scholarly journals Checking Causal Consistency of Distributed Databases

2019 ◽  
pp. 35-51
Author(s):  
Rachid Zennou ◽  
Ranadeep Biswas ◽  
Ahmed Bouajjani ◽  
Constantin Enea ◽  
Mohammed Erradi
Keyword(s):  
Distributed Databases ◽  
Causal Consistency

scholarly journals Checking causal consistency of distributed databases

Computing ◽  
2021 ◽  
Author(s):  
Rachid Zennou ◽  
Ranadeep Biswas ◽  
Ahmed Bouajjani ◽  
Constantin Enea ◽  
Mohammed Erradi
Keyword(s):  
Distributed Databases ◽  
Causal Consistency

Network search

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Web Search ◽  
Distributed Databases ◽  
Small World ◽  
Peer Networks ◽  
Model Parameters ◽  
Breadth First Search ◽  
Ranking Algorithms ◽  
Network Search ◽  
Peer To Peer Networks ◽  
Search Processes

This chapter gives a discussion of search processes on networks. It begins with a discussion of web search, including crawlers and web ranking algorithms such as PageRank. Search in distributed databases such as peer-to-peer networks is also discussed, including simple breadth-first search style algorithms and more advanced “supernode” approaches. Finally, network navigation is discussed at some length, motivated by consideration of Milgram's letter passing experiment. Kleinberg's variant of the small-world model is introduced and it is shown that efficient navigation is possible only for certain values of the model parameters. Similar results are also derived for the hierarchical model of Watts et al.

scholarly journals Modelling and optimization of information systems with distributed databases

2021 ◽  
Vol 1155 (1) ◽  
pp. 012062
Author(s):  
I Ya Lvovich ◽  
Ya E Lvovich ◽  
A P Preobrazhenskiy ◽  
Yu P Preobrazhenskiy ◽  
O N Choporov
Keyword(s):  
Information Systems ◽  
Distributed Databases ◽  
Modelling And Optimization

scholarly journals State Management for Cloud-Native Applications

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 423
Author(s):  
Márk Szalay ◽  
Péter Mátray ◽  
László Toka
Keyword(s):  
Large Scale ◽  
Distributed Databases ◽  
Access Time ◽  
Replica Placement ◽  
State Management ◽  
Placement Decisions ◽  
Dynamic Replication ◽  
Cloud Databases ◽  
Placement Algorithm ◽  
The One

The stateless cloud-native design improves the elasticity and reliability of applications running in the cloud. The design decouples the life-cycle of application states from that of application instances; states are written to and read from cloud databases, and deployed close to the application code to ensure low latency bounds on state access. However, the scalability of applications brings the well-known limitations of distributed databases, in which the states are stored. In this paper, we propose a full-fledged state layer that supports the stateless cloud application design. In order to minimize the inter-host communication due to state externalization, we propose, on the one hand, a system design jointly with a data placement algorithm that places functions’ states across the hosts of a data center. On the other hand, we design a dynamic replication module that decides the proper number of copies for each state to ensure a sweet spot in short state-access time and low network traffic. We evaluate the proposed methods across realistic scenarios. We show that our solution yields state-access delays close to the optimal, and ensures fast replica placement decisions in large-scale settings.

Query Optimization in the Databases Distributed by Means of Product Equivalence Relations

1988 ◽  
Vol 11 (3) ◽  
pp. 241-265
Author(s):  
W. Marek ◽  
C. Rauszer
Keyword(s):  
Query Optimization ◽  
Selection Process ◽  
Distributed Databases ◽  
Optimization Techniques ◽  
Equivalence Relations ◽  
Database Operations ◽  
By Products

In this paper, we address the problem of query optimization in distributed databases. We show that horizontal partitions of databases, generated by products of equivalence relations, induce optimization techniques for the basic database operations (i.e., the selection, projection, and join operators). In the case of selection, our method allows for restriction of the number of blocks to be searched in the selection process and subsequent simplification of the selection formula at each block. For the natural join operation, we propose an algorithm that reduces the computation of fragments. Proofs of the correctness of our algorithms are also included.

scholarly journals PatchIndex: exploiting approximate constraints in distributed databases

2021 ◽  
Author(s):  
Steffen Kläbe ◽  
Kai-Uwe Sattler ◽  
Stephan Baumann
Keyword(s):  
Data Analytics ◽  
Distributed Databases ◽  
Database Systems ◽  
Optimization Techniques ◽  
Cloud Data ◽  
Database Administrator ◽  
Small Set ◽  
Parallel Index ◽  
Access Data ◽  
Integrate Data

AbstractCloud data warehouse systems lower the barrier to access data analytics. These applications often lack a database administrator and integrate data from various sources, potentially leading to data not satisfying strict constraints. Automatic schema optimization in self-managing databases is difficult in these environments without prior data cleaning steps. In this paper, we focus on constraint discovery as a subtask of schema optimization. Perfect constraints might not exist in these unclean datasets due to a small set of values violating the constraints. Therefore, we introduce the concept of a generic PatchIndex structure, which handles exceptions to given constraints and enables database systems to define these approximate constraints. We apply the concept to the environment of distributed databases, providing parallel index creation approaches and optimization techniques for parallel queries using PatchIndexes. Furthermore, we describe heuristics for automatic discovery of PatchIndex candidate columns and prove the performance benefit of using PatchIndexes in our evaluation.

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