Better Big Data Store for Real-Time Processing of Modern MRO System Via Transaction Key Groups

现代MRO系统的可扩展数据管理策略研究

Received: 7 December 2017

Abstract

Aim. MRO2 system is a data management platform. It has the ability to manage and store all kinds of data in the product's lifecycle, that is both the mass storage capacity and the scalability are required. For the existing big-data stores for MRO2 systemeither only focus on the storage problem, or only do the scalability issue. In this paper, a two-layer data management model is proposed, in which the top layer uses the memory storage for scalability and the bottom layer uses the distributed key-value storage for mass storage. By adding a middle layer of the key group between the application and the KV storage system, the keys for real-time processing are combined to cache in a node. It satisfies the characteristics of the real-time application and improves the dynamic scalability. The present protocol of the dynamic key groups for real-time distributed computation for MRO2 system is explained in detail. And then the protocol for creating and deleting key groups is introduced. The third topic is an implement of a big-data store for supporting MRO2 system. In this topic, the delay times for creating and deleting the dynamic transaction groups to estimation are used. Finally, the experiments to appraise the present method are done. The response time of the present method is quite efficient in comparison with the other methods to be used inbig data storage systems.

摘要

现代MRO系统是对产品全生命周期中各种不同类型数据进行统一管理和存储的数据管理平台，既要具有海量存储的能力，亦需要具有可扩展性。而现存的MRO系统，要么只关注存储问题，要么只解决可扩展性问题。提出了一种二层数据管理模型，上层利用内存存储解决可扩展性，下层使用分布式键值存储（KV存储）达到海量存储的目的。通过在应用程序和KV存储系统之间添加键分组的中间层，使得实时处理所需要的键被组合起来缓存在一个节点上，既满足了实时应用的特性，又提高了动态可扩展性。首先给出了实时处理键组的数据模型，其次介绍实时处理键组的创建和删除协议，最后提出了支持实时处理键组的海量数据存储系统结构并对系统进行了评价，取得良好的效果。