Managed Query Service Isolating Custom Function Execution
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Solution Overview
Problem
Computing systems for querying large data sets are difficult to implement and maintain, with existing solutions often leading to non-optimal utilization of resources and complexity in configuration and maintenance, especially when dealing with distributed query frameworks and database management systems.
Innovation Solution
A managed query service that isolates the execution of custom functions within queries, using an event-driven computing service to execute functions independently and efficiently, by mapping identified functions to isolated resources and generating query execution plans that optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing clusters with distributed query frameworks are used to query large data sets, then query performance is improved, but system complexity and difficulty of implementation increase
Solution Approach 1:
The patent introduces a managed query service as an intermediary layer between the user and the computing cluster. This service handles query parsing, optimization, and execution plan generation, thereby shielding users from the underlying system complexity while maintaining high query performance through optimized resource utilization across the distributed cluster.
Solution Approach 2:
The managed query service implements automatic query optimization and execution plan generation without requiring user intervention. The system self-adjusts resource allocation, selects optimal execution strategies, and manages the distributed query framework automatically, reducing implementation difficulty while preserving productivity benefits.
2Adaptability or versatility
If custom functions are executed within the query processing system, then query functionality is enhanced, but system security and stability deteriorate due to potential malicious code interference
Solution Approach 1:
The patent segments the query execution environment into isolated function execution contexts. Custom functions are executed in separate, sandboxed environments that are isolated from the core query processing system. This segmentation allows enhanced query functionality through custom functions while preventing malicious code from interfering with system stability or security.
Solution Approach 2:
The system introduces an intermediary execution layer that manages custom function invocation. This intermediary validates, isolates, and controls the execution of custom functions, allowing versatile query functionality while maintaining security boundaries that protect the core system from malicious or erroneous code.
3Productivity
If computing clusters are configured for distributed querying, then resource utilization improves, but configuration and maintenance difficulty increase
Solution Approach 1:
The managed query service implements self-service automation for cluster configuration and resource management. The system automatically configures distributed query frameworks, manages resource allocation across computing nodes, and handles maintenance tasks without requiring manual intervention, thereby achieving optimal resource utilization while eliminating configuration and maintenance difficulties.
Solution Approach 2:
The patent introduces a managed query service as an intermediary that abstracts the complex configuration and maintenance of distributed computing clusters. This service layer handles all configuration, resource allocation, and maintenance operations automatically, allowing users to benefit from optimized resource utilization without facing the operational complexity of managing distributed systems.
4Manufacturing precision
If manual ETL operations are performed to prepare data, then data processing control is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system implements automated ETL (Extract, Transform, Load) operations through the managed query service. Data processing transformations are automatically executed as part of the query execution plan, eliminating manual ETL steps. This automation maintains precise control over data processing while dramatically reducing time consumption and operational complexity.
Data Source
AI summary
The performance of functions included in a query may be isolated from the performance of the query. A query may be received and a function within the query may be identified. Execution of the function may be isolated from the performance of the query. In some embodiments, a remote execution engine or service may perform the function in response to a request invoking performance of the function generated as part of executing a query execution plan for the query. Results from the function may be received and a result for the query provided based on the results of the function.