Trigger inheritance and overriding in an active object database system

Bertino, Elisa; Guerrini, Giovanna; Merlo, Isabella

doi:10.1109/69.868909

Cited by 14 publications

(5 citation statements)

References 32 publications

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“…There are many traditional ways to find the changed parts. Trigger mode is creating a trigger for every table in the database [17]. When a table changes, it can be captured by the trigger, and then increments can be found.…”

Section: B Incremental Synchronizationmentioning

confidence: 99%

Function of Content Defined Chunking Algorithms in Incremental Synchronization

Zhang

et al. 2020

IEEE Access

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Data chunking algorithms divide data into several small data chunks in a certain way, thus transforming the operation of data into the one of multiple small data chunks. Data chunking algorithms have been widely used in duplicate data detection, parallel computing and other fields, but it is seldom used in data incremental synchronization. Aiming at the characteristics of incremental data synchronization, this paper proposes a novel data chunking algorithm. By dividing two data that need synchronization into small data chunks, comparing the contents of these small data chunks, different ones are the incremental data that need to be found. The new algorithm determines to set a cut-point based on the number of 1 contained in the binary format of all bytes in an interval. Thus it improves the resistance against the byte shifting problem at the expense of the chunk size stability, which makes it more suitable for the incremental data synchronization. Comparing this algorithm with several known classical or state of art algorithms, experiments show that the incremental data found by this algorithm can be reduced by 32%∼57% compared to the others with same changes between two data. The experimental results based on real-world datasets show that PCI improves the calculation speed of classic Rsync algorithm up to 70%, however, with a drawback of increasing the Transmission compression rate up to 11.8%. INDEX TERMS Data synchronization, chunking algorithm, data backup, increment.

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Section: B Incremental Synchronizationmentioning

confidence: 99%

Function of Content Defined Chunking Algorithms in Incremental Synchronization

Zhang

et al. 2020

IEEE Access

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“…When synchronizing incremental data are stored in database, the methods of discovering incremental data include database triggers [29], log-based document parsing [30], programming control and so on.…”

Section: ) Relational Database Systemmentioning

confidence: 99%

MII: A Novel Content Defined Chunking Algorithm for Finding Incremental Data in Data Synchronization

Zhang

Cai

et al. 2019

IEEE Access

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In the data backup system, to reduce the bandwidth and processing time overhead caused by full backup technology during data synchronization between backups and source data, incremental backup technology is emerging as the focus of academic and industrial research. It is key but poorly-solved to find the incremental data between backups and source data for incremental backup technology. To find out the incremental data during the backup process, here, in this paper, we propose a novel content-defined chunking algorithm. The source data and backup data are chunked into some small chunks in the same way with the variable length. Then, by comparing whether a chunk of source data is different from any of the chunks in backup data, we can evaluate whether the chunk of source data is incremental data. By experiments, the chunking algorithm in this paper is compared to other ones which are the classical or state-of-the-art algorithms. The experimental results show that the incremental data found by this algorithm can be reduced by 13%-34% compared to the others with the same chunk throughput. INDEX TERMS Data synchronization, chunking algorithm, data backup, increment.

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“…From related work we extracted various aspects and their options: All found inheritance mechanisms are transitive. Furthermore, inheritance is often discussed regarding certain foci, i.e., signatures (schema of inputs and outputs), behavior, or implementation [32,27,20,30,23,17,5]. Besides these aspects, inheritance is usually distinguished into single-inheritance and multi-inheritance [12,20,27,30,32,17], i.e., child entities inherit from a single or multiple parent entities respectively.…”

Section: Inheritancementioning

confidence: 99%

“…Several researchers proposed inheritance of pre-and postconditions of operations (rule premises) [23,24,30] where modifications to conditions are restricted to strengthening or weakening. Other research regards inheritance of triggers (which can be considered event-condition-action rules) in object-oriented databases [5], where a trigger's premises may become weaker and trigger actions may be extended. FLORA-2 [17] combines rules and object-oriented features where methods are specified as rules and can be inherited.…”

Section: Proof-of-concept Prototypementioning

confidence: 99%

Rule Module Inheritance with Modification Restrictions

Burgstaller

Neumayr

Sallinger

et al. 2018

Lecture Notes in Computer Science

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Adapting rule sets to different settings, yet avoiding uncontrolled proliferation of variations, is a key challenge of rule management. One fundamental concept to foster reuse and simplify adaptation is inheritance. Building on rule modules, i.e., rule sets with input and output schema, we formally define inheritance of rule modules by incremental modification in single inheritance hierarchies. To avoid uncontrolled proliferation of modifications, we introduce formal modification restrictions which flexibly regulate the degree to which a child module may be modified in comparison to its parent. As concrete rule language, we employ Datalog ± which can be regarded a common logical core of many rule languages. We evaluate the approach by a proof-of-concept prototype.

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Trigger inheritance and overriding in an active object database system

Cited by 14 publications

References 32 publications

Function of Content Defined Chunking Algorithms in Incremental Synchronization

Function of Content Defined Chunking Algorithms in Incremental Synchronization

MII: A Novel Content Defined Chunking Algorithm for Finding Incremental Data in Data Synchronization

Rule Module Inheritance with Modification Restrictions

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