scholarly journals Mixed Uses of Materialized View and Signature View-Index Mechanism for Efficient Query Processing on CORBA

2004 ◽  
Vol 11D (1) ◽  
pp. 61-68
Keyword(s):  
Query Processing ◽  
Materialized View ◽  
Efficient Query Processing

Efficient Query Processing with Structural Join Indexing in an Object Relational Data Warehousing Environment

2011 ◽  
pp. 243-256
Author(s):  
Vivekanand Gopalkrishnan ◽  
Qing Li ◽  
Kamalakar Karlapalem
Keyword(s):  
Query Processing ◽  
Data Warehousing ◽  
Cost Model ◽  
Hill Climbing ◽  
Relational Data ◽  
Structural Join ◽  
Object Relational ◽  
Hybrid Data ◽  
Efficient Query Processing ◽  
Query Semantics

In an Object Relational Data Warehousing (ORDW) environment, the semantics of data and queries can be explicitly captured, represented, and utilized based on is-a and class composition hierarchies, thereby resulting in more efficient OLAP query processing. In this chapter, we show the efficacy in building semantic-rich hybrid data indexes incorporating Structural Join Index Hierarchy (SJIH) on the ORDW views. Given a set of queries, we use a hill-climbing heuristic algorithm to select (near) optimal SJIHs, thereby embedding query semantics into the indexing framework. Finally, by a cost model, we analyze the effectiveness of our approach vis-a-vis the pointer chasing approach.

Effective keyword search on graph data using limited root redundancy of answer trees

2018 ◽  
Vol 14 (3) ◽  
pp. 299-316 ◽  
Author(s):  
Chang-Sup Park
Keyword(s):  
Query Processing ◽  
Keyword Search ◽  
Information Need ◽  
Keyword Query ◽  
Content Type ◽  
Graph Data ◽  
Distinct Root ◽  
Path Index ◽  
Complex Graph ◽  
Efficient Query Processing

Purpose This paper aims to propose a new keyword search method on graph data to improve the relevance of search results and reduce duplication of content nodes in the answer trees obtained by previous approaches based on distinct root semantics. The previous approaches are restricted to find answer trees having different root nodes and thus often generate a result consisting of answer trees with low relevance to the query or duplicate content nodes. The method allows limited redundancy in the root nodes of top-k answer trees to produce more effective query results. Design/methodology/approach A measure for redundancy in a set of answer trees regarding their root nodes is defined, and according to the metric, a set of answer trees with limited root redundancy is proposed for the result of a keyword query on graph data. For efficient query processing, an index on the useful paths in the graph using inverted lists and a hash map is suggested. Then, based on the path index, a top-k query processing algorithm is presented to find most relevant and diverse answer trees given a maximum amount of root redundancy allowed for a set of answer trees. Findings The results of experiments using real graph datasets show that the proposed approach can produce effective query answers which are more diverse in the content nodes and more relevant to the query than the previous approach based on distinct root semantics. Originality/value This paper first takes redundancy in the root nodes of answer trees into account to improve the relevance and content nodes redundancy of query results over the previous distinct root semantics. It can satisfy the users’ various information need on a large and complex graph data using a keyword-based query.

Handling Constraints Using Penalty Functions in Materialized View Selection

2019 ◽  
Vol 8 (2) ◽  
pp. 1-17
Author(s):  
Anjana Gosain ◽  
Kavita Sachdeva
Keyword(s):  
Query Processing ◽  
Penalty Function ◽  
Penalty Functions ◽  
Maintenance Cost ◽  
Penalty Function Method ◽  
View Selection ◽  
Materialized View ◽  
Processing Cost ◽  
Adaptive Penalty ◽  
Materialized View Selection

Materialized view selection (MVS) plays a vital role for efficiently making decisions in a data warehouse. This problem is NP-hard and constrained optimization problem. The authors have handled both the space and maintenance cost constraint using penalty functions. Three penalty function methods i.e. static, dynamic and adaptive penalty functions have been used for handling constraints and Backtracking Search Optimization algorithm (BSA) has been used for optimizing the total query processing cost. Experiments were conducted comparing the static, dynamic and adaptive penalty functions on varying the space constraint. The adaptive penalty function method yields the best results in terms of minimum query processing cost and achieves the optimality, scalability and feasibility of the problem on varying the lattice dimensions and on increasing the number of user queries. The authors proposed work has been compared with other evolutionary algorithms i.e. PSO and genetic algorithm and yields better results in terms of minimum total query processing cost of the materialized views.

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