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MongoDB is one of the typical NoSQL database. The database mechanisms of MongoDB about document-oriented storage, GridFS for storing files of any size. The data storage structure of MongoDB is given, which uses BSON as the data storage and network transfer format for documents, simple and fast in query and easy in horizontal scalability with low cost.
NoSQL database is the broad definition of nonrelational data storage. As a result of the new storage model, the traditional normal-form theory difficult to adapt to new applications. In this paper, the characteristics of the data logic model of NoSQL database MongoDB and the mode design principles were analyzed, then a method based on anti-normal form model was proposed. This method is based on the...
GPUs have been proven very effective for structured applications. However, emerging data intensive applications are increasingly unstructured — irregular in their memory and control flow behavior over massive data sets. While the irregularity in these applications can result in poor workload balance among fine-grained threads or coarse-grained blocks, one can still observe dynamically formed pockets...
Big Data boosts the development of data management and analysis in database systems but it also poses a challenge to traditional database. NoSQL databases are provided to deal with the new challenges brought by Big Data because of its high performance, storage, scalability and availability. In NoSQL databases, it is an essential requirement to provide scalable and efficient index services for real-time...
Isoline generating is often used in reservoir simulation, but the speed of data processing is likely to become slowly while the number of data is enormous. During the isoline generating, isoline tracing takes most of the time. In order to satisfy the requirement of real-time, an isoline tracing algorithm with CUDA is designed in this paper. In the algorithm designed here, equivalent points are stored...
Mining frequent patterns is important for mining association rules. However, because of the inherent complexity, mining complete frequent patterns from a dense database could be impractical, and the quantity of the mined patterns is usually very large, it is hard to understand and make use of them. Maximal frequent patterns contain and compress all frequent patterns, and the memory needed for saving...
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