游戏大数据平台研究与实践

立足于游戏平台数据快速处理需求,构建基于分布式＋关系数据混合多元的大数据处理架构,针对高价值密度的结构化数据采用关系数据处理;大量无序的非结构化数据采用分布式机制处理。两种类型数据实现有序化后,统一交予传统关系数据库构建关系化模型并展示,既能实现关键经营分析数据的高效处理,又能满足无序的日志数据规模化处理需求。通过剖析其总体架构、主要功能和关键技术,从而为其他业务平台大数据分析建设和改造提供借鉴和参考。...

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Bibliographic Details
Published in电信科学 Vol. 30; no. 10; pp. 21 - 26
Main Author 苏洋 刘晓军 唐勇 黄洋
Format Journal Article
LanguageChinese
Published 中国通信学会 01.10.2014
人民邮电出版社有限公司
炫彩互动网络科技有限公司 南京210029%中国电信股份有限公司广东研究院 广州510630
Subjects
大数据
数据挖掘
游戏平台
游戏平台
大数据
数据挖掘
big data
game platform
data mining
Online AccessGet full text
ISSN1000-0801
DOI10.3969/j.issn.1000-0801.2014.10.004

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Summary:立足于游戏平台数据快速处理需求,构建基于分布式＋关系数据混合多元的大数据处理架构,针对高价值密度的结构化数据采用关系数据处理;大量无序的非结构化数据采用分布式机制处理。两种类型数据实现有序化后,统一交予传统关系数据库构建关系化模型并展示,既能实现关键经营分析数据的高效处理,又能满足无序的日志数据规模化处理需求。通过剖析其总体架构、主要功能和关键技术,从而为其他业务平台大数据分析建设和改造提供借鉴和参考。
Bibliography:Su Yang, Liu Xiaojun, Tang Yong, Huang Yang （1. Dazzle Interactive Network Technologies, Nanjing 210029, China; 2. Guangdong Research Institute of China Telecom Co., Ltd., Guangzhou 510630, China）
Based on the game platform data processing needs, the diversified mix of large data processing architecturewas built based on distributed ＋ relational data, for high-value-density structured data using relational data processing;lots of disorderly unstructured data processing was using a distributed mechanism. Two types of data to achieve theorderly were unified handed over to traditional relational database model to build relationships and showed that couldbe achieved through efficient handling of business analysis data, but also to meet the scale of disorderly log dataprocessing requirements. The overall architecture, the main features and key technologies were analyzed, so asreference was provided for other business data analysis platform for large construction and renovation.
11-2103/TN
big data, game platform, dat
ISSN:1000-0801
DOI:10.3969/j.issn.1000-0801.2014.10.004