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Mitigating YARN Container Overhead with Input Splits

机译:减轻纱线容器开销,输入分裂

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We analyze YARN container overhead and present early results of reducing its overhead by dynamically adjusting the input split size. YARN is designed as a generic resource manager that decouples programming models from resource management infrastructures. We demonstrate that YARN's generic design incurs significant overhead because each con- tainer must perform various initialization steps, including authentication. To reduce container overhead without changing the existing YARN framework significantly, we propose leverag- ing the input split, which is the logical representation of physical HDFS blocks. With input splits, we can combine multiple HDFS blocks and increase the input size of each container, thereby enabling a single map wave and reducing the number of containers and their initialization overhead. Experimental results shows that we can avoid recurring container overhead by selecting the right size for input splits and reducing the number of containers.
机译:我们通过动态调整输入分割尺寸来分析纱线容器开销并提出通过动态调整其开销的早期结果。纱线设计为通用资源管理器,该经理从资源管理基础架构中解耦编程模型。我们展示了纱线的通用设计会导致显着的开销,因为每个配置器必须执行各种初始化步骤,包括身份验证。为了减少容器开销而不显着改变现有的纱线框架,我们提出了输入拆分,这是物理HDFS块的逻辑表示。使用输入拆分,我们可以组合多个HDFS块并增加每个容器的输入大小,从而实现单个映射波并减少容器的数量及其初始化开销。实验结果表明,我们可以通过选择输入分裂的正确尺寸并减少容器的数量来避免重复的容器开销。

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