It may be advantageous to keep the join as a materialized view if a parallel data-store is used to hold two relationsr and s and we need to join r and s. What are the advantages and disadvantages in terms of total throughput, space usage, and user query response time?

How is a clustered index made, and what are the main differences between a clustered index and a sparse index?

Consider the following scenario: there is only one vacant slot in a class and two students want to enroll. Which aspect of a database prevents them from sharing a single seat?

Give an example of a query for which each of the three partitioning approaches would produce the fastest response, notably round-robin, hash partitioning, and range partitioning.

Describe how HASH JOIN is currently implemented in version 12 of Postgres (or any compatible version)

Assume a relation 'R' having 200 records. These records are stored in blocks having block factor as 20. Consider another relation 'S' having 120 records and all these records are stored in 30 blocks. These two tables have to be joined using nested loop join algorithm. At any instance main memory can hold exactly one block of R and one block of S. What are the total number of block access required to join R and S ?

Convert this ER model to a list of tablesProvide the queries that implement the database

How many queries remain before you can determine whether database as a service is the optimal solution for your library's needs?

A link like the second course may be built from a collection of many-to-one connections. Do the main and foreign key restrictions impose the many-to-one cardinality limitation on the relation? What makes you believe that is?

Keeping the join as a materialized view may be handy if a parallel data store is utilized to hold two relations r and s and we need to connect them. In terms of total throughput, space use, and response time to user requests, what are the advantages and costs of this approach?