MySQL Workbench exercise Refer to the film, actor, and film_actor tables of the Sakila database. This exercise is based

[answerhappygod]

MySQL Workbench exercise Refer to the film, actor, and
film_actor tables of the Sakila database. This exercise is based on
the initial Sakila installation. If you have altered these tables
or their data, your results may be different. Do the following in
MySQL Workbench: Enter the following statements: USE sakila; SELECT
last_name, first_name, ROUND(AVG(length), 0) AS average FROM actor
INNER JOIN film_actor ON film_actor.actor_id = actor.actor_id INNER
JOIN film ON film_actor.film_id = film.film_id WHERE title = "ALONE
TRIP" GROUP BY last_name, first_name ORDER BY average; Highlight
the SELECT query. In the main menu, select Query > Explain
Current Statement. In the Display Info box, highlighted in red
below, select Data Read per Join. Workbench displays the following
execution plan: Image is a screenshot of Workbench. The SELECT
query described in the lab instructions is highlighted. Below the
SELECT query is a flowchart diagram, representing an execution plan
for the SELECT query. The flowchart contains boxes and diamonds
labeled 1 through 7. Box 1 has four labels: 1 row, Non-Unique Key
Lookup, film, and idx_title. Box 2 has four labels: 5 rows,
Non-Unique Key Lookup, film_actor, and idx_fk_film_id. Diamond 3
has two labels: 5 rows, and nested loop. Arrows from boxes 1 and 2
point to diamond 3. Box 4 has four labels: 1 row, Unique Key
Lookup, actor, and PRIMARY. Diamond 5 has two labels: 5 rows, and
nested loop. Arrows from diamond 3 and box 4 point to diamond 5.
Box 6 has two labels: GROUP, and tmp table. Box 7 has two labels:
ORDER and filesort. An arrow from box 6 points to box 7. An arrow
from box 7 points to an unnumbered box with two labels: Query cost
3.07, and query_block #1. The execution plan depicts the result of
EXPLAIN for the SELECT query. The execution plan has seven steps,
corresponding to the red numbers on the screenshot: Access a single
film row using the idx_title index on the title column. Access
matching film_actor rows using the idx_fk_film_id index on the
film_id foreign key. Join the results using the nested loop
algorithm. Access actor rows via the index on the primary key. Join
actor rows with the prior join result using the nested loop
algorithm. Store the result in a temporary table and compute the
aggregate function. Sort and generate the result table. Refer to
MySQL nested loop documentation for an explanation of the nested
loop algorithm. Now, replace = in the WHERE clause with < and
generate a new execution plan. Step 1 of the execution plan says
Index Range Scan. The index scan accesses all films with titles
preceding "ALONE TRIP", rather than a single film. Finally, replace
< in the WHERE clause with > and generate a third execution
plan. Step 1 of the execution plan says Full Table Scan and
accesses actor rather than film. zyLab coding In the zyLab
environment, write EXPLAIN statements for the three queries, in the
order described above. Submit the EXPLAIN statements for testing.
The zyLab execution plans do not exactly match the Workbench
execution plans, since this lab uses a subset of film, actor, and
film_actor rows from the Sakila database. NOTE: In submit-mode
tests that generate multiple result tables, the results are merged.
Although the tests run correctly, the results appear in one table.
404476.1671086.qx3zqy7 LAB ACTIVITY 1.9.1: LAB - Query execution
plans (Sakila)