امام طبری کا تفسیری منہج اور ترجیحات کا تحقیقی مطالعہ

The Jāmiʿ al-bayān ʿan taʾwīl āy al-Qurʾān (جامع البیان عن تاویل ای القران) the book of Quranic interpretation is known as Tafsīr al-Ṭabarī. The author Imām Ṭabarī was blessed for being skilled enough in presenting the message of Islam with different methods. The methodology he has chosen to explain the precious hidden beads of Holy Quran is associated with the methodology of tafsir bi-al-ma’thur (تفسیر بالماثور). His presented explanations are completely independent from the reflection of his personal opinions. The statements of the early stages of Islam, the direct transmissions by the Holy prophet Muhammad (ﷺ) and his companions were chiefly used to understand the meaning of Holy Quran. The jurisprudence, linguistic, and the philosophic approaches are also referred in his tafsir.

Compression-Aware Query Optimization Using Cost-Based Model

In these days to enhance the performance of databases researchers propose compression as well as query optimization. Compression reduces volume of data and query optimization reduces execution time of query. There are some issues while compressing database and performing query optimization the first one is the selection of suitable compression scheme. Second is how to reduce the query execution time. which algorithm we use. How to overcome on the demerits of these two issues. We use dictionary-based approach for compression with many small dictionaries that quickly load in the memory on demand. One big diction requires more time for loading and scanning. We also perform query optimization on database without decompressing it by considering fewer execution plans instead of all. The use of many small - dictionaries save space, load quickly. Due to compression, smaller size of intermediate results, less I/O operation required and less buffer misses occurs. While in query optimization selection of randomized algorithm with enhancement consider fewer execution plans instead of all plans. This reduce query execution time. We conclude that the use of compression and query optimization improve the performance of database.