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NEW QUESTION: 1
Which of the following statement about the OSPF backbone area is correct?
A. All routers in the backbone area are ABR
B. All areas can be backbone areas
C. Area 0 is the backbone area.
D. The backbone area must be deployed when the number of routers running OSPF exceeds two.
Answer: C

NEW QUESTION: 2
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 a solution that resolves the missing data issue.
The solution must minimize the amount of development effort. What should you recommend?
A. Normalize the OrderDetails table.
B. Normalize the Products table.
C. Denormalize the OrderDetails table.
D. Denormalize the Products table.
Answer: B
Explanation:
Explanation
- Scenario:
- 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.
- 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.

NEW QUESTION: 3
Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data?
A. Pig
B. HBase
C. Hive
D. Sqoop
E. Flume
F. Oozie
G. Hue
Answer: B
Explanation:
Use Apache HBase when you need random, realtime read/write access to your Big
Data.
Note: This project's goal is the hosting of very large tables -- billions of rows X millions of columns
-- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned,
column-oriented store modeled after Google's Bigtable: A Distributed Storage System for
Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided
by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop
and HDFS.
Features
Linear and modular scalability.
Strictly consistent reads and writes.
Automatic and configurable sharding of tables
Automatic failover support between RegionServers.
Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables.
Easy to use Java API for client access.
Block cache and Bloom Filters for real-time queries.
Query predicate push down via server side Filters
Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data
encoding options
Extensible jruby-based (JIRB) shell
Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX
Reference: http://hbase.apache.org/ (when would I use HBase? First sentence)