انواع کتب حدیث: لفظی و معنوی موزونیت

The obeisance of Holy Prophet (S. A. W) is the path of forgiveness and essential component of faith. Therefore, the series of preservations of, (RA) Sahabah by continued is (صلى الله عليه وسلم) Prophet Holy of actions and sayings the followers of Ṣaḥābah and Scholars of the Ummah. For worldly and eternal saving, disciplined efforts were carried out in order to preserve this series. This methodology of preservation with extreme care and technique is exemplary. The process for collection of Hadith was initiated and shaped into books and volumes. It is due to the dignified status of Hadith that Allah created such individuals who preserved the sayings of Holy Prophet (ﷺ) with religious fervor, zeal, honesty and great care. In this article meaningful analysis has been given for such important terminologies which convey technically internal characteristics of the series of books and are a great source of literary beauty. In this connection, terminologies and their meanings represent reflection of each other. The basis of these terminologies is not only on estimated ideas but on the literary and intellectual facts. These are not only according to the time and age but also historical and geographical according to the need of hour and circumstances. From Muḥaddithīn’s point of view, these collections have certain benefits and purposes due to which they kept naming them. The brief, simple and understandable words of terminologies are common; however, their purpose is not common. It is distinguished and extra ordinary. The words used in terminologies are not special but purpose is not to express application. Their contextual meaning is taken under consideration instead of the literal one.

Self-Prediction of Performance Metrics for Dbms Workload

Database Management System (DBMS) workload involves homogenous as well as heterogeneous data and concurrent users. Humans are incapable to manage the versatile data and dynamic behavior of DBMS workload. There is a need of fast computations of current server’s loads and requirements, AI algorithms and machine learning techniques. Autonomic computing technology using types of workload Decision Support System (DSS) or Online Transaction Processing (OLTP) and its performance requirement can help servers, adaptation of the workloads. If we know the type of workload, we can design such systems that predict the identified workload performance and adapt the changes in the behavior of the workload. For managing the workload, we have to face number of problems for the DBMS to better perform. Before executing, we can predict and control the workload to tune the DBMS. Predicting performance of the workload is important for tuning a DBMS and makes the DBMS aware of itself making it autonomic. The optimizer and DBMS can tune itself accordingly. Evolving behavior of workload can be handled by making the system adaptive. We have developed a framework called Autonomic Workload Performance Predictor (AWPP) for predicting the performance of the workload making it adaptive to the changing behavior of the workload. Case-based reasoning approach is applied and results are compared with other well-known machine learning techniques to observe the accuracy and effectiveness and significance of AWPP framework. MySQL database management system is being used to execute different benchmark workload to validate the proposed workload performance prediction framework. For training and testing TPC- H and TPC-C like queries are used as our representative workload. We have taken the various benchmark workloads of DSS and OLTP for experimentation. CBR approach produced effective, accurate and significant results while predicting the performance of workload using the information available before executing a workload and adapting the workload on evolution. These predictions will be helpful for optimizer and DBMSs algorithms as well as for workload management, capacity planning, system sizing.