Author: Clinton Gormley,Zachary Tong
Publisher: "O'Reilly Media, Inc."
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Whether you need full-text search or real-time analytics of structured data—or both—the Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships. If you’re a newcomer to both search and distributed systems, you’ll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you’ll follow a problem-based approach to learn why, when, and how to use Elasticsearch features. Understand how Elasticsearch interprets data in your documents Index and query your data to take advantage of search concepts such as relevance and word proximity Handle human language through the effective use of analyzers and queries Summarize and group data to show overall trends, with aggregations and analytics Use geo-points and geo-shapes—Elasticsearch’s approaches to geolocation Model your data to take advantage of Elasticsearch’s horizontal scalability Learn how to configure and monitor your cluster in production
ER 2018 Workshops Emp-ER, MoBiD, MREBA, QMMQ, SCME, Xi’an, China, October 22-25, 2018, Proceedings
Author: Carson Woo,Jiaheng Lu,Zhanhuai Li,Tok Wang Ling,Guoliang Li,Mong Li Lee
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This book constitutes the refereed proceedings of five workshops symposia, held at the 37th International Conference on Conceptual Modeling, ER 2018, in Xi’an, China, in October 2018. The 42 papers promote and disseminate research on theories of concepts underlying conceptual modeling, methods and tools for developing and communicating conceptual models, techniques for transforming conceptual models into effective implementations, and the impact of conceptual modeling techniques on databases, business strategies and information systems. The following workshops are included in this volume: Emp-ER: Empirical Methods in Conceptual Modeling, MoBiD: Modeling and Management of Big Data, MREBA: Conceptual Modeling in Requirements and Business Analysis, QMMQ: Quality of Models and Models of Quality, SCME: Conceptual Modeling Education.