Hybrid Classification of OLAP Queries in Cloud Computing Environment

Generally, the execution time of the decision requests on large tables is very high which degrades the performance of data warehouses (DW). On the other hand, having high traffic can influence the response time of queries. Cloud Computing (CC) offers a solution to this kind of problem by providing a flexible environment in which data is highly available since it is stored and duplicated in different nodes. Optimizing the performance of an DW deployed on CC is indispensable task that aims to make cloud services conform to customer expectations by increasing performance at a minimum cost. This optimization is based on the improvement of various factors such as the response time to the client queries, availability, scalability, etc. Thus, having a voluminous and dynamic queries load can make the task of optimization difficult. For this purpose, we propose in this paper a hybrid classification technique of queries, in order to minimize his number and reduce the total cost of hosting the DW on the CC

Optimizing the Performance of Data Warehouse by Query Cache Mechanism

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How to Optimize the Environmental Impact of Transformed NoSQL Schemas through a Multidimensional Cost Model?

The complexity of database systems has increased significantly along with the continuous growth of data, resulting in NoSQL systems and forcing Information Systems (IS) architects to constantly adapt their data models (i.e., the data structure of information stored in the database) and carefully choose the best option(s) for storing and managing data. In this context, we propose %in this paper an automatic global approach for leading data models' transformation process. This approach starts with the generation of all possible solutions. It then relies on a cost model that helps to compare these generated data models in a logical level to finally choose the best one for the given use case. This cost model integrates both data model and queries cost. It also takes into consideration the environmental impact of a data model as well as its financial and its time costs. This work presents for the first time a multidimensional cost model encompassing time, environmental and financial constraints, which compares data models leading to the choice of the optimal one for a given use case. In addition, a simulation for data model's transformation and cost computation has been developed based on our approach

Implementing Multidimensional Data Warehouses into NoSQL

International audienceNot only SQL (NoSQL) databases are becoming increasingly popular and have some interesting strengths such as scalability and flexibility. In this paper, we investigate on the use of NoSQL systems for implementing OLAP (On-Line Analytical Processing) systems. More precisely, we are interested in instantiating OLAP systems (from the conceptual level to the logical level) and instantiating an aggregation lattice (optimization). We define a set of rules to map star schemas into two NoSQL models: columnoriented and document-oriented. The experimental part is carried out using the reference benchmark TPC. Our experiments show that our rules can effectively instantiate such systems (star schema and lattice). We also analyze differences between the two NoSQL systems considered. In our experiments, HBase (columnoriented) happens to be faster than MongoDB (document-oriented) in terms of loading time

Managing RDF Graphs using Mapreduce Algorithm with Indexing Solution for Future Direction

�Indexing solution� based on Big RDF (Resource Description Framework) graphs with improve processing which populate the semantic web, are the core data structure of the big web data, the natural transposition of big data on the web. Indexing data structure improve processing on the big RDF graph. it was present the �baseline operation� of fortunate web big data analytic. this require process, access and manage RDF graphs. It was dealing with severe temporal complexity. A solution to problem is represented by MapReduce model based algorithm for indexing solution which try to exploit the computation power offered by the MapReduce processing model in indexing order. this paper provide a survey on MapReduce based algorithm for state-of-the-art proposal using indexing solution