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Aggregate-Query Processing in Data Warehousing Environments

Aggregate-Query Processing in Data Warehousing Environments* Ashish Gupta Venky Harinarayan Dallan Quass IBM Almaden Research Center Abstract In this paper we introduce generalized pro- jections (GPs), an extension of duplicate- eliminating projections, that capture aggre- gations, groupbys, duplicate-eliminating pro-Aggregate query processing in the presence of duplicates,,10/03/2015· Aggregate query processing. In this section, we consider aggregate queries with the SQL-syntax presented in Section 1. 3.1. The LCA algorithm: one-phase aggregation. A naive brute-force (BF) algorithm can be designed as follows. All sensor nodes take their readings periodically and keep these readings into their local tables. Each sensor node transmits its measured data as well as thoseAggregate Query Processing on XML Data - CiteSeerX,aggregate attribute values of all resulting element sets; and average(pattern) computes the average over the aggregate attribute values of all resulting element sets. 3. Aggregate query processing Among the aggregate operations, count is an im-portant one. We will present an algorithm for proc-essing the count operation and discuss how to im-

Aggregation and query processing

Aggregation and query processing. From the perspective of query processing (QP), aggregation can be both a costly operation, and an operation whose placement has an important impact on query performance. Aggregation generally computes an aggregated value. Vector aggregation is costly, compared to scalar aggregation, as rows must be grouped together to obtain the aggregated resultAggregate Query Processing on Incomplete Data |,19/07/2018· Aggregate Query Processing on Incomplete Data. Authors; Authors and affiliations; Anzhen Zhang; Jinbao Wang; Jianzhong Li; Hong Gao; Conference paper. First Online: 19 July 2018. 1 Citations; 910 Downloads; Part of the Lecture Notes in Computer Science book series (LNCS, volume 10987) Abstract,Optimizing Aggregate Query Processing in Cloud Data Warehouses,Aggregate query processing has been studied in many research works [5]. But, as per our knowledge, not many of them consider communication cost in optimizing aggregate query processing. We analyzed some of the works which optimize the aggregate query operations. Along with that knowledge, we propose our storage structures, which will not only optimize query operations, but also communica

Ad-hoc aggregate query processing algorithms based on

Secondly, different aggregate operations for query processing are presented based on different encoding schemes. Thirdly, cost analysis for different aggregate operations is presented. Finally, the effectiveness and efficiency of the proposed algorithms is showed by the analytical and experimental results. References [1] Cannataro, M., Talia, D. and Srimani, P.K., Parallel data-intensive,Aggregate query processing in the presence of,10/03/2015· Aggregate query processing. In this section, we consider aggregate queries with the SQL-syntax presented in Section 1. 3.1. The LCA algorithm: one-phase aggregation. A naive brute-force (BF) algorithm can be designed as follows. All sensor nodes take their readings periodically and keep these readings into their local tables. Each sensor node transmits its measured data as well as those dataSAMPLING BASED JOIN-AGGREGATE QUERY PROCESSING,Approximate aggregate query processing techniques presented in [1,2] provide approximate results to a simple non-join aggregate query as depicted in Query 1, for Big Data queries. Here, aggregate() denotes the aggregate function such as: Sum, Average, Variance, Standard Deviation etc. Additionally, individual selection predicates can be imposed on relation R. Specifically, in [1], the,

Optimizing Aggregate Query Processing in Cloud Data Warehouses

aggregate query processing algorithms focus on optimizing various query operations but give less importance to communication cost overhead (Two-phase algorithm). However, in cloud architectures, the communi-cation cost overhead is an important factor in query processing. Thus, we consider communication overhead to improve the distributed query pro-Aggregate query processing in the presence of duplicates,,Aggregate query processing in the presence of duplicates in wireless sensor networks. Author links open overlay panel Jun-Ki Min a Jun-Ki Min aAd-hoc aggregate query processing algorithms based on,The paper focuses on proposing ad-hoc aggregate query algorithms based on bit-store. Firstly, the storage model of bit-store including its attribute encoding schemes and bit file organization is introduced. Secondly, different aggregate operations for query processing are presented based on different encoding schemes. Thirdly, cost analysis for different aggregate operations is presented. Finally, the

Optimizing Performance of Aggregate Query

24/04/2019· Among previous research, most of them are working on precise query processing, while approximate query processing (AQP) techniques which make interactive data exploration more efficiently and allows users to tradeoff between query accuracy and response time have not been investigate comprehensively. In this paper, we study the characteristics of aggregate query, a typicalCN101681368A - Aggregation query processing - Google,Aggregation query processing Download PDF Info Publication number CN101681368A. CN101681368A CN200880015990A CN200880015990A CN101681368A CN 101681368 A CN101681368 A CN 101681368A CN 200880015990 A CN200880015990 A CN 200880015990A CN 200880015990 A CN200880015990 A CN 200880015990A CN 101681368 A CN101681368 A CNClustering spatial networks for aggregate query processing,,made by the aggregate network operations during query processing. For this purpose, different techniques based on the clustering graph model are proposed in the literature. In this work, we show that the state-of-the-art clustering graph model is not able to correctly capture the disk access costs of aggregate network operations. Moreover, we propose a novel clustering hypergraph model that,

Probabilistic Threshold Range Aggregate Query Processing,

Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data,A range aggregate query (RA query) on certain data returns summarized information about objects satisfying a given query range, such as the total num-ber of qualified objects [19]. This type of query is important since users may be interested only in aggregate information instead of specific IDs. For instance,aggregate query processing in peer to peer networks,Aggregate Query Processing In Peer To Peer Networks. Query processing in peer to peer network project is a cse project which is implemented in visual studio cThis project explains about finding our sum, average, minimum and maximum count and aggregate in query processingPeer to peer database has become one of the biggest sources for uploading downloading of images videos and . Robust and,Optimizing Aggregate Query Processing in Cloud Data Warehouses,aggregate query processing algorithms focus on optimizing various query operations but give less importance to communication cost overhead (Two-phase algorithm). However, in cloud architectures, the communi-cation cost overhead is an important factor in query processing. Thus, we consider communication overhead to improve the distributed query pro-

Aggregate-Query Processing in Data Warehousing,

Aggregate-Query Processing in Data Warehousing Environments. Share on. Authors: Ashish Gupta. View Profile, Venky Harinarayan. View Profile, Dallan Quass. View Profile. Authors Info & Affiliations ; Publication: VLDB '95: Proceedings of the 21th International Conference on Very Large Data Bases September 1995 Pages 358–369. 114 citation; 0; Downloads. Metrics. Total Citations 114. Total,SAMPLING BASED JOIN-AGGREGATE QUERY PROCESSING,Approximate aggregate query processing techniques presented in [1,2] provide approximate results to a simple non-join aggregate query as depicted in Query 1, for Big Data queries. Here, aggregate() denotes the aggregate function such as: Sum, Average, Variance, Standard Deviation etc. Additionally, individual selection predicates can be imposed on relation R. Specifically, in [1], the,Ad-hoc aggregate query processing algorithms based on,The paper focuses on proposing ad-hoc aggregate query algorithms based on bit-store. Firstly, the storage model of bit-store including its attribute encoding schemes and bit file organization is introduced. Secondly, different aggregate operations for query processing are presented based on different encoding schemes. Thirdly, cost analysis for different aggregate operations is presented. Finally, the

Wolap: Wavelet-based range aggregate query processing

We efficient processing of a variety of polynomial queries. Toward combine both cube models in an integrated framework, called this end, ProPolyne utilizes the wavelet transform of data WOLAP, for efficient polynomial aggregate query processing. We further enhance WOLAP by proposing practical solutions for frequency distribution, known as DFD, to form and process real-world deployment inOptimizing Performance of Aggregate Query,24/04/2019· Among previous research, most of them are working on precise query processing, while approximate query processing (AQP) techniques which make interactive data exploration more efficiently and allows users to tradeoff between query accuracy and response time have not been investigate comprehensively. In this paper, we study the characteristics of aggregate query, a typicalClustering spatial networks for aggregate query processing,,made by the aggregate network operations during query processing. For this purpose, different techniques based on the clustering graph model are proposed in the literature. In this work, we show that the state-of-the-art clustering graph model is not able to correctly capture the disk access costs of aggregate network operations. Moreover, we propose a novel

Probabilistic Threshold Range Aggregate Query Processing,

Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data,A range aggregate query (RA query) on certain data returns summarized information about objects satisfying a given query range, such as the total num-ber of qualified objects [19]. This type of query is important since users may be interested only in aggregate information instead of specific IDs. For instance,(PDF) Processing Multiple Aggregation Queries in Geo,,A query can take full advantage of the view if the aggregation required by the query is the same as the view. Thus, multiple queries can be supported through the view. Second, the views are distributed in the sensor network, so it does not overload any single sensor and it does not require any super sensor (i.e., a more powerful sensor) for data storage or processing. Queries are executed by,an aggregate query processing system for wireless network,an aggregate query processing system for wireless network. aggregate query processing in sensor networks An Aggregate Query Processing System For Wireless Network Aggregate Query Processing In Wireless Sensor Networ aggregate query processing in wireless sensor network aggregate real time state information afterDictionary s List of Every Word of the Year