IMPROVING NEAR REAL TIME DATA WAREHOUSE REFRESHMENT

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

HAZRATI ISA; Daneshpour Negin

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: SIGNAL AND DATA PROCESSING Year:2018 | Volume:15 | Issue:2 (SERIAL 36) Page(s): 31-43

Download Full-Text

Persian Verion

View:

714

Download:

Cites:

Information Journal Paper

Title

IMPROVING NEAR REAL TIME DATA WAREHOUSE REFRESHMENT

Author(s)

HAZRATI ISA | Daneshpour Negin | Issue Writer Certificate

Keywords

NEAR REAL TIME DATA WAREHOUSEQ1

JOINQ1

DATA STREAMQ1

DECISION MAKINGQ1

Abstract

Near-real time data warehouse gives the end users the essential information to achieve appropriate decisions. Whatever the data are fresher in it, the decision would have a better result either. To achieve a fresh and up-to-date data, the changes happened in the side of source must be added to the data warehouse with little delay. For this reason, they should be transformed in to the data warehouse format. One of the famous algorithms in this area is called X-HYBRIDJOIN. In this algorithm the data characteristics of real word have been used to speed up the JOIN operation. This algorithm keeps some partitions, which have more uses, in the main memory. In the proposed algorithm in this paper, disk-based relation is JOINed with input DATA STREAM. The aim of such JOIN is to enrich stream. The proposed algorithm uses clustered index for disk-based relation and JOIN attribute. Moreover, it is assumed that the JOIN attribute is exclusive throughout the relation. This algorithm has improved the mentioned algorithm in two stages. At the first stage, some records of source table which are frequently accessible are detected. Detection of such records is carried out during the algorithm implementation. The mechanism is in the way that each record access is counted by a counter and if it becomes more than the determined threshold, then it is considered as the frequently used record and placed in the hash table. The hash table is used to keep the frequently used records in the main memory. When the stream is going to enter in to JOIN area, it is searched in this table. At the second stage, the choice method of the partition which is going to load in the main memory has been changed. One dimensional array is used to choose the mentioned partition. This array helps to select a partition of source table with highest number of records for the JOIN among all partitions of source table. Using this array in each iteration, always leads to choose the best partition loading in memory. To compare the usefulness of the suggested algorithm some experiments have been done. Experimental results show that the service rate acquired in suggested algorithm is more than the existing algorithms. Service rate is the number of JOINed records in a time unit. Increasing service rate causes the effectiveness of the algorithm.

Cites

No record.

References

No record.

Cite

APA: Copy

HAZRATI, ISA, & Daneshpour, Negin. (2018). IMPROVING NEAR REAL TIME DATA WAREHOUSE REFRESHMENT. SIGNAL AND DATA PROCESSING, 15(2 (SERIAL 36) ), 31-43. SID. https://sid.ir/paper/160924/en

Vancouver: Copy

HAZRATI ISA, Daneshpour Negin. IMPROVING NEAR REAL TIME DATA WAREHOUSE REFRESHMENT. SIGNAL AND DATA PROCESSING[Internet]. 2018;15(2 (SERIAL 36) ):31-43. Available from: https://sid.ir/paper/160924/en

IEEE: Copy

ISA HAZRATI, and Negin Daneshpour, “IMPROVING NEAR REAL TIME DATA WAREHOUSE REFRESHMENT,” SIGNAL AND DATA PROCESSING, vol. 15, no. 2 (SERIAL 36) , pp. 31–43, 2018, [Online]. Available: https://sid.ir/paper/160924/en

Related Journal Papers