论文标题
LingBM：用于构建GraphQl服务器的方法的性能基准（扩展版本）
LinGBM: A Performance Benchmark for Approaches to Build GraphQL Servers (Extended Version)
论文作者
论文摘要
GraphQL是一种构建Web API的流行新方法，可使客户能够准确检索所需的数据。鉴于构建GraphQL服务器的工具和技术越来越多，因此越来越需要比较特定方法或技术如何影响GraphQL Server的性能。为此，我们提出了LingBM，这是一种GraphQL性能基准测试，可通过实验研究创建GraphQL Server的各种方法实现的性能。在本文中，我们讨论了基准的设计注意事项，描述其主要组件（数据架构；查询模板；性能指标），并根据定义具体实验相关的统计属性分析基准。此后，我们提出了通过在三种不同用例中应用基准测试获得的实验结果，这证明了LingBM的广泛适用性。
GraphQL is a popular new approach to build Web APIs that enable clients to retrieve exactly the data they need. Given the growing number of tools and techniques for building GraphQL servers, there is an increasing need for comparing how particular approaches or techniques affect the performance of a GraphQL server. To this end, we present LinGBM, a GraphQL performance benchmark to experimentally study the performance achieved by various approaches for creating a GraphQL server. In this article, we discuss the design considerations of the benchmark, describe its main components (data schema; query templates; performance metrics), and analyze the benchmark in terms of statistical properties that are relevant for defining concrete experiments. Thereafter, we present experimental results obtained by applying the benchmark in three different use cases, which demonstrates the broad applicability of LinGBM.
