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NEW QUESTION: 1
Which two statements are true regarding configuring an Identity Provider Instance within Workspace Portal? (Choose two.)
A. Workspace Portal natively supports Kerberos, RSA SecurID, and Smart-card authentication types.
B. The Meta-data XML enables Workspace Portal to automatically receive the metadata of the Third-Party Identity Provider Instance.
C. The Configure Via option is only available when you add a third-party identity provider instance.
D. Third-party Identity Provider Instances must be SAML 2.0 compliant.
Answer: C,D

NEW QUESTION: 2
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
You are not permitted to make changes to the client applications.
You need to optimize the storage for the data warehouse.
What change should you make?
A. Partition the Fact.Order table, and move historical data to new filegroups on lower-cost storage.
B. Create new tables on lower-cost storage, move the historical data to the new tables, and then shrink the database.
C. Remove the historical data from the database to leave available space for new data.
D. Move historical data to new tables on lower-cost storage.
Answer: A
Explanation:
Explanation
Create the load staging table in the same filegroup as the partition you are loading.
Create the unload staging table in the same filegroup as the partition you are deleteing.
From scenario: Data older than one year is accessed infrequently and is considered historical.
References:
https://blogs.msdn.microsoft.com/sqlcat/2013/09/16/top-10-best-practices-for-building-a-large-scale-relational-d

NEW QUESTION: 3
Ein Informationssicherheitsmanager entwickelt eine neue Informationssicherheitsstrategie. Welche der folgenden Funktionen würde als BESTE Ressource dienen, um die Strategie zu überprüfen und Leitlinien für die Geschäftsausrichtung bereitzustellen?
A. Der Lenkungsausschuss
B. Interne Revision
C. Der Verwaltungsrat
D. Die Rechtsabteilung
Answer: A

NEW QUESTION: 4
A combiner reduces:
A. The amount of intermediate data that must be transferred between the mapper and reducer.
B. The number of values across different keys in the iterator supplied to a single reduce method call.
C. The number of input files a mapper must process.
D. The number of output files a reducer must produce.
Answer: A
Explanation:
Combiners are used to increase the efficiency of a MapReduce program. They are used to aggregate intermediate map output locally on individual mapper outputs. Combiners can help you reduce the amount of data that needs to be transferred across to the reducers. You can use your reducer code as a combiner if the operation performed is commutative and associative. The execution of combiner is not guaranteed, Hadoop may or may not execute a combiner. Also, if required it may execute it more then 1 times. Therefore your MapReduce jobs should not depend on the combiners execution.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, What are combiners? When should I use a combiner in my MapReduce Job?