Leveraging computation sharing and parallel processing in location-dependent query processing

2011 ◽  
Vol 61 (1) ◽  
pp. 215-234 ◽  
Author(s):  
Jonathan Cazalas ◽  
Ratan Guha
Keyword(s):  
Parallel Processing ◽  
Query Processing ◽  
Location Dependent Query ◽  
Computation Sharing

Study on Clustering-Based Location Dependent Query

2012 ◽  
Vol 532-533 ◽  
pp. 897-901
Author(s):  
Ming Jun Wei ◽  
Li Chun Xia ◽  
Jian Guo Jin ◽  
Qiu Hong Fan
Keyword(s):  
Mobile Computing ◽  
Query Processing ◽  
Location Analysis ◽  
System Efficiency ◽  
Analysis Algorithm ◽  
System Resources ◽  
Location Dependent Query ◽  
Special Case ◽  
New Location

This paper firstly analyzes the importance and necessity of location dependent query in the mobile computing. Then, it proposes a special case in the application of the location dependent query. That is as follows: Inquirers may send the same location dependent query in different but similar positions. However, the server will not deal with them together but treat them separately. Thus, it will not only cause the waste of system resources but also delay disposal of other queries. According to the principal of clustering we propose a new location Analysis Algorithms-similar merging location analysis algorithm (SMLA). By the algorithm, similar queries can be combined into the same query, so as to reduce the load on central servers, improve system efficiency and query processing performance.

scholarly journals Smart Intra-query Fault Tolerance for Massive Parallel Processing Databases

2019 ◽  
Vol 5 (1) ◽  
pp. 65-79
Author(s):  
Yunhong Ji ◽  
Yunpeng Chai ◽  
Xuan Zhou ◽  
Lipeng Ren ◽  
Yajie Qin
Keyword(s):  
Cost Effectiveness ◽  
Fault Tolerance ◽  
Parallel Processing ◽  
Query Processing ◽  
Success Rate ◽  
Database Systems ◽  
Analytical Processing ◽  
Commodity Clusters ◽  
Massive Parallel Processing ◽  
Query Latency

AbstractIntra-query fault tolerance has increasingly been a concern for online analytical processing, as more and more enterprises migrate data analytical systems from mainframes to commodity computers. Most massive parallel processing (MPP) databases do not support intra-query fault tolerance. They may suffer from prolonged query latency when running on unreliable commodity clusters. While SQL-on-Hadoop systems can utilize the fault tolerance support of low-level frameworks, such as MapReduce and Spark, their cost-effectiveness is not always acceptable. In this paper, we propose a smart intra-query fault tolerance (SIFT) mechanism for MPP databases. SIFT achieves fault tolerance by performing checkpointing, i.e., materializing intermediate results of selected operators. Different from existing approaches, SIFT aims at promoting query success rate within a given time. To achieve its goal, it needs to: (1) minimize query rerunning time after encountering failures and (2) introduce as less checkpointing overhead as possible. To evaluate SIFT in real-world MPP database systems, we implemented it in Greenplum. The experimental results indicate that it can improve success rate of query processing effectively, especially when working with unreliable hardware.

scholarly journals Location-Dependent Query Processing Under Soft Real-Time Constraints

2009 ◽  
Vol 5 (3) ◽  
pp. 205-232 ◽  
Author(s):  
Zoubir Mammeri ◽  
Franck Morvan ◽  
Abdelkader Hameurlain ◽  
Nadhem Marsit
Keyword(s):  
Performance Evaluation ◽  
Query Processing ◽  
Real Time ◽  
Mobile Devices ◽  
Communication Cost ◽  
Time Constraints ◽  
Mobile Clients ◽  
Location Dependent Query

In recent years, mobile devices and applications achieved an increasing development. In database field, this development required methods to consider new query types like location-dependent queries (i.e. the query results depend on the query issuer location). Although several researches addressed problems related to location-dependent query processing, a few works considered timing requirements that may be associated with queries (i.e., the query results must be delivered to mobile clients on time). The main objective of this paper is to propose a solution for location-dependent query processing under soft real-time constraints. Hence, we propose methods to take into account client location-dependency and to maximize the percentage of queries respecting their deadlines. We validate our proposal by implementing a prototype based on Oracle DBMS. Performance evaluation results show that the proposed solution optimizes the percentage of queries meeting their deadlines and the communication cost.

Partial Global Indexing for Location-Dependent Query Processing

2007 ◽  
pp. 739-743
Author(s):  
J. Jayaputera
Keyword(s):  
Simulation Model ◽  
Query Processing ◽  
Access Time ◽  
Current Cell ◽  
Local Storage ◽  
Location Dependent Query ◽  
Future Work

The idea of this article is based on the parallel indexing concept (Taniar & Rahayu, 2002) in which an indexed object residing in a BS is either fully, partially, or not replicated to others BSs. Therefore, every server contains either partial or all indexes of other servers. In our proposed approach, whenever the requested results return from neighboring cells, we append the resulting items to the current cell. This implies that when the next user sends a request, the current cell needs to look up its own index first to verify if the data is in its local storage. If the data is not present, the current server sends a request to the neighboring cells on behalf of the client; otherwise, the current server directly sends the requested query to the client. We have evaluated our proposed approach and showed that the access time can be reduced by a factor of two.The next section of this article describes some related work. We then describe our proposed work and the simulation model, and we compare the performance of our proposed technique to other techniques. Finally, we conclude the article and suggest future work.

scholarly journals Location-Dependent Query Processing: Semantic Cache for Real-Time Smart City Analytics

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Rabia Hasan ◽  
Waseem Shehzad ◽  
Ejaz Ahmed ◽  
Hasan Ali Khattak ◽  
Ahmed S. AlGhamdi ◽  
...  
Keyword(s):  
Query Processing ◽  
Research Work ◽  
Processing System ◽  
Mobile User ◽  
Location Based Services ◽  
Prediction Algorithm ◽  
User Query ◽  
Novel Approach ◽  
Deep Integration ◽  
Location Dependent Query

With the advent of wireless sensor networks and their deep integration with the world have enabled users worldwide to achieve benefits from location-based services through mobile applications, the problems such as low bandwidth, high network traffic, and disconnections issues are normally extracted from mobile services. An efficient database system is required to manage mentioned problems. Our research work finds the probability of user’s next locations. A mobile user (query issuer) changes its position when performing a specific mobile search, where these queries change and repeat the search with the issuer position. Moreover, the query issuer can be static and may perform searches with varying conditions of queries. Data is exchanged with mobile devices and questions that are formulated during searching for query issuer locations. An aim of the research work is achieved through effectively processing of queries in terms of location-dependent, originated by mobile users. Significant studies have been performed in this field in the last two decades. In this paper, our novel approach comprise of usage of semantic caches with the Bayesian networks using a prediction algorithm. Our approach is unique and distinct from the traditional query processing system especially in mobile domain for the prediction of future locations of users. Consequently, a better search is analyzed using the response time of data fetch from the cache.

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