Recipe-Driven Distributed Data Processing for Tenant-Safe Queries
Solution Overview
Problem
In multi-tenant distributed data systems, developing separate programs for each organization to query their data is costly and inefficient, and allowing tenants to develop their own code poses security risks and resource inefficiencies, as it can lead to unfair resource utilization and access to unauthorized data.
Innovation Solution
Implementing a system where tenant-specific processing instructions, or 'recipes,' are used in conjunction with provider-supplied code to manage data queries, ensuring data security and efficiency by pre-filtering data access and dynamically handling different queries without requiring tenants to develop custom code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate programs are developed for each organization to query their data, then data processing can be customized for each tenant, but development costs increase and the system becomes less efficient
Solution Approach 1:
The patent implements a universal query processing system that can handle multiple tenants' data processing needs through a single platform. The system uses a common infrastructure with configurable parameters to serve different organizations without requiring separate custom programs for each tenant, thereby reducing development costs while maintaining the ability to customize queries through configuration rather than code development.
2Adaptability or versatility
If tenants are allowed to develop their own code for data processing, then specific processing requests can be handled, but security risks increase and resource utilization becomes inefficient
Solution Approach 1:
The patent introduces an intermediary layer between tenants and the data processing system. This intermediary manages and executes queries on behalf of tenants using pre-approved, secure code. The system acts as a mediator that translates tenant-specific processing requests into secure, controlled operations, thereby maintaining data security while still allowing customization of processing logic through configuration rather than direct tenant-coded access.
3Adaptability or versatility
If tenants develop their own code for data processing, then specific queries can be handled, but resource utilization becomes unfair and inefficient
Solution Approach 1:
The patent implements a self-service query management system where tenants can define their processing requirements through configuration parameters rather than custom code development. The system automatically optimizes resource allocation and executes queries efficiently using shared infrastructure. This approach allows tenants to get customized processing while the system maintains efficient resource utilization through centralized management and optimization, preventing any single tenant from monopolizing resources.
Data Source
AI summary
Methods, systems, and devices for data processing within a distributed data system are described. In a multi-tenant distributed data system, a provider may supply executable code for processing data using declarative processing instructions received from a tenant. For example, a tenant may provide tenant-specific processing instructions for a requested set of data. The processing instructions may indicate input information (e.g., a data structure, tenant-specific fields, etc.), transformation information (e.g., from a set of pre-defined transformations), and output information. The provider-supplied code may use the tenant-specific processing instructions to process and generate the requested set of data, where the code may be executed by multiple nodes within the system. As such, the code executed by multiple nodes may utilize the input information, transformation information, and output information from the tenant-specific processing instructions to generate the requested data and provide the data to the tenant.