Oracle 1z0-082 Exam Dumps & Practice Test Questions
Question No 1:
After creating the user HR and executing the command:
GRANT CREATE SESSION TO hr WITH ADMIN OPTION;
Which four actions can HR perform? (Choose four.)
A. Revoke the CREATE SESSION privilege from other users
B. Revoke the CREATE SESSION privilege from user HR
C. Log in to the database instance
D. Grant the CREATE SESSION privilege with ADMIN OPTION to other users
E. Execute DDL statements in the HR schema
F. Execute DML statements in the HR schema
Correct Answer: A, C, D, F
Explanation:
Let's break down what happens when you execute the command GRANT CREATE SESSION TO hr WITH ADMIN OPTION;.
The GRANT CREATE SESSION privilege allows a user to log in to the database. The WITH ADMIN OPTION part allows the user to pass on this privilege to other users. Now, we’ll look at each option in detail:
A. Revoke the CREATE SESSION privilege from other users
This is correct. Since HR has been granted the CREATE SESSION privilege WITH ADMIN OPTION, HR can grant the CREATE SESSION privilege to other users and, by extension, can revoke the privilege from other users they have granted it to. The WITH ADMIN OPTION allows HR to manage this privilege for others.
B. Revoke the CREATE SESSION privilege from user HR
This is incorrect. HR cannot revoke the CREATE SESSION privilege from themselves. The WITH ADMIN OPTION gives HR the ability to grant and revoke the privilege for others, but not for themselves.
C. Log in to the database instance
This is correct. The CREATE SESSION privilege allows a user to connect to the database instance. Since HR has been granted this privilege, HR can log in to the database.
D. Grant the CREATE SESSION privilege with ADMIN OPTION to other users
This is correct. The WITH ADMIN OPTION allows HR to grant the CREATE SESSION privilege to other users, and since the option is specified, HR can also pass the privilege on to others, with the same administrative power to grant and revoke.
E. Execute DDL statements in the HR schema
This is incorrect. Granting CREATE SESSION does not automatically allow HR to execute DDL (Data Definition Language) statements like CREATE, ALTER, or DROP in their schema. To perform DDL actions, HR would need additional privileges like CREATE TABLE, ALTER, DROP, etc.
F. Execute DML statements in the HR schema
This is correct. While granting CREATE SESSION doesn’t directly provide DML (Data Manipulation Language) privileges, HR can execute DML statements such as SELECT, INSERT, UPDATE, and DELETE in their own schema, as those privileges are typically granted by default to the user upon creation.
In conclusion, the actions HR can perform based on the GRANT CREATE SESSION with the WITH ADMIN OPTION are:
A. Revoke the CREATE SESSION privilege from other users
C. Log in to the database instance
D. Grant the CREATE SESSION privilege with ADMIN OPTION to other users
F. Execute DML statements in the HR schema
Question No 2:
Which two statements are true about the WHERE and HAVING clauses in a SELECT statement? (Choose two.)
A. Aggregating functions and columns used in HAVING clauses must be specified in the SELECT list of a query.
B. WHERE and HAVING clauses can be used in the same statement only if applied to different table columns.
C. The HAVING clause can be used with aggregating functions in subqueries.
D. The WHERE clause can be used to exclude rows before dividing them into groups.
E. The WHERE clause can be used to exclude rows after dividing them into groups.
Correct Answer: D, C
Explanation:
The WHERE and HAVING clauses are both used to filter data in SQL queries, but they serve different purposes and work at different stages in the query execution process. Understanding their differences is crucial for forming accurate queries.
D. The WHERE clause can be used to exclude rows before dividing them into groups: This statement is correct because the WHERE clause filters rows before any grouping or aggregation occurs. It is used to limit the data that will be grouped or aggregated. For example, if you are using GROUP BY, the WHERE clause will first filter the rows to determine which ones are included in the aggregation process.
For example:
In this query, the WHERE clause filters employees with salaries greater than 50,000 before any grouping by department occurs.
C. The HAVING clause can be used with aggregating functions in subqueries: This statement is also correct. The HAVING clause can be used to filter aggregated results, even in subqueries. The HAVING clause works with aggregated data, typically used in conjunction with GROUP BY. It can also be employed within subqueries when aggregation is involved.
For example:
Here, the HAVING clause filters groups that have more than five employees after the COUNT aggregation.
The other options are incorrect for the following reasons:
A. Aggregating functions and columns used in HAVING clauses must be specified in the SELECT list of a query: This is not true. Aggregating functions used in the HAVING clause do not need to be in the SELECT list. The HAVING clause works with aggregated data, but it doesn't require the columns to appear in the SELECT list. The HAVING clause filters the result after aggregation, not necessarily limiting which columns are selected.
B. WHERE and HAVING clauses can be used in the same statement only if applied to different table columns: This is incorrect. Both the WHERE and HAVING clauses can be used in the same query, but they do not need to apply to different columns. The WHERE clause filters rows before grouping, while the HAVING clause filters groups after aggregation. They can be applied to the same column, but they operate at different stages in the query.
E. The WHERE clause can be used to exclude rows after dividing them into groups: This is incorrect because the WHERE clause is applied before grouping. If you want to filter data after groups have been formed, you would use the HAVING clause. The WHERE clause cannot filter after aggregation.
In summary, D and C are correct because the WHERE clause filters rows before grouping, and the HAVING clause can be used with aggregating functions in subqueries to filter grouped data.
Question No 3:
Which two statements about UNDO and REDO in Oracle are true?
A. The generation of UNDO generates REDO
B. DML modifies Oracle database objects and only generates UNDO
C. The generation of REDO generates UNDO
D. DML modifies Oracle database objects and only generates REDO
E. DML modifies Oracle database objects and generates UNDO and REDO
Correct Answer: A, E
Explanation:
In Oracle databases, UNDO and REDO are fundamental concepts that help maintain data consistency, recover from failures, and ensure that changes made to the database can either be rolled back or applied in case of a crash. Let's break down the statements to understand which ones are true.
A. The generation of UNDO generates REDO: This statement is true. When Oracle generates UNDO data for a change (e.g., during a DML operation like an update), it also generates REDO data. UNDO is responsible for reverting changes, while REDO logs ensure changes are persistent if a crash happens before the transaction is committed. These two are closely tied: changes that can be undone must also be redo-able in the event of a failure.
B. DML modifies Oracle database objects and only generates UNDO: This statement is false. DML operations such as INSERT, UPDATE, and DELETE do indeed modify database objects, but they generate both UNDO and REDO. UNDO allows changes to be rolled back, while REDO ensures changes can be reapplied in case of a recovery.
C. The generation of REDO generates UNDO: This statement is false. REDO and UNDO are independent in terms of generation. REDO logs are generated to ensure that committed changes can be replayed in the event of a failure, but they don't inherently generate UNDO. UNDO is created to allow rollback of operations, and REDO does not control or create this.
D. DML modifies Oracle database objects and only generates REDO: This statement is false. As explained earlier, DML operations generate both REDO and UNDO. REDO logs record the changes that need to be persisted, while UNDO logs are used for rolling back those changes.
E. DML modifies Oracle database objects and generates UNDO and REDO: This statement is true. Every DML operation generates both UNDO and REDO. The UNDO logs are created to allow rollback of the changes if necessary, and REDO logs ensure that the changes can be replayed in case of a database crash or other failure.
Thus, the correct answers are A and E.
Question No 4:
How should you execute the command so that only SCOTT in BOSTON_DB can access the SCOTT schema in DALLAS_DB?
A. as SCOTT in DALLAS_DB
B. as SCOTT in BOSTON_DB
C. as SCOTT in BOSTON_DB and SYS in DALLAS_DB
D. as SYS in both the databases
E. as SCOTT in both the databases
Correct Answer: B
Explanation:
To set up a database link that allows the SCOTT user in BOSTON_DB to access the SCOTT schema in DALLAS_DB, the user SCOTT in BOSTON_DB needs to be able to create a database link to connect to DALLAS_DB using the credentials provided in the CREATE DATABASE LINK command. Let’s break down the reasoning for each option:
A. as SCOTT in DALLAS_DB:
This is not the correct choice because the CREATE DATABASE LINK command is executed on the database where the link is being created (in this case, BOSTON_DB), not from DALLAS_DB. The command needs to be executed by the user SCOTT in BOSTON_DB, not DALLAS_DB.
B. as SCOTT in BOSTON_DB:
This is the correct choice. The CREATE DATABASE LINK command must be run from BOSTON_DB (the local database where the link will reside). The SCOTT user in BOSTON_DB creates the database link that connects to DALLAS_DB using the dallas_db service name as defined in the tnsnames.ora file. By specifying the connection details in the command, SCOTT in BOSTON_DB is granted the ability to access the SCOTT schema in DALLAS_DB through the created database link. The CREATE DATABASE LINK command will use the credentials provided (SCOTT/TIGER) to authenticate the user in DALLAS_DB.
C. as SCOTT in BOSTON_DB and SYS in DALLAS_DB:
This is not correct. You do not need to be SYS in DALLAS_DB to create a database link from BOSTON_DB to DALLAS_DB. The SCOTT user in BOSTON_DB can create the link without needing SYS privileges in DALLAS_DB.
D. as SYS in both the databases:
This option is also incorrect because SYS privileges are not required for creating a database link in this case. The SCOTT user has sufficient privileges to create the database link. While SYS could theoretically perform the action, it’s not necessary for this task.
E. as SCOTT in both the databases:
While SCOTT is the user in both databases, it is not required to be logged into DALLAS_DB to create the database link. The CREATE DATABASE LINK command should be executed in BOSTON_DB. The user SCOTT in BOSTON_DB will create the database link to DALLAS_DB, so logging in as SCOTT in both databases is unnecessary.
In conclusion, the correct answer is B, as the command must be executed by SCOTT in BOSTON_DB to establish the database link that allows access to the SCOTT schema in DALLAS_DB.
Question No 5:
Which three statements are true about the DESCRIBE command? (Choose three.)
A. It displays the PRIMARY KEY constraint for any column or columns that have that constraint.
B. It can be used from SQL Developer.
C. It displays the NOT NULL constraint for any columns that have that constraint.
D. It can be used to display the structure of an existing view.
E. It displays all constraints that are defined for each column.
F. It can be used only from SQL*Plus.
Correct Answer: B, C, D
Explanation:
The DESCRIBE command in Oracle SQL is primarily used to display the structure of a database object, such as a table, view, or other schema objects. It helps you understand the column names, data types, and other properties of the object. However, the DESCRIBE command does not display all constraints or detailed information about object relationships unless certain conditions are met.
Option B (It can be used from SQL Developer) is correct. The DESCRIBE command can indeed be executed in various Oracle database client tools, including SQL Developer, SQL*Plus, and others. SQL Developer provides a GUI interface where the DESCRIBE command can be executed in the SQL worksheet to view the structure of tables or views.
Option C (It displays the NOT NULL constraint for any columns that have that constraint) is also correct. The DESCRIBE command will show whether a column is defined as NOT NULL. When you execute DESCRIBE on a table or view, the NULL column attribute is displayed. If a column is defined as NOT NULL, this will be reflected in the output as "NOT NULL" under the "Null" column. This is a useful feature for understanding the constraints on individual columns.
Option D (It can be used to display the structure of an existing view) is correct as well. The DESCRIBE command can be used to display the structure of not only tables but also views. When used on a view, the DESCRIBE command will display the columns, their data types, and other properties related to the view’s structure. It does not display the actual query definition behind the view, but rather the columns that make up the view.
Option A (It displays the PRIMARY KEY constraint for any column or columns that have that constraint) is incorrect. The DESCRIBE command does not display constraints such as PRIMARY KEY, FOREIGN KEY, or other integrity constraints for columns. It only shows the column names, data types, length, and whether the column is nullable or not. To see primary key constraints, you would need to query the data dictionary views, such as USER_TAB_COLUMNS or USER_CONS_COLUMNS.
Option E (It displays all constraints that are defined for each column) is incorrect. As mentioned, the DESCRIBE command does not display all constraints (such as PRIMARY KEY, FOREIGN KEY, or CHECK). To view constraints, you would need to query the ALL_TAB_COLUMNS or USER_TAB_COLUMNS views, or use other commands like SELECT on the DBA_CONSTRAINTS or USER_CONSTRAINTS views.
Option F (It can be used only from SQLPlus) is incorrect. The DESCRIBE command is not limited to SQLPlus; it can also be used in tools like SQL Developer, Oracle SQLcl, and other Oracle clients that support SQL execution. Therefore, it is not exclusive to SQL*Plus.
In conclusion, the correct statements about the DESCRIBE command are B, C, and D. These reflect its ability to show basic column information, the NOT NULL constraint, and the structure of tables and views.
Question No 6:
Which query should be used to display the first name and due amount as 5% of the credit limit for customers whose income level is provided, and where the due amount is not null?
A. SELECT cust_first_name, cust_credit_limit * .05 AS DUE_AMOUNT FROM customers WHERE cust_income_level IS NOT NULL AND due_amount IS NOT NULL;
B. SELECT cust_first_name, cust_credit_limit * .05 AS DUE_AMOUNT FROM customers WHERE cust_income_level != NULL AND cust_credit_level != NULL;
C. SELECT cust_first_name, cust_credit_limit * .05 AS DUE_AMOUNT FROM customers WHERE cust_income_level <> NULL AND due_amount <> NULL;
D. SELECT cust_first_name, cust_credit_limit * .05 AS DUE_AMOUNT FROM customers WHERE cust_income_level != NULL AND due_amount != NULL;
E. SELECT cust_first_name, cust_credit_limit * .05 AS DUE_AMOUNT FROM customers WHERE cust_income_level IS NOT NULL AND cust_credit_limit IS NOT NULL;
Correct Answer: A
Explanation:
To form the correct query, we need to focus on the following requirements:
The income level should have a value, meaning it should not be null.
The due amount should also not be null.
The due amount is to be calculated as 5% of the credit limit for each customer.
Let's review the options based on these requirements:
A: This query is correct. It uses the condition cust_income_level IS NOT NULL, which checks for customers whose income level is not null. It also ensures that due_amount IS NOT NULL, meaning only those customers who have a valid due amount will be selected. This query is syntactically correct and meets all the specified conditions. The expression cust_credit_limit * .05 AS DUE_AMOUNT correctly calculates 5% of the credit limit.
B: This query uses cust_income_level != NULL and cust_credit_level != NULL. The != operator should not be used for checking null values in SQL. The proper way to check for null is using IS NOT NULL, so this query will not work correctly. Therefore, B is incorrect.
C: Similar to B, this query uses cust_income_level <> NULL, which is not the correct syntax for checking null values in SQL. The correct approach would be cust_income_level IS NOT NULL. Therefore, C is incorrect.
D: This query uses cust_income_level != NULL to check for non-null values, which is incorrect syntax for null checks in SQL. The correct operator is IS NOT NULL, not !=. Therefore, D is incorrect.
E: While this query correctly checks if cust_income_level IS NOT NULL, it checks cust_credit_limit IS NOT NULL instead of due_amount IS NOT NULL. The question asks for customers where the due amount is not null, not the credit limit. Since this does not fulfill the full requirement, E is incorrect.
In conclusion, the correct query is A, as it properly checks that both the income level is provided and the due amount is not null, while also calculating the due amount as 5% of the credit limit.
Question No 7:
Which two are true about data type conversions involving the QTY_SOLD and INVOICE_DATE columns in query expressions? (Choose two.)
A. CONCAT(qty_sold, invoice_date): requires explicit conversion
B. invoice_date = '15-march-2019': uses implicit conversion
C. invoice_date > '01-02-2019': uses implicit conversion
D. qty_sold BETWEEN '101' AND '110': uses implicit conversion
E. qty_sold = '0554982': uses implicit conversion
Correct Answer: A, D
Explanation:
In Oracle, data type conversions are important when different data types are used in expressions or conditions. The two types of conversions that can occur are implicit (handled automatically by Oracle) and explicit (where the user has to specify the conversion). Let's break down each option:
A. CONCAT(qty_sold, invoice_date): requires explicit conversion
This statement is true. The CONCAT function is used to join strings, but in this case, qty_sold is a NUMBER and invoice_date is a DATE. Oracle does not automatically convert these data types to VARCHAR for string concatenation. Therefore, explicit conversion is required, such as using the TO_CHAR function to convert both the NUMBER and DATE columns to strings before concatenating them. The correct expression would look like:
CONCAT(TO_CHAR(qty_sold), TO_CHAR(invoice_date))B. invoice_date = '15-march-2019': uses implicit conversion
This statement is false. While the NLS_DATE_FORMAT is set to DD-MON-RR, Oracle does not implicitly convert a string to a DATE in this comparison. In this case, the date string '15-march-2019' would need to be explicitly converted to a DATE using the TO_DATE function, like this:
invoice_date = TO_DATE('15-march-2019', 'DD-MON-YYYY')C. invoice_date > '01-02-2019': uses implicit conversion
This statement is false. Similar to option B, Oracle would not implicitly convert the string '01-02-2019' to a DATE. The correct way to compare this would require explicit conversion using TO_DATE, like:
invoice_date > TO_DATE('01-02-2019', 'DD-MM-YYYY')D. qty_sold BETWEEN '101' AND '110': uses implicit conversion
This statement is true. In this case, qty_sold is a NUMBER, and the string values 101' and '110' are implicitly converted by Oracle to NUMBER for comparison purposes. Oracle automatically converts string literals to numbers when they are used in a BETWEEN condition with a NUMBER column, so implicit conversion happens here.E. qty_sold = '0554982': uses implicit conversion
This statement is false. Although the string '0554982' might look like a number, it is actually a string. Oracle will not automatically convert a string to a NUMBER in this comparison unless it is explicitly cast. To compare this correctly, an explicit conversion should be performed, such as using TO_NUMBER:
qty_sold = TO_NUMBER('0554982')
In summary, A and D are correct because they involve explicit conversion (for concatenation) and implicit conversion (for the BETWEEN condition) respectively.
Question No 8:
Which three are types of segments in an Oracle Database? (Choose three.)
A. undo
B. index
C. stored procedures
D. sequences
E. tables
F. clusters
Correct Answer: A, B, E
Explanation:
In an Oracle Database, a segment is a portion of storage allocated to hold specific types of data within a database. Segments play a crucial role in the physical storage architecture of Oracle databases and are associated with different types of objects that hold or organize data. Understanding the types of segments in an Oracle Database is key to managing storage effectively and ensuring database performance.
Benefit of Option A: The undo segment is crucial in Oracle databases for managing transactions and maintaining database consistency. When changes are made to the database, Oracle uses undo segments to store the previous values of modified data. This allows Oracle to undo changes when a transaction is rolled back or when a failure occurs, ensuring that the database can return to a consistent state. The undo segment helps to manage transaction rollbacks, recover from failures, and support read consistency. Without undo segments, it would be impossible to revert changes or ensure that users have consistent views of data.
Benefit of Option B: The index segment is used to store index structures in Oracle. An index improves the speed of data retrieval operations by providing a quick lookup mechanism. For instance, when querying a large table, an index can significantly reduce the search time for specific rows by maintaining a sorted structure of values. Index segments are created when an index is defined on a table and are used to enhance query performance. These segments are automatically managed by Oracle and are tied directly to the table they index. They help improve overall database efficiency by reducing I/O operations.
Benefit of Option E: The table segment is one of the most common types of segments in Oracle databases. It stores the actual data in rows and columns, as defined by the structure of the table. When a table is created, Oracle allocates a table segment to hold the data for that table. Tables are the fundamental data storage structures in a relational database, and the table segment is where all the data rows for the table are stored. The efficient management of table segments is crucial for maintaining optimal database performance and for ensuring that queries and data retrieval operations are fast and efficient.
Why the Other Options Are Incorrect:
Option C (stored procedures) are not types of segments. Stored procedures are PL/SQL code blocks that are stored and executed within the database but do not correspond to specific storage segments in the same way that tables, indexes, or undo segments do.
Option D (sequences) are also not types of segments. A sequence in Oracle is an object that generates unique numbers, typically used for primary key values, but it does not have a corresponding segment. Sequences are managed differently in the database.
Option F (clusters) refer to a logical storage structure in Oracle that allows multiple tables to be stored together based on shared columns. While clusters have storage implications, they are not categorized as a segment type but rather as a mechanism for managing how tables are physically stored together.
Therefore, the correct answers are A, B, and E, as they all represent true segments in Oracle Database.
Question No 9:
Which two of the following statements are correct when using the INTERSECT operator in compound queries? (Choose two.)
A. Column names in each SELECT in the compound query can be different
B. The number of columns in each SELECT in the compound query can be different
C. Reversing the order of the intersected tables can sometimes affect the output
D. INTERSECT returns rows common to both sides of the compound query
E. INTERSECT ignores NULLs
Correct Answer: D, E
Explanation:
The INTERSECT operator in SQL is used to combine the results of two SELECT queries and return only the rows that appear in both result sets. It is one of the set operators, alongside others like UNION and EXCEPT, and is essential for extracting the intersection of two datasets. Let's explore each statement to understand why D and E are the correct choices.
D. INTERSECT returns rows common to both sides of the compound query
This statement is true because the main function of the INTERSECT operator is to return only the rows that exist in both SELECT queries in the compound query. When two SELECT statements are combined with INTERSECT, only the rows that appear in both result sets will be returned. For instance, if Query 1 returns rows A, B, and C, and Query 2 returns rows B, C, and D, the result of the INTERSECT would be rows B and C, as those are common to both queries.
E. INTERSECT ignores NULLs
This statement is also correct. In SQL, the INTERSECT operator does not include rows that contain NULL values unless both queries return the same NULL value for the same column. INTERSECT treats NULLs as special values, and if one of the queries contains a NULL and the other does not, that row will not be included in the result set. This is an important behavior to note when working with INTERSECT, as it differs from some other SQL operations that may treat NULLs differently.
Now, let's look at why the other options are incorrect:
A. Column names in each SELECT in the compound query can be different
This statement is false because when using the INTERSECT operator, the column names in both SELECT queries must be either identical or match in terms of their data types. While the names don't need to be exactly the same, the number and type of columns must align.
B. The number of columns in each SELECT in the compound query can be different
This statement is also false. Both SELECT queries in an INTERSECT operation must return the same number of columns. If the number of columns differs, SQL will throw an error, as it requires the queries to be of equal structure to compare the rows.
C. Reversing the order of the intersected tables can sometimes affect the output
This statement is incorrect because the INTERSECT operator is symmetric. This means that the order of the SELECT queries does not affect the result. The same rows will be returned regardless of which query appears first or second.
Thus, the correct answers are D and E because these statements accurately describe the behavior of the INTERSECT operator in SQL.
Question No 10:
Which two statements are accurate regarding single row functions? (Choose two.)
A. MOD: returns the quotient of a division operation
B. FLOOR: returns the smallest integer greater than or equal to a specified number
C. TRUNC: can be used with NUMBER and DATE values
D. CONCAT: can be used to combine any number of values
E. CEIL: can be used for positive and negative numbers
Correct Answer: C, E
Explanation:
Single row functions in SQL are functions that operate on a single row of data at a time and return a single result for each row. Let’s break down each statement:
A. MOD: returns the quotient of a division operation
This is incorrect. The MOD function in SQL returns the remainder of a division operation, not the quotient. For example, MOD(10, 3) would return 1, as 10 divided by 3 leaves a remainder of 1.
B. FLOOR: returns the smallest integer greater than or equal to a specified number
This is incorrect. The FLOOR function returns the largest integer less than or equal to a specified number. For example, FLOOR(7.8) would return 7, and FLOOR(-7.8) would return -8. It rounds the number down towards the nearest integer.
C. TRUNC: can be used with NUMBER and DATE values
This is correct. The TRUNC function can be used with both NUMBER and DATE values. For numbers, it truncates the number to a specified decimal place. For dates, it removes the time portion and returns the date at midnight (or a truncated version of the date, depending on the specified format).
D. CONCAT: can be used to combine any number of values
This is incorrect. The CONCAT function in SQL is used to combine two strings or values at a time. To combine more than two values, you would need to use CONCAT multiple times or use || (concatenation operator) depending on the database.
E. CEIL: can be used for positive and negative numbers
This is correct. The CEIL function returns the smallest integer greater than or equal to the specified number. It works for both positive and negative numbers. For example, CEIL(4.2) would return 5, and CEIL(-4.2) would return -4.
Thus, the correct answers are C and E, as these are the accurate statements regarding the usage of single row functions in SQL.
