Abstract
This work is devoted to the analysis and optimization of the application search process using the ElasticSearch software tool. The subject of research is the Elastic platform in the context of data retrieval and analysis. The object is to optimize the search and data analysis process based on this platform. The purpose of this work is to study the possibilities and features of using ElasticSearch to create an effective application search mechanism in large application stores. The main tasks for achieving the goal of the work are defined. Conducted analysis of scientific literature on methods and technologies of data search and analysis based on the Elastic platform. Covers the core components and capabilities of the Elastic platform, including ElasticSearch, Kibana, and LogStash. A comparative analysis of search performance on the Elastic platform and alternative solutions was performed. A test scenario was developed and implemented to evaluate the speed and accuracy of the search using the platform. Implemented service that provides search functionality for applications. The possibilities of integrating the developed service with existing applications and systems for optimal use of its functionality are considered. The developed service was tested using various data sets to confirm its effectiveness and accuracy. The possibilities of scaling and optimization of the developed service for optimal performance when using large volumes of data are determined. The results of using the developed service are compared with similar solutions and conclusions are given regarding its competitiveness. Instructions for using the developed service have been developed and recommendations for its effective implementation in practical scenarios have been provided. The analysis of the obtained results was carried out and conclusions were drawn regarding the effectiveness and practical value of the developed service for solving specific tasks of processing and analyzing large volumes of data using the Elastic platform. Empirical research was conducted using real data sets to evaluate the performance of search on the platform. Explored opportunities to optimize and improve search performance on the platform through configuration and customization. Conclusions are made regarding the effectiveness of search using the Elastic platform and recommendations are provided for its use in specific scenarios
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