Crowdly

Non-correlated subquery

Scalar subquery

Correlated subquery

Which operator is used ...

(match the appropriate)

to check if a subquery returns no rows?

to compare for equality a single value with the result of a subquery?

to compare by more/less a value with the result of a subquery that returns a single column and a single row?

Which type of subquery is executed once for the entire outer query?

Nested subquery

It will not bring the customers that they have never put an order.

Non-correlated subquery

Scalar subquery

Correlated subquery

Assuming that we have 2 tables - customers and orders:

Assuming the following query

select * from customers join orders on orders.customer_id = customers.customer_id;

Which of the following is not true about NATURAL JOINs?

If columns having same names have different data types, it returns error

Natural joins are not based on primary/foreign keys

It selects rows from the two tables having different values in the matched columns

Natural join is based on all columns in two tables having same name

Which of the following is NOT a commonly accepted rule for joining multiple tables?

It is recommended that aliases be keywords to keep the statement uniform throughout the query

Put join conditions before other conditions in the WHERE clause when using implicit join

It is recommended that joins between tables are based on Primary/Foreign keys

Any table listed in a join condition MUST exist in the FROM clause when using implicit join

A UNION query is which of the following?

Combines the output from multiple queries and must include the same number of columns

Combines the output from multiple queries and does not include the same number of columns

Combines the output from no more than two queries and does not include the same number of columns

Combines the output from no more than two queries and must include the same number of columns

What type of join is needed when you wish to include rows that do not have matching values?

CROSS JOIN

OUTER JOIN

INNER JOIN

SELF JOIN

Which of the following is true about a group function?

Group functions ignore null values

DISTINCT keyword makes a group function consider duplicate values

Group functions operate on sets of rows to produce multiple results per group

Which SELECT statement brings both the customers with and those without an order?

Assuming that we have 2 tables - customers and orders:

select * from customers left join orders on orders.customer_id = customers.customer_id where orders.order_id is not null;

select * from customers left join orders on orders.customer_id = customers.customer_id;

select * from customers join orders on orders.customer_id = customers.customer_id;

select * from customers left join orders on orders.customer_id = customers.customer_id where orders.order_id is null;