基于Spark的犯罪预警分析系统的设计与实现

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1、目录1绪论································································································11.1研究背景及选题意义··································································11.1.1研究背景·········································································11.1.2选题意义······················

2、···················································21.2国内外研究现状········································································21.2.1多源异构数据处理·····························································21.2.2大数据Spark计算引擎························································31.2.3犯罪预测··

3、·······································································31.3研究内容与本文结构··································································42相关理论及运用技术···········································································52.1大数据技术··················································

4、·····························52.1.1Hadoop生态圈···································································52.1.2Spark技术栈·····································································62.1.3Elastic技术栈····································································62.2机器学习·········

5、·········································································62.2.1经典算法·········································································72.2.2算法评价·········································································92.3其他相关技术··············································

6、·····························92.3.1Kafka消息总线································································102.3.2WebSocket技术·······························································102.3.3可视化技术····································································102.4本章小结·················

7、·······························································113犯罪预警分析系统需求分析································································123.1业务现状分析·········································································123.