Adaptive Warehouse Workload Multiplexing

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Solution Overview

Problem

Existing data systems face inefficiencies in executing operations like stored procedures, as they cannot utilize multiple computing resources concurrently, leading to slowed speed and efficiency.

Innovation Solution

The implementation of an adaptive warehouse framework that multiplexes workloads across different workload regions and clusters based on workload types and sizes, allowing for dynamic allocation of computing resources.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If stored procedures are executed in existing data systems, then the operations can be performed, but multiple computing resources cannot be utilized concurrently leading to slowed speed and efficiency

Engineering Contradiction:

Improveexecution speedVSAvoidresource utilization capability

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent segments stored procedures into multiple independent tasks that can be executed in parallel across different computing resources. The workflow engine divides a stored procedure into task components, each assignable to different virtual warehouses or computing nodes, enabling concurrent execution and improving overall productivity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent creates a universal workflow engine that can handle multiple types of operations (stored procedures, ad-hoc queries, ETL jobs) through a common architecture. This multi-functional system allows different workload types to share the same computing infrastructure, improving resource utilization and execution speed simultaneously.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Loss of time

If more computing resources are allocated to execute operations, then execution time can be shortened, but resource underutilization occurs when operations cannot use multiple resources

Engineering Contradiction:

Improveexecution timeVSAvoidresource underutilization

Core Design Contradiction:

Loss of timeVSLoss of energy

Solution Approach 1:

The patent implements dynamic resource allocation where the system automatically adjusts the number and type of computing resources based on the specific operation being executed. The workflow engine monitors task progress and dynamically assigns or releases virtual warehouses, ensuring optimal resource utilization without waste while minimizing execution time.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback mechanisms where execution performance data is collected and used to optimize future resource allocation. The workflow engine learns from past execution patterns to pre-allocate appropriate computing resources, reducing both execution time and avoiding resource underutilization through data-driven decisions.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250190240A1Adaptive warehouses

Publication Date: 2025.06.12 SNOWFLAKE INC

AI summary

Techniques for providing adaptive warehouses in a multi-tenant data system are described. The workloads for the account can be multiplexed in the adaptive warehouse environment. Warehouse endpoints in a warehouse layer can be defined for an account in the multi-tenant data system. A compute layer for the account can be divided into workload regions, where each workload region corresponds to a different workload type.