| dc.description.abstract | Business competition has become more aggressive these days. Meeting consumer demand is the focus at which every company is aiming nowadays in order to win the competition. In recent years, data mining and big data have become a hot topic. How to extract valuable information from various databases to benefit business, conduct accurate analysis, and predict consumer behavior become critical while big date tools is helpful in all these. The tools can help business develop business strategies, strengthen competitive advantage, and maximize profits.
Although Hadoop, a big data platform, has brought many advantages, such as the scalability and the tolerance of single node failure, it has its disadvantage as well. This research is based on the case study of NoSQL Database HBase, which has been applied in a prominent foundry company in Taiwan. This research systematically studied the problems and tried to find out the factors that affected the system’s efficiency and stability and searched for solutions for each factor, and then evaluated the effectiveness of the solutions for the repeated problems.
The results of this study shows that HBase’s performance and stability will likely be impacted by the factors such as Hadoop platform stability, DataNode xceiver parameter, operation system parameters, the region count of each RegionServer. Also, the row key design will impact the read/write performance as well. This study also found the stability problem of HBase was related to the inappropriate process management. This suggests that to improve HBase’s performance and stability has to be performed not only from system level perspective but also from the management perspective. Through the improvement of management control like consistency of parameter, version control of parameters, deployment processes, change management, enhancing monitoring and emergency management can reduce human error and construct a more stable distributed cluster system.
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