics are monitored and used to optimize future query execution decisions. The control node uses feedback from previous executions to make informed decisions about computing node selection and resource allocation, improving latency measurement and control over time.
2Adaptability or versatility
If computational resources are allocated across multiple data centers, then query execution flexibility is improved, but resource constraint management becomes more complex
Solution Approach 1:
The patent segments the continuous query into multiple independent subqueries that can be executed separately on different computing nodes. This segmentation allows the system to manage resource allocation at a finer granularity level, reducing the complexity of managing resources across multiple data centers while maintaining execution flexibility.
Solution Approach 2:
The control node serves multiple functions: it acts as a query receiver, execution plan generator, computing node coordinator, and performance monitor. This multi-functionality consolidates resource allocation management complexity into a single universal component rather than requiring complex coordination across all computing nodes.
3Productivity
If subqueries are dynamically redistributed based on monitoring, then execution efficiency is improved, but system complexity increases
Solution Approach 1:
The control node performs preliminary analysis and planning before executing subqueries. It determines the execution plan and selects appropriate computing nodes in advance based on available information, reducing the need for complex real-time decision-making during execution and simplifying the dynamic redistribution mechanism.
Solution Approach 2:
The system implements dynamic redistribution of subqueries based on monitored performance metrics and changing resource availability. The control node can adaptively reassign subqueries to different computing nodes during execution, optimizing efficiency while managing complexity through centralized control rather than distributed real-time negotiations.
Data Source
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AI summary
It is disclosed a control node (40; 50) capable of deciding in which computing nodes to execute a plurality of subqueries of a real-time continuous query, and a method therefore. The plurality of subqueries are executed (210; 302) in two or more computing nodes and properties of at least one of: the one or more data centers comprising the computing nodes, execution of the plurality of subqueries, and the data streams, are monitored (212; 304). A subquery is selected, after which this is executed (214; 306) in an alternative computing node. Properties are monitored (214, 308) during this second execution, and if monitored properties from this execution indicate an improved performance, the subquery may be transferred (218; 310)to said alternative computing node. It is an advantage that real-time queries may be optimized, by determining in which computing node to execute what subqueries of a query for best performance.