Indexing techniques and structured queries for relational databases management systems.

Uloženo v:
Podrobná bibliografie
Název: Indexing techniques and structured queries for relational databases management systems.
Autoři: Saidu, Isah Charles, Yusuf, Musa, Nemariyi, Florence Chukwuemeka, George, Ayenopwa Comfort
Zdroj: Journal of Nigerian Society of Physical Sciences; Nov2024, Vol. 6 Issue 4, p1-12, 12p
Témata: RELATIONAL databases, INDEXING, INDEXES, DATABASE management, SQL
Abstrakt: Indexing has long been used to improve the speed of relational database systems, and choosing an adequate index at design time is critical to the database's efficiency. In this study, it was demonstrated empirically that data access time and data insertion time for moderately large datasets are influenced by the index chosen at design time. However, deletion time is approximately the same. As a result, regardless of the query optimization strategy utilized at runtime, record access/insertion time depends on the type of index employed at design time. This paper presents a comparison of BTree indexes with Hash indexes. It was demonstrated empirically that insertion is substantially faster with the Hash index than with the Btree index, at the expense of a larger Hash index file size. The Btree index is slower due to the rebuild time of Btree indexes during insertion. The empirical results of this study complement that of theoretical results for both Btree and Hash indexes. On the other hand, hash index files are large, restricting their use for applications with rapidly increasing dataset sizes; thus, a tradeoff employing Hash index or Btrees is required. In general, this study proposes Hash indexes for small dataset applications and Btree indexes for large dataset applications on systems with limited memory. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Nigerian Society of Physical Sciences is the property of Nigerian Society of Physical Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Biomedical Index
Buďte první, kdo okomentuje tento záznam!
Nejprve se musíte přihlásit.