电信科学 ›› 2015, Vol. 31 ›› Issue (10): 165-171.doi: 10.11959/j.issn.1000-0801.2015212

• 运营技术广角 • 上一篇    下一篇

流计算大数据技术在运营商实时信令处理中的应用

董斌1,杨迪1,王铮1,周文红2   

  1. 1 中国电信股份有限公司上海研究院 上海 200122
    2 中国电信集团公司 北京 100032
  • 出版日期:2015-10-20 发布日期:2017-07-21

Steam Computing Analysis and Application on Operator Real-time Signal Big Data Processing

Bin Dong1,Di Yang1,Zheng Wang1,Wenhong Zhou2   

  1. 1 Shanghai Research Institute of China Telecom Co.，Ltd.，Shanghai 200122，China
    2 China Telecom Corporation，Beijing 100032，China
  • Online:2015-10-20 Published:2017-07-21

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被引次数

10

摘要：

基于Hadoop搭建的大数据平台采用离线批处理的方式，无法满足对数据实效性敏感的业务要求。针对运营商动态数据信息开放大数据平台的实时信令处理要求，对流式计算大数据组件进行了分析，介绍了与流计算大数据相关的实时采集、汇聚和处理组件，形成了端到端实时信令处理大数据技术解决方案，并提出了融合批处理和实时计算的大数据平台解决方案，提高了网络信令数据的时效性，为业务创新提供更大空间，带来更多利益。

关键词: 大数据, 流式计算, Storm, 实时信令数据处理

Abstract:

Big data platform based on the Hadoop structures using offline batch processing mode，unable to meet the service requirements for data timeliness.In order to solve the real-time signal processing requirements in operator OIDD（open information of dynamic data）big data platform，the big-data system components of stream computing were discussed，real-time data collecting，distribution and processing components which formed the end-to-end real-time signal processing big data technology solutions were recommended，and the solutions of the OIDD big data platform which integrated batch computing and stream computing were proposed.It will improve the timeliness of the network signaling data and provide more space for business innovation and bring more benefits.

Key words: big data, stream computing, Storm, real-time signal data processing

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