Panorama x relational database11/4/2022 ![]() ![]() To this end, we propose a full-fledged query interface composed of a TSQL2-like query language with an underlying algebraic framework. In this paper, we go beyond the disjointed panorama of current approaches and adopt a new holistic approach to the integration of stream processing capabilities into the temporal database world based on the streaming table concept. ![]() #Panorama x relational database verificationModern data-intensive applications have to manage huge quantities of streaming/relational data and need advanced query capabilities involving combinations of continuous queries (CQs) and one-time queries (OTQs) also requiring the verification of complex temporal conditions. The proposed approach implements a new general and flexible strategy for repairing detected inconsistencies in a deferred manner and possibly in multiple steps, according to varying user’s requirements and to specifications which are customary in the real world. The feasibility of the approach has been shown through the development and testing of a system prototype, named Deferred-Repair Manager. The approach separates the inconsistency repairs from the inconsistency detection phase and deals with the execution of corrective actions, which also take into account enterprise’s business rules that define some relationships between data.Īlgorithms, methods and support data structures for deferred and multi-step inconsistency repair of currency data are presented. the salary of an employee) in a valid-time or bitemporal XML database is proposed. The purpose of this work is to deal with deferred and multi-step repair of detected data inconsistencies.Ī general approach for deferred and stepwise repair of inconsistencies that result from retroactive updates of currency data (e.g. at inconsistency detection time) or in a deferred manner, at one or several chosen repair times according to application requirements. payment of arrears after a retroactive salary increase) either immediately (i.e. Such an inconsistency state must be repaired by performing corrective actions (e.g. Experiments demonstrated that our two methods are relatively stable in overall time performance on different datasets in the Hyperledger Fabric System.Ī temporal XML database could become an inconsistent model of the represented reality after a retroactive update. In the experimental part, we compare the query time on two datasets and analyse the query performance. TIF (temporal index based on files) builds the index of files by the block transaction data, which is arranged in chronological order and is stored at a certain time interval. ![]() TISD (temporal index based on state databases) segments the historical data by time interval in the time dimension and indexes events at the same time interval. In this paper, we propose two index building methods (TISD and TIF) to address this issue in Hyperledger Fabric System. The problem is due to current blockchain solutions do not support temporal data processing. However, sequential access based on block files in the blockchain hinders efficient query processing. Blockchain technology has the characteristics of decentralization, data encryption, smart contract, and so on, especially suitable in the complex heterogeneous network. Paul Ramsey of Refractions Research has written up a nice summary of how were are using PostGIS.As a large number of mobile terminals are connected to the IoT, the security problem of IoT is a challenge to the IoT technology. In other words, PostGIS is a spatially-aware version of Postgresql. PostGIS is a set of extensions to the relational database management system PostgreSQL, which provide access to spatial constructs, operators, and functions. ![]()
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