Final answer:
To provide a physical query plan, estimate the cost and cardinality, and suggest alternate query plans with indexes.
The query involves joining three tables without indexes, leading to a high computational cost. Estimated costs could only be provided theoretically. Optimizing the query with indexes on Book.author and Checkout.sid would likely reduce the execution cost significantly.
Step-by-step explanation:
To provide a physical query plan, we can use the information given about the number of records and pages in each table. Based on the query, we can estimate the cost of the plan by considering the number of pages that need to be accessed and joined. The cardinality of the result can be estimated by considering the selectivity of the conditions in the query.
For the given query, an alternate query plan could involve creating indexes on the 'author' column in the 'Book' table and the 'age' column in the 'Student' table. With these indexes, the database can use an index scan instead of a table scan, reducing the number of pages accessed.
To compute the cost of the new plan, we will need to estimate the number of pages accessed and joined for each table. We can then calculate the total cost based on these estimates.
The query involves joining three tables without indexes, leading to a high computational cost. Estimated costs could only be provided theoretically. Optimizing the query with indexes on Book.author and Checkout.sid would likely reduce the execution cost significantly.
The provided query implies a join across three tables in a database: Student, Book, and Checkout. To create a physical query plan without indexes and where data is not sorted, a common approach would be a series of nested-loop joins. Without indexes, the data pages of each table would need to be accessed sequentially, which increases the computational cost significantly due to the number of records and pages involved.
An estimated cost for such a query would involve reading all the pages for each table and the associated processing. The cardinality of the result would be determined by the number of records fulfilling all the conditions of the query, which can vary.
To optimize this, creating indexes on the Book.author and Checkout.sid columns could be helpful. This would allow the database to quickly filter records in the Book table by the specific author and to efficiently match students with their checkouts in the Checkout table. An alternative query plan could then use these indexes for faster lookups, significantly reducing the cost associated with the query execution.