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NEW QUESTION: 1
DRAG DROP
Overview
Application Overview
Contoso, Ltd., is the developer of an enterprise resource planning (ERP) application.
Contoso is designing a new version of the ERP application. The previous version of the ERP application used SQL Server 2008 R2.
The new version will use SQL Server 2014.
The ERP application relies on an import process to load supplier data. The import process updates thousands of rows simultaneously, requires exclusive access to the database, and runs daily.
You receive several support calls reporting unexpected behavior in the ERP application.
After analyzing the calls, you conclude that users made changes directly to the tables in the database.
Tables
The current database schema contains a table named OrderDetails.
The OrderDetails table contains information about the items sold for each purchase order.
OrderDetails stores the product ID, quantities, and discounts applied to each product in a purchase order.
The product price is stored in a table named Products. The Products table was defined by using the SQL_Latin1_General_CP1_CI_AS collation.
A column named ProductName was created by using the varchar data type. The database contains a table named Orders.
Orders contains all of the purchase orders from the last 12 months. Purchase orders that are older than 12 months are stored in a table named OrdersOld.
The previous version of the ERP application relied on table-level security.
Stored Procedures
The current version of the database contains stored procedures that change two tables.
The following shows the relevant portions of the two stored procedures:
Customer Problems
Installation Issues
The current version of the ERP application requires that several SQL Server logins be set up to function correctly. Most customers set up the ERP application in multiple locations and must create logins multiple times.
Index Fragmentation Issues
Customers discover that clustered indexes often are fragmented. To resolve this issue, the customers defragment the indexes more frequently. All of the tables affected by fragmentation have the following columns that are used as the clustered index key:
Backup Issues
Customers who have large amounts of historical purchase order data report that backup time is unacceptable.
Search Issues
Users report that when they search product names, the search results exclude product names that contain accents, unless the search string includes the accent.
Missing Data Issues
Customers report that when they make a price change in the Products table, they cannot retrieve the price that the item was sold for in previous orders.
Query Performance Issues
Customers report that query performance degrades very quickly. Additionally, the customers report that users cannot run queries when SQL Server runs maintenance tasks.
Import Issues During the monthly import process, database administrators receive many supports call from users who report that they cannot access the supplier data. The database administrators want to reduce the amount of time required to import the data.
Design Requirements
File Storage Requirements
The ERP database stores scanned documents that are larger than 2 MB. These files must only be accessed through the ERP application. File access must have the best possible read and write performance.
Data Recovery Requirements
If the import process fails, the database must be returned to its prior state immediately.
Security Requirements
You must provide users with the ability to execute functions within the ERP application, without having direct access to the underlying tables.
Concurrency Requirements
You must reduce the likelihood of deadlocks occurring when Sales.Prod and Sales.Proc2 execute.
You need to recommend which statement should be used to update SalesOrder.
How should you recommend completing the statement? To answer, drag the appropriate elements to the correct locations. Each element may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
Answer:
Explanation:
NEW QUESTION: 2
On January 2, 1993, Quo, Inc. hired Reed to be its controller. During the year, Reed, working closely with Quo's president and outside accountants, made changes in accounting policies, corrected several errors dating from 1992 and before, and instituted new accounting policies.
Quo's 1993 financial statements will be presented in comparative form with its 1992 financial statements.
This question represents one of Quo's transactions. List B represents the general accounting treatment required for these transactions. These treatments are:
* Cumulative effect approach - Include the cumulative effect of the adjustment resulting from the accounting change or error correction in the 1993 financial statements, and do not restate the 1992 financial statements.
* Retroactive or retrospective restatement approach - Restate the 1992 financial statements and adjust 1992 beginning retained earnings if the error or change affects a period prior to 1992.
* Prospective approach - Report 1993 and future financial statements on the new basis but do not restate 1992 financial statements.
Item to Be Answered
The equipment that Quo manufactures is sold with a five-year warranty. Because of a production breakthrough, Quo reduced its computation of warranty costs from 3% of sales to 1% of sales.
List B (Select one)
A. Prospective approach.
B. Cumulative effect approach.
C. Retroactive or retrospective restatement approach.
Answer: A
NEW QUESTION: 3
For each intermediate key, each reducer task can emit:
A. As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.
B. As many final key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
C. One final key-value pair per key; no restrictions on the type.
D. As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
E. One final key-value pair per value associated with the key; no restrictions on the type.
Answer: C
Explanation:
Reducer reduces a set of intermediate values which share a key to a smaller set of values.
Reducing lets you aggregate values together. A reducer function receives an iterator of input values from an input list. It then combines these values together, returning a single output value.
Reference: Hadoop Map-Reduce Tutorial; Yahoo! Hadoop Tutorial, Module 4: MapReduce
NEW QUESTION: 4
Which of the following can a manager use from the Team Overview tab? Note: There are 2 correct answers to
this question?
A. The Get Feedback feature to collect additional comments on the form
B. The Stack Ranker to evaluate competencies for their direct reports
C. The Stack Ranker to evaluate objectives for their direct reports
D. The Ask Feedback button to send an email to internal or external users
Answer: A,D
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