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NEW QUESTION: 1
Which of the below choices are needed for Quick Discovery? (Choose two.)
A. Target IP
B. PID
C. MID Server
D. Discovery Schedule
Answer: C,D

NEW QUESTION: 2
Overview
General Overview
ADatum Corporation has offices in Miami and Montreal.
The network contains a single Active Directory forest named adatum.com. The offices connect to each other by using a WAN link that has 5-ms latency. A: Datum standardizes its database platform by using SQL Server
2014 Enterprise edition.
Databases
Each office contains databases named Sales, Inventory, Customers, Products, Personnel, and Dev.
Servers and databases are managed by a team of database administrators. Currently, all of the database administrators have the same level of permissions on all of the servers and all of the databases.
The Customers database contains two tables named Customers and Classifications.
The following graphic shows the relevant portions of the tables:

The following table shows the current data in the Classifications table:

The Inventory database is updated frequently.
The database is often used for reporting.
A full backup of the database currently takes three hours to complete.
Stored Procedures
A stored procedure named USP_1 generates millions of rows of data for multiple reports. USP_1 combines data from five different tables from the Sales and Customers databases in a table named Table1.
After Table1 is created, the reporting process reads data from Table1 sequentially several times. After the process is complete, Table1 is deleted.
A stored procedure named USP_2 is used to generate a product list. The product list contains the names of products grouped by category.
USP_2 takes several minutes to run due to locks on the tables the procedure accesses. The locks are caused by USP_1 and USP_3.
A stored procedure named USP_3 is used to update prices. USP_3 is composed of several UPDATE statements called in sequence from within a transaction.
Currently, if one of the UPDATE statements fails, the stored procedure fails. A stored procedure named USP_4 calls stored procedures in the Sales, Customers, and Inventory databases.
The nested stored procedures read tables from the Sales, Customers, and Inventory databases. USP_4 uses an EXECUTE AS clause.
All nested stored procedures handle errors by using structured exception handling. A stored procedure named USP_5 calls several stored procedures in the same database. Security checks are performed each time USP_5 calls a stored procedure.
You suspect that the security checks are slowing down the performance of USP_5. All stored procedures accessed by user applications call nested stored procedures.
The nested stored procedures are never called directly.
Design Requirements
Data Recovery
You must be able to recover data from the Inventory database if a storage failure occurs. You have a Recovery Time Objective (RTO) of 5 minutes.
You must be able to recover data from the Dev database if data is lost accidentally. You have a Recovery Point Objective (RPO) of one day.
Classification Changes
You plan to change the way customers are classified. The new classifications will have four levels based on the number of orders. Classifications may be removed or added in the future. Management requests that historical data be maintained for the previous classifications. Security A group of junior database administrators must be able to manage security for the Sales database. The junior database administrators will not have any other administrative rights. A: Datum wants to track which users run each stored procedure.
Storage
ADatum has limited storage. Whenever possible, all storage space should be minimized for all databases and all backups.
Error Handling
There is currently no error handling code in any stored procedure.
You plan to log errors in called stored procedures and nested stored procedures. Nested stored procedures are never called directly.
You need to recommend a solution to minimize the amount of time it takes to execute USP_5. What should you include in the recommendation?
A. Enable cross-database chaining.
B. Use a server role to group all logins.
C. Copy USP.5 to each database.
D. Use the EXECUTE AS clause in USP_5.
Answer: A
Explanation:
Explanation
Scenario:
A stored procedure named USP_5 changes data in multiple databases. Security checks are performed each time USP_5 accesses a database.
- Cross-database ownership chaining occurs when a procedure in one database depends on objects in another database. A cross-database ownership chain works in the same way as ownership chaining within a single database, except that an unbroken ownership chain requires that all the object owners are mapped to the same login account. If the source object in the source database and the target objects in the target databases are owned by the same login account, SQL Server does not check permissions on the target objects.

NEW QUESTION: 3
MapReduce v2 (MRv2/YARN) is designed to address which two issues?
A. Ability to run frameworks other than MapReduce, such as MPI.
B. HDFS latency.
C. Reduce complexity of the MapReduce APIs.
D. Single point of failure in the NameNode.
E. Resource pressure on the JobTracker.
F. Standardize on a single MapReduce API.
Answer: A,E
Explanation:
YARN (Yet Another Resource Negotiator), as an aspect of Hadoop, has two major kinds of benefits:
*(D) The ability to use programming frameworks other than MapReduce. / MPI (Message Passing Interface) was mentioned as a paradigmatic example of a MapReduce alternative
*Scalability, no matter what programming framework you use.
Note:
*The fundamental idea of MRv2 is to split up the two major functionalities of the JobTracker, resource management and job scheduling/monitoring, into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM). An application is either a single job in the classical sense of Map-Reduce jobs or a DAG of jobs.
*(B) The central goal of YARN is to clearly separate two things that are unfortunately smushed together in current Hadoop, specifically in (mainly) JobTracker:
/ Monitoring the status of the cluster with respect to which nodes have which resources available. Under YARN, this will be global. / Managing the parallelization execution of any specific job. Under YARN, this will be done separately for each job. The current Hadoop MapReduce system is fairly scalable - Yahoo runs 5000 Hadoop jobs, truly concurrently, on a single cluster, for a total 1.5 - 2 millions jobs/cluster/month. Still, YARN will remove scalability bottlenecks
Reference: Apache Hadoop YARN - Concepts & Applications

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