Real time data access log analysis system of EAST tokamak based on spark

TL;DR

This paper presents a real-time log analysis system for the EAST tokamak's MDSplus data server using Spark Streaming, enabling efficient processing and visualization of large-scale log data for fusion experiment management.

Contribution

It introduces a novel real-time log analysis system based on Spark Streaming, integrating log monitoring, aggregation, and distribution technologies for large-scale data processing in fusion experiments.

Findings

System processes tens of millions of logs per second

Demonstrates steady and reliable performance

Provides valuable data management insights

Abstract

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.