How does query processing and query optimization related?

 Query processing and optimization are a fundamental, if not critical, part of any DBMS. To be utilized effectively, the results of queries must be available in the timeframe needed by the submitting user—be it a person, robotic assembly machine, or even another distinct and separate DBMS. 

OR,

Maintaining large databases with high performance is called database query optimization. A distributed database is a group of autonomous cooperating centralized databases, in that query processing requires transferring data from one system to another through a communication network. In the query optimization process, the cost is always associated with each and every query execution plan (QEP).



Comments

Popular posts from this blog

What are different steps used in JDBC? Write down a small program showing all steps.

Explain Parallel Efficiency of MapReduce.

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?