LSM Tree Admission Queue for Multi-Tenant Overload Control
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Solution Overview
Problem
Conventional LSM tree-based storage systems lack effective admission control techniques, leading to resource overload and poor performance for both write and read operations, particularly in distributed database systems, which can cause node failures and degrade system performance.
Innovation Solution
Implement a method and system for controlling admission of transactional operations using an admission queue and LSM tree, where work items are queued and ordered based on priority, tenant identity, and historical consumption, with tokens generated to manage capacity and size, ensuring fair resource allocation and load balancing across tenants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional LSM tree-based storage systems are used without admission control, then write operations can be processed quickly, but the storage system becomes overloaded and operates poorly for both write and read operations
Solution Approach 1:
The admission control system performs preliminary assessment of incoming write operations before they are executed on the LSM tree. It evaluates resource availability, tenant quotas, and system load conditions in advance, accepting or rejecting operations proactively to prevent overload before it occurs, thus maintaining both speed and reliability
Solution Approach 2:
The system continuously monitors LSM tree performance metrics, resource utilization, and operational patterns, using this feedback to dynamically adjust admission decisions. This closed-loop control ensures the system responds to changing conditions while maintaining stable operation and preventing overload
2Reliability
If admission control is implemented to manage resource allocation, then resource overload is prevented, but system complexity increases
Solution Approach 1:
The admission control system is segmented into distinct functional modules: resource monitoring components, tenant quota management components, operational evaluation components, and decision-making components. This modular architecture manages complexity by allowing each component to handle specific aspects of resource management independently
Solution Approach 2:
The admission control system acts as an intermediary layer between incoming write operations and the LSM tree storage engine. This mediator evaluates operations against resource constraints and tenant policies before forwarding them to the storage system, isolating the complexity of resource management from both the client operations and the core storage engine
3Productivity
If multiple tenants share the same cluster nodes, then resource utilization improves, but fairness and isolation between tenants become difficult to maintain
Solution Approach 1:
The system applies differentiated resource allocation and admission policies tailored to each tenant's specific requirements, service level agreements, and historical behavior patterns. Each tenant receives customized resource guarantees and throttling rules, allowing fair coexistence while maintaining overall high resource utilization across the multi-tenant cluster
Data Source
AI summary
Systems and methods for controlling admission of transactional operations for execution are provided. An admission queue configured to control admission to an LSM tree can receive a plurality of work items corresponding to a plurality of tuples. The plurality of work items can be queued in the admission queue for execution based on the plurality of tuples. Indications of a capacity of the LSM tree and a size of each work item of the plurality of work items can be determined. A plurality of tokens configured to enable admission of the plurality of work items to the LSM tree can be generated based on the indications of the capacity of the LSM tree and the size of each work item. Based on the plurality of tokens, a work item of the plurality of work items can be admitted from the admission queue to the LSM tree.