基于Spark的EAST托卡马克实时数据访问日志分析系统
Real time data access log analysis system of EAST tokamak based on spark
摘要：
EAST装置产生的实验数据越来越大，需要对EAST装置上的MDSplus数据存储服务器进行监控。为了方便对MDSplus服务器上的用户进行管理，需要一个实时监控日志分析系统。该日志分析系统采用的数据处理框架是Spark生态圈中的Spark Streaming框架，其实时流数据来源于MDSplus日志。该框架还使用了Flume和Kafka等框架的日志监控，聚合和分发等关键技术，使MDSplus的海量日志数据处理能力成为可能。该系统可以在第二级处理数千万个未处理的MDSplus日志信息，然后对日志信息进行建模并将其显示在Web上。本文介绍了基于spark的实时数据访问日志分析系统的总体架构的设计与实现。实验结果表明，该系统性能稳定可靠，对聚变实验数据的管理具有重要的应用价值。该系统已设计完成，并将在下一次活动中采用，系统的详细信息将在本文中给出。
英文摘要：
The experiment data generated by the EAST device is getting larger and larger, and it is necessary to monitor the MDSplus data storage server on EAST. In order to facilitate the management of users on the MDSplus server, a real-time monitoring log analysis system is needed. The data processing framework adopted by this log analysis system is the Spark Streaming framework in Spark ecosphere, whose real-time streaming data is derived from MDSplus logs. The framework also makes use of key technologies such as log monitoring, aggregation and distribution with framework likes Flume and Kafka which makes it possible for MDSplus mass log data processing power. The system can process tens of millions of unprocessed MDSplus log information at a second level, then model the log information and display it on the web. This report introduces the design and implementation of the overall architecture of real time data access log analysis system based on spark. Experimental results show that the system is proved to be with steady and reliable performance and has an important application value to the management of fusion experiment data. The system has been designed and will be adopted in the next campaign and the system details will be given in the paper.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
