摘要
随着大数据时代的到来,数据出现了爆炸式的增长。这些海量数据的出现,影响了很多现有数据存储、处理和分析系统,其中就包括在网络安全中发挥着重要作用的审计系统。目前的审计系统中使用关系数据库对数据进行存储和处理,由于关系数据库的局限性,使得审计系统无法存储和处理大数据。针对该问题,提出了一种兼容现有系统的大数据存储方法,能够有效的解决大数据存储问题。同时,为了解决大数据(HBase)检索效率低下的问题,提出了一种使用Solr建立二级索引的方法,大大的提高了检索效率,满足了审计系统存储和处理大数据的需求。
With the advent of big data era, there is an explosive growth in data volume. The emergence of massive data directly affects storage, processing and analysis systems of the existing data, including audit system, which plays an important role in network security. The current audit system implements data storage and processing with relational databases. Due to the limitations of relational databases, the audit system is unable to store and process big data. To solve this problem, a big data storage method compatible with the existing system is proposed, thus to effectively solve the problem of big data storage. Meanwhile, in order to solve the low efficiency of HBase retrieval, the method using Solr to establish secondary index is presented, which could greatly raise the retrieval efficiency and satisfy the needs of audit system in storing and processing big data.
出处
《通信技术》
2016年第3期346-351,共6页
Communications Technology
