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NEW QUESTION: 1
Which two statements are true when row-archival management is enabled? (Choose two.)
A. Visibility of the ORA_ARCHIVE_STATEcolumn is controlled by the ROW ARCHIVAL VISIBILITY session parameter.
B. The ROW ARCHIVAL VISIBILITYsession parameter defaults to all rows.
C. The ORA_ARCHIVE_STATEcolumn is visible if it is referenced in the selectlist of a query.
D. The ORA_ARCHIVE_STATEcolumn is updated manually or by a program that can reference activity tracking columns, to indicate that a row is no longer considered active.
E. The ORA_ARCHIVE_STATEcolumn is updated automatically by the database based on activity tracking columns, to indicate that a row is no longer considered active.
Answer: A,C
Explanation:
Explanation/Reference:

NEW QUESTION: 2
View the Exhibit of the Department Security tree. Using the Row Security Permission List, the operator is granted access to department 13000. How would you restrict access to department 21000 for this operator?

A. Remove the department from the department tree.
B. Assign this department "No Access" in the Security by Permission List.
C. Inactivate the department in the department table.
D. Run the Refresh SJT_CLASS_ALL process.
E. Assign this department the Access code value of "No Access" in the Security by
Department Tree page.
F. You do not need to do anything because the employee was granted access to department 13000.
Answer: E

NEW QUESTION: 3
CORRECT TEXT
Problem Scenario 85 : In Continuation of previous question, please accomplish following activities.
1. Select all the columns from product table with output header as below. productID AS ID code AS Code name AS Description price AS 'Unit Price'
2. Select code and name both separated by ' -' and header name should be Product
Description'.
3. Select all distinct prices.
4 . Select distinct price and name combination.
5 . Select all price data sorted by both code and productID combination.
6 . count number of products.
7 . Count number of products for each code.
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Select all the columns from product table with output header as below. productID
AS ID code AS Code name AS Description price AS "Unit Price'
val results = sqlContext.sql(......SELECT productID AS ID, code AS Code, name AS
Description, price AS Unit Price' FROM products ORDER BY ID"""
results.show()
Step 2 : Select code and name both separated by ' -' and header name should be "Product
Description.
val results = sqlContext.sql(......SELECT CONCAT(code,' -', name) AS Product Description, price FROM products""" ) results.showQ
Step 3 : Select all distinct prices.
val results = sqlContext.sql(......SELECT DISTINCT price AS Distinct Price" FROM products......) results.show()
Step 4 : Select distinct price and name combination.
val results = sqlContext.sql(......SELECT DISTINCT price, name FROM products""" ) results. showQ
Step 5 : Select all price data sorted by both code and productID combination.
val results = sqlContext.sql('.....SELECT' FROM products ORDER BY code, productID'.....) results.show()
Step 6 : count number of products.
val results = sqlContext.sql(......SELECT COUNT(') AS 'Count' FROM products......) results.show()
Step 7 : Count number of products for each code.
val results = sqlContext.sql(......SELECT code, COUNT('} FROM products GROUP BY code......) results. showQ val results = sqlContext.sql(......SELECT code, COUNT('} AS count FROM products
GROUP BY code ORDER BY count DESC......)
results. showQ