Time-series data is being increasingly generated in real-world applications. To process the massive data with high performance, we have introduced CnosDB, a distributed database tailored for time series to achieve hig...
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ISBN:
(纸本)9789819755745;9789819755752
Time-series data is being increasingly generated in real-world applications. To process the massive data with high performance, we have introduced CnosDB, a distributed database tailored for time series to achieve high writing speed and storage efficiency. To allow the users to seamlessly integrate the superior time series database into their applications, in this paper, we propose Cnos-connector, a generic, easy-to-use, and flexible tool that enables the users to simply interact with CnosDB using the wrapped Python functions. Cnos-connector adapts for Python database API Specification v2.0 (PEP 249), a popular interface framework that has been used by many Python libraries (e.g. Pandas), so that they can be used in conjuction with each other to improve the usability. We plan to demonstrate how the users integrate CnosDB into their applications in various scenarios using Cnos-connector.
The rise of the Internet of Things (IoT) has led to the increasing prevalence of industrial monitoring applications, which is achieved by collecting, managing, and analyzing the time-series data generated by various i...
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ISBN:
(纸本)9789819755745;9789819755752
The rise of the Internet of Things (IoT) has led to the increasing prevalence of industrial monitoring applications, which is achieved by collecting, managing, and analyzing the time-series data generated by various industrial equipments. However, existing monitoring tools are mainly designed for IT scenarios (e.g., dabatase monitoring), but can hardly handle the industrial applications that require processing time-series data significantly larger in volume with lower latency. To address these challenges, we propose iMonitor, a real-time data monitoring system specifically designed for industrial IoT applications. We describe the main features and key techniques of iMonitor, and adopt a real-world blast furnace ironmaking scenario as an example to demonstrate the functionalities of the system.
We propose a novel graph database system that overcomes existing limitations by integrating relational databases, unifying RDF and property graph data models, and incorporating large language models and natural langua...
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ISBN:
(纸本)9789819755745;9789819755752
We propose a novel graph database system that overcomes existing limitations by integrating relational databases, unifying RDF and property graph data models, and incorporating large language models and natural language processing. Graphologue, our system, leveraging openGauss, enhances scalability and performance compared to traditional graph databases. The integration of RDF and property graph models enables flexible data modeling, combining expressiveness and flexibility. We introduce large language models to simplify query generation using natural language, reducing complexity. Additionally, we employ natural language processing to generate graphs from unstructured data, enhancing inclusiveness. Our research aims to advance graph database technology, offering a unified and user-friendly solution for efficient data analysis and querying in interconnected environments.
Since the widespread applications of Internet of Things, the data generated by various devices (e.g., industrial sensors) in real-time is rapidly growing, providing new opportunities by discovering knowledge from thes...
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ISBN:
(纸本)9789819755745;9789819755752
Since the widespread applications of Internet of Things, the data generated by various devices (e.g., industrial sensors) in real-time is rapidly growing, providing new opportunities by discovering knowledge from these data to achieve industrial intelligence. However, the problem of how to efficiently collect, process, and store the massive data generated by a large amount of different devices challenges existing systems. Motivated by this, we develop KTC, a real-time data ingestion system for the Industrial Internet of Things that features many advantages, including high throughput, life-long storage, horizontal scaling, ease of use and extend, and so on. In this paper, we introduce the architecture and key techniques of KTC, and describe the key demonstration scenarios of our system.
In recent years, there has been a notable rise in the application of machine learning to cost estimation for query optimization. Central to an effective cost model are the abilities of accuracy, efficiency, lightness,...
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ISBN:
(纸本)9789819609130;9789819609147
In recent years, there has been a notable rise in the application of machine learning to cost estimation for query optimization. Central to an effective cost model are the abilities of accuracy, efficiency, lightness, and generalizability. However, traditional cost models are based on heuristics thus lack of accuracy. On the other hand, the learned cost models frequently struggle to strike a balance between accuracy and efficiency, with many lacking broad applicability. To combat these challenges, we introduce FAITH, a fast, accurate, and database-agnostic learned cost model. FAITH harnesses data from multiple sources to learn cross-database meta-knowledge. It is then effectively refined, leveraging the unique data information from the target database via an Adapter we developed. Proven through various benchmarks, FAITH consistently showcases its prowess in delivering accurate and robust cost estimations.
Data privacy policy requirements are a quickly evolving part of the data management domain. Healthcare (e.g., HIPAA), financial (e.g., GLBA), and general laws such as GDPR or CCPA impose controls on how personal data ...
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ISBN:
(纸本)9789819755745;9789819755752
Data privacy policy requirements are a quickly evolving part of the data management domain. Healthcare (e.g., HIPAA), financial (e.g., GLBA), and general laws such as GDPR or CCPA impose controls on how personal data should be managed. Relational databases do not offer built-in features to support data management features to comply with such laws. As a result, many organizations implement adhoc solutions or use third party tools to ensure compliance with privacy policies. However, external compliance framework can conflict with the internal activity in a database (e.g., trigger side-effects or aborted transactions). In our prior work, we introduced a framework that integrates data retention and data purging compliance into the database itself, requiring only the support for triggers and encryption, which are already available in any mainstream database engine. In this demonstration paper, we introduce DBCompliant - a tool that demonstrates how our approach can seamlessly integrate comprehensive policy compliance (defined via SQL queries). Although we use PostgreSQL as our backend, DBCompliant could be adapted to any other relational database. Finally, our approach imposes low (less than 5%) user query overhead.
With the ever-increasing amount of data stored and processed and ever-evolving hardware technology, there is not only an ongoing need for testing database management systems but also data-intensive systems in general....
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ISBN:
(纸本)9798400704222
With the ever-increasing amount of data stored and processed and ever-evolving hardware technology, there is not only an ongoing need for testing database management systems but also data-intensive systems in general. Reviving the previous success of nine previous workshops, the goal of the Workshop on Testing databasesystems (DBTest) 2024 is to bring researchers and practitioners from academia and industry together to discuss key problems and ideas related to testing databasesystems and applications. The long-term objective of our efforts is to reduce the cost and time required to test and tune data management and processing products so that users and vendors can spend more time and energy on actual innovations.
Index recommendation and knob tuning are two important database tuners. Despite substantial progress in each of them, how these tuners together affect the overall database performance is still an open question. There ...
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ISBN:
(纸本)9789819755516;9789819755523
Index recommendation and knob tuning are two important database tuners. Despite substantial progress in each of them, how these tuners together affect the overall database performance is still an open question. There exists a critical research gap in addressing integrated optimization of these tuners especially with additional consideration of resource utilization. Only a few works have focused on this, with challenges including high-dimensional search space, difficulty in model fitting, and delayed evaluation bias. To address these issues, we propose MODT, a novel Multi-Objective database Tuning framework, which combines hierarchical reinforcement learning (HRL) with a two-level recursive structure to automatically provide sequential configuration of indexes and knobs based on workload characteristics and database status. Compared with state-of-the-art integrated optimization approaches on TPC-H, TPC-DS, and Join Order Benchmark (JOB), MODT can find competitive index-knob configurations and outperforms competitors in reducing execution time and resource utilization.
OSGraph is an open source community data visualization and analysis platform with a dataset of 5.8 billion graph records. Utilizing a graph structure to represent repositories and developers, it offers in-depth insigh...
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ISBN:
(纸本)9789819755745;9789819755752
OSGraph is an open source community data visualization and analysis platform with a dataset of 5.8 billion graph records. Utilizing a graph structure to represent repositories and developers, it offers in-depth insights into the open source ecosystem. The platform includes key metrics such as developer Activity and Openrank, allowing users to effortlessly explore, analyze, and visualize open source data through intuitive panel features. OSGraph is publicly accessible. The demonstration showcases the functionality of detailed data panels and advanced analysis tools. OSGraph provides a simple and user-friendly experience for exploring the open source landscape.
Nowadays, web applications are generally utilized as a busybody between PC clients. Also, web applications are utilized by online business organizations, government agencies, research organizations, etc. that need to ...
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