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A Distributed Processing Framework System Based on Time Travel and Temporal Aggregation Query

A distributed processing and distributed node technology, applied in the computer field, can solve the problems of temporal big data time travel and temporal aggregation operations without developing distributed solutions, and no native support for temporal data queries, etc.

Active Publication Date: 2020-10-20
SHANGHAI JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As far as we know, none of the existing big data systems (such as Apache Hadoop, Apache Spark) natively support temporal data query, and none of the previous work has developed memory-based distributed solutions to process temporal big data. Time Travel and Temporal Aggregation Operations

Method used

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  • A Distributed Processing Framework System Based on Time Travel and Temporal Aggregation Query
  • A Distributed Processing Framework System Based on Time Travel and Temporal Aggregation Query
  • A Distributed Processing Framework System Based on Time Travel and Temporal Aggregation Query

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Embodiment Construction

[0038] The present invention is described in further detail now in conjunction with accompanying drawing. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the configurations related to the present invention.

[0039] 1. Problem definition

[0040] Specifically, the present invention attempts to implement two representative operations on temporal data (ie, time travel and temporal aggregation) in a distributed environment. However, the framework and algorithms we describe later can be easily extended to support other temporal operations (e.g., temporal joins) and other data (e.g., bitemporal data [R. Bliujute, C.S. Jensen, S. Saltenis, G. Slivinskas: R-tree based indexing of now-relative bittemporal data. In VLDB, 1998], dual-time data, that is, data records that contain both valid time (Valid time) and transaction time (Transaction time)). Next, we formally define...

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Abstract

The invention discloses a distributed processing framework system based on time travel and temporal aggregation querying. The system includes a partition unit, a local index unit and a global index unit. The partition unit is responsible for partitioning all data to distributed nodes. The local index unit is used for managing temporal data in all partitions. The global index unit is used for managing partition intervals. The system provides a distributed memory analysis framework for temporal big data, and the framework is easy to understand and implement without losing efficiency, and can satisfy requirements of high throughput and low latency.

Description

technical field [0001] The invention belongs to the field of computers, and in particular relates to a temporal data query system, in particular to a distributed processing framework system based on time travel and temporal aggregation query. Background technique [0002] The management of temporal data has been studied for decades and has recently received increasing attention due to its wide range of applications [cf: M. Gupta, J. Gao, C. C. Aggarwal, J. Han: Outlier Detection for Temporal Data: A Survey.In TKDE,2014; F.Li,K.Yi,W.Le:Top-k queries on temporal data.InVLDBJ,2010]. For example, a user may wish to investigate demographic information for an administrative region (eg, California) at a certain time (eg, 5 years ago). Querying historical versions of a database (as described above) is often referred to as time travel [R.Elmasri, G.T.Wuu, and Y.J.Kim. The Time Index: An Access Structure for Temporal Data. InVLDB, 1990; B.Becker, S.Gschwind, T. Ohler, B. Seeger, B. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/22G06F16/2458G06F16/27
Inventor 姚斌过敏意张伟唐飞龙陈全冷静文
Owner SHANGHAI JIAOTONG UNIV