In recent years, Massively Parallel Processors have increasingly been used to manage and query vast amounts of data. Dramatic performance improvements are achieved through distributed execution of queries across many nodes. Query optimization for such system is a challenging and important problem.In this paper we describe the Query Optimizer inside the SQL Server Parallel Data Warehouse product (PDW QO). We leverage existing QO technology in Microsoft SQL Server to implement a cost-based optimizer for distributed query execution. By properly abstracting metadata we can readily reuse existing logic for query simplification, space exploration and cardinality estimation. Unlike earlier approaches that simply parallelize the best serial plan, our optimizer considers a rich space of execution alternatives, and picks one based on a cost-model for the distributed execution environment. The result is a high-quality, effective query optimizer for distributed query processing in an MPP.

Objectives:The Sex Hormone Binding Globulin (SHBG) plays an important role in male infertility. Methods: The present research computationally emphases to SHBG protein with 47 natural phytocompounds using docking studies. Results: From the results showed the interactions between 1KDM protein with 47 phytocompounds, a natural compound chlorogenic acid showed the best glide docking XP score -7.255 kcal/mol and the binding energy value of -47.869 kcal/ mol. Based on the result, the chlorogenic acid and target were run on MD simulations stable at 10 ns. Conclusion: Finally, this study concludes the chlorogenic acid is a suitable drug candidate for infertility.

Managing a combined store consisting of database data and file data in a robust and consistent manner is a challenge for database systems and content management systems. In such a hybrid system, images, videos, engineering drawings, etc. are stored as files on a file server while meta-data referencing/indexing such files is created and stored in a relational database to take advantage of efficient search. In this paper we describe solutions for two potentially problematic aspects of such a data management system: backup/recovery and data consistency. We present algorithms for performing backup and recovery of the DBMS data in a coordinated fashion with the files on the file servers. Our algorithms for coordinated backup and recovery have been implemented in the IBM DB2/DataLinks product [1]. We also propose an efficient solution to the problem of maintaining consistency between the content of a file and the associated metadata stored in the DBMS from a reader's point of view without holding long duration locks on meta-data tables. In the model, an object is directly accessed and edited in-place through normal file system APIs using a reference obtained via an SQL Query on the database. To relate file modifications to meta-data updates, the user issues an update through the DBMS, and commits both file and meta-data updates together.

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