警務(wù)信息化系統(tǒng)中云存儲平臺的設(shè)計和實現(xiàn)
發(fā)布時間：2018-12-16 20:25
【摘要】：隨著計算機的普及，網(wǎng)絡(luò)技術(shù)的快速發(fā)展，警務(wù)系統(tǒng)開始利用計算機技術(shù)替代一部分的人工作業(yè)，以更好的發(fā)揮警務(wù)系統(tǒng)的作用。警務(wù)信息化系統(tǒng)為警務(wù)人員提供了從警務(wù)信息的登記錄入到統(tǒng)計查詢整個流程的功能。但是當(dāng)前傳統(tǒng)的警務(wù)系統(tǒng)在存儲層面面臨著一些局限：首先警務(wù)數(shù)據(jù)數(shù)量的快速增加，特別是在警務(wù)數(shù)據(jù)聯(lián)網(wǎng)之后，大數(shù)據(jù)量增加了傳統(tǒng)數(shù)據(jù)庫的負(fù)擔(dān)，其次警務(wù)系統(tǒng)的數(shù)據(jù)庫直接建立在服務(wù)器之上，和其他程序共享資源，隔離性差，，再次警務(wù)系統(tǒng)的存儲平臺幾乎沒有擴展性，最后面對大數(shù)據(jù)，傳統(tǒng)數(shù)據(jù)庫難以進(jìn)行存儲和分析，特別是那些非結(jié)構(gòu)化數(shù)據(jù)。 因此本文嘗試從存儲的角度對警務(wù)信息化進(jìn)行優(yōu)化，主要包括以下三個部分： 1.將傳統(tǒng)的數(shù)據(jù)庫建立在新的存儲平臺之上。這個存儲平臺建立在數(shù)據(jù)庫和服務(wù)器硬件中間，利用KVM虛擬化技術(shù)將底層的計算資源統(tǒng)一，然后利用CloudStack管理虛擬化之后的服務(wù)資源。通過創(chuàng)建虛擬機的方式為數(shù)據(jù)庫提供平臺。 2.利用Hadoop建立一個分布式文件系統(tǒng)，所有的大數(shù)據(jù)都可以存儲在HDFS中，然后利用MapReduce進(jìn)行并行化分析。利用Hadoop對大數(shù)據(jù)的支持，為警務(wù)系統(tǒng)提供包括警務(wù)數(shù)據(jù)、警務(wù)程序日志分析等功能。 3.利用Sqoop等工具，將關(guān)系型數(shù)據(jù)庫中的數(shù)據(jù)導(dǎo)入HDFS，然后將HDFS中分析得到的結(jié)果數(shù)據(jù)再次導(dǎo)入關(guān)系型數(shù)據(jù)庫中。以此來實現(xiàn)兩個子系統(tǒng)之間的數(shù)據(jù)遷移功能。 本文從存儲的角度對警務(wù)信息化平臺做了新的設(shè)計和實現(xiàn)，利用云計算的技術(shù)，為存儲平臺增加了可靠性、可擴展性和大數(shù)據(jù)能力。隨著警務(wù)信息化的深入和發(fā)展，這種存儲設(shè)計思路將體現(xiàn)出它的優(yōu)勢。
[Abstract]:With the popularization of computer and the rapid development of network technology, police service system began to use computer technology to replace part of the manual operation, in order to play a better role in the police service system. Police information system provides police officers with the function from the registration of police information to the whole process of statistical inquiry. However, the traditional police system is facing some limitations at the storage level: firstly, the number of police data increases rapidly, especially after the police data network, the large amount of data increases the burden of the traditional database. Secondly, the database of the police service system is built directly on the server, sharing resources with other programs, and the isolation is poor. Again, the storage platform of the police system has almost no expansibility. Finally, facing big data, Traditional databases are difficult to store and analyze, especially unstructured data. Therefore, this paper attempts to optimize the police informatization from the perspective of storage, mainly including the following three parts: 1. The traditional database is built on the new storage platform. The storage platform is based on database and server hardware, and unifies the underlying computing resources by using KVM virtualization technology, and then uses CloudStack to manage the service resources after virtualization. Provides a platform for the database by creating virtual machines. 2. Using Hadoop to build a distributed file system, all big data can be stored in HDFS, and then parallelized by MapReduce. With the support of Hadoop to big data, we can provide police service system with police data, police program log analysis and so on. 3. Using Sqoop and other tools, the data from relational database are imported into HDFS, and the result data from HDFS are imported into relational database again. The function of data migration between two subsystems is realized. In this paper, the police information platform is designed and implemented from the perspective of storage. The cloud computing technology is used to increase the reliability, expansibility and big data ability of the storage platform. With the deepening and development of police information, this storage design will reflect its advantages.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP333
本文編號：2383006
[Abstract]:With the popularization of computer and the rapid development of network technology, police service system began to use computer technology to replace part of the manual operation, in order to play a better role in the police service system. Police information system provides police officers with the function from the registration of police information to the whole process of statistical inquiry. However, the traditional police system is facing some limitations at the storage level: firstly, the number of police data increases rapidly, especially after the police data network, the large amount of data increases the burden of the traditional database. Secondly, the database of the police service system is built directly on the server, sharing resources with other programs, and the isolation is poor. Again, the storage platform of the police system has almost no expansibility. Finally, facing big data, Traditional databases are difficult to store and analyze, especially unstructured data. Therefore, this paper attempts to optimize the police informatization from the perspective of storage, mainly including the following three parts: 1. The traditional database is built on the new storage platform. The storage platform is based on database and server hardware, and unifies the underlying computing resources by using KVM virtualization technology, and then uses CloudStack to manage the service resources after virtualization. Provides a platform for the database by creating virtual machines. 2. Using Hadoop to build a distributed file system, all big data can be stored in HDFS, and then parallelized by MapReduce. With the support of Hadoop to big data, we can provide police service system with police data, police program log analysis and so on. 3. Using Sqoop and other tools, the data from relational database are imported into HDFS, and the result data from HDFS are imported into relational database again. The function of data migration between two subsystems is realized. In this paper, the police information platform is designed and implemented from the perspective of storage. The cloud computing technology is used to increase the reliability, expansibility and big data ability of the storage platform. With the deepening and development of police information, this storage design will reflect its advantages.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP333
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