When using GROUP BY, all non-aggregated columns in the SELECT list must be included in the GROUP BY clause. Since DEPARTMENT_NAME is functionally dependent on DEPARTMENT_ID (assuming a typical normalized schema), adding it to GROUP BY is correct and efficient. Using MAX() would work but is conceptually incorrect for a deterministic relationship.

The error explicitly states a parent key violation. If the developer has verified the key exists, the most probable cause in a multi-user database is that the parent row is locked by an uncommitted transaction (e.g., an update or delete). Privilege errors or syntax errors would generate different Oracle error codes.

A LEFT OUTER JOIN (or just LEFT JOIN) returns all rows from the left table (E – employees), and the matched rows from the right table (M – managers). If there is no match (i.e., MANAGER_ID is NULL), the result will still contain the employee row with NULL values for the manager’s columns. An INNER JOIN would exclude employees without managers.

In Oracle, the DEFAULT clause expression (like SYSDATE) is evaluated at the time the INSERT statement is executed, not for each individual row. If the INSERT statement runs for a long time (e.g., inserting millions of rows from a source), all rows get the same SYSDATE value from the start of the statement. This is a key practical nuance of DEFAULT with functions.

The question asks for the result of `COUNT(*)`. The `COUNT(*)` function counts all rows in the table, regardless of NULLs or values in any column. Therefore, it will return the total number of rows, which is 100. The other counts would be: COUNT(list_price)=95, COUNT(NVL(…))=100, COUNT(DISTINCT…)= would depend on other distinct values.

The Oracle optimizer relies on statistics to choose the most efficient execution plan. If statistics are stale or missing, it may incorrectly estimate the cost of an index scan versus a full table scan. Gathering fresh statistics (using DBMS_STATS) is a fundamental first step in diagnosing poor index usage. While bind variable datatypes can influence plans, outdated statistics are a more common root cause.

A unique constraint or index on (email, department_id) allows duplicate emails as long as the department_id is different (e.g., ‘john.doe@co.com’ in department 10 and ‘john.doe@co.com’ in department 20 are unique combinations). It also allows duplicate department_ids with different emails. Option 1 would enforce uniqueness per department only, allowing duplicate emails across departments. Option 2 forbids any duplicate emails. CHECK constraints cannot enforce uniqueness.

All three options correctly compare the year portion of the hire dates. Option 1 uses EXTRACT(YEAR FROM date). Option 2 converts the year to a string using TO_CHAR. Option 3 uses TRUNC(date, ‘YEAR’) to set both dates to the first day of their respective years for comparison. While performance may vary slightly, logically, each one successfully identifies employees and managers hired in the same calendar year.

Set operators (UNION, INTERSECT, MINUS) combine results of queries column-wise. To generate a Cartesian product (all combinations of values from two distinct lists), you need a CROSS JOIN. The correct approach would be: `SELECT DISTINCT d.department_id, j.job_id FROM (SELECT department_id FROM employees) d CROSS JOIN (SELECT job_id FROM employees) j;`. The question’s phrasing highlights a common trap of thinking of this as a set operation problem.

When using GROUP BY, all non-aggregated columns in the SELECT list must be included in the GROUP BY clause. Since DEPARTMENT_NAME is functionally dependent on DEPARTMENT_ID (assuming a typical normalized schema), adding it to GROUP BY is correct and efficient. Using MAX() would work but is conceptually incorrect for a deterministic relationship.0