hadoop summit tokyo分析的相关内容

文章 2017-03-01 来自：开发者社区

【Hadoop Summit Tokyo 2016】基于Spark的高性能时空轨迹分析

本讲义出自YongHua (Henry) Zeng在Hadoop Summit Tokyo 2016上的演讲，主要分享了基于Spark的高性能时空轨迹分析的相关背景、架构以及技术设计，在技术设计方面主要讲解了大数据平台的设计、数据治理的设计、算法模型以及Spark轨迹计算等内容，最后还对于高性能时空轨迹分析的未来发展进行了展望。

文章 2017-02-27 来自：开发者社区

【Hadoop Summit Tokyo 2016】使用基于Lambda架构的Spark的近实时的网络异常检测和流量分析

本讲义出自Pankaj Rastogi与Debasish Das在Hadoop Summit Tokyo 2016上的演讲，主要分享了网络数据相关知识、网络异常DDoS攻击以及使用基于Lambda架构的Spark的近实时的网络异常检测和流量分析的架构设计，并分享了Trapezium的相关概念。

文章 2017-02-26 来自：开发者社区

【Hadoop Summit Tokyo 2016】上云还是回到服务器：混合分析一瞥

本讲义出自Keith Manthey在Hadoop Summit Tokyo 2016上的演讲，主要分享了关于混合数据分析的两种架构的迁移，对于从服务器迁移到云端和从云端迁回到服务器进行了分析介绍，并且对于数据湖泊的概念进行了介绍。

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开源大数据平台 E-MapReduce

开源大数据平台 E-MapReduce（简称“EMR”）是云原生开源大数据平台，向客户提供简单易集成的Hadoop、Hive、Spark、Flink、Presto、ClickHouse、StarRocks、Delta、Hudi等开源大数据计算和存储引擎服务。

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立即开通

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StarRocks 免费试用

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最佳实践

EMR实时计算实践