Composite Object Writes with Dependency-Aware Execution Plans
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Solution Overview
Problem
Existing systems face inefficiencies and increased latency due to the sequential execution of multiple write operations for composite data objects, which depend on other data in multiple data stores, leading to communication bottlenecks and potential failures.
Innovation Solution
A gateway server optimizes write operations by generating an execution plan based on an object dependency graph, minimizing discrete write requests through parallel execution of dependency objects and coalescing requests, reducing the number of sequential operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple write operations are executed sequentially for composite data objects, then data dependency requirements are satisfied, but system latency increases and processing efficiency decreases
Solution Approach 1:
The system performs preliminary analysis of data dependencies before executing write operations. By constructing a dependency graph and identifying execution orders in advance, the system prepares the optimal execution plan that satisfies all data dependencies while enabling parallel execution of independent operations, thus reducing overall latency without compromising reliability
Solution Approach 2:
The system dynamically adjusts the execution strategy based on the analyzed dependency structure. Instead of fixed sequential execution, the system dynamically determines which operations can be executed in parallel by analyzing the dependency graph, allowing flexible optimization of execution timing while maintaining correct dependency satisfaction
2Reliability
If multiple discrete write requests are generated for composite data objects, then complete data commitment is achieved, but communication overhead and processing complexity increase
Solution Approach 1:
The system merges multiple discrete write requests into a unified execution plan based on the dependency graph analysis. By combining operations that can be executed together and optimizing the overall execution strategy, the system reduces communication overhead and processing complexity while ensuring complete data commitment for all composite data objects
3Productivity
If write operations are executed out-of-order, then parallel execution may be achieved, but write operations may fail due to missing dependency data
Solution Approach 1:
The system performs preliminary construction of a dependency graph that explicitly defines the execution order requirements for all write operations. By analyzing and recording dependencies before execution, the system can safely parallelize independent operations while guaranteeing that dependent operations execute only after their prerequisites are satisfied, thus maintaining high success rate alongside parallel execution
Data Source
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AI summary
This disclosure relates to optimizing write requests based on an object dependency graph. An example method generally includes receiving, from a client device, a write request specifying an object to be written to the data store. A gateway server determines, based on an object dependency graph associated with the specified object and identifying relationships between the specified object and one or more dependency objects, one or more dependency objects to be written to the data store. The gateway server generates a plurality of write requests for the specified object and the one or more dependency objects and generates an execution plan for the plurality of write requests based on the object dependency graph. The gateway server executes the plurality of write requests based on the execution plan.